Author: zhichao.li <zhichao.li@intel.com>
Closes#7709 from zhichao-li/translate and squashes the following commits:
9418088 [zhichao.li] refine checking condition
f2ab77a [zhichao.li] clone string
9d88f2d [zhichao.li] fix indent
6aa2962 [zhichao.li] style
e575ead [zhichao.li] add python api
9d4bab0 [zhichao.li] add special case for fodable and refactor unittest
eda7ad6 [zhichao.li] update to use TernaryExpression
cdfd4be [zhichao.li] add function translate
https://issues.apache.org/jira/browse/SPARK-9664
Author: Yin Huai <yhuai@databricks.com>
Closes#7982 from yhuai/udafRegister and squashes the following commits:
0cc2287 [Yin Huai] Remove UDAFRegistration and add apply to UserDefinedAggregateFunction.
The new aggregate replaces the old GeneratedAggregate.
Author: Reynold Xin <rxin@databricks.com>
Closes#7983 from rxin/remove-generated-agg and squashes the following commits:
8334aae [Reynold Xin] [SPARK-9674][SQL] Remove GeneratedAggregate.
This PR is a fork of PR #5733 authored by chenghao-intel. For committers who's going to merge this PR, please set the author to "Cheng Hao <hao.chengintel.com>".
----
When a data source relation meets the following requirements, we persist it in Hive compatible format, so that other systems like Hive can access it:
1. It's a `HadoopFsRelation`
2. It has only one input path
3. It's non-partitioned
4. It's data source provider can be naturally mapped to a Hive builtin SerDe (e.g. ORC and Parquet)
Author: Cheng Lian <lian@databricks.com>
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7967 from liancheng/spark-6923/refactoring-pr-5733 and squashes the following commits:
5175ee6 [Cheng Lian] Fixes an oudated comment
3870166 [Cheng Lian] Fixes build error and comments
864acee [Cheng Lian] Refactors PR #5733
3490cdc [Cheng Hao] update the scaladoc
6f57669 [Cheng Hao] write schema info to hivemetastore for data source
This PR has the following three small fixes.
1. UnsafeKVExternalSorter does not use 0 as the initialSize to create an UnsafeInMemorySorter if its BytesToBytesMap is empty.
2. We will not not spill a InMemorySorter if it is empty.
3. We will not add a SpillReader to a SpillMerger if this SpillReader is empty.
JIRA: https://issues.apache.org/jira/browse/SPARK-9611
Author: Yin Huai <yhuai@databricks.com>
Closes#7948 from yhuai/unsafeEmptyMap and squashes the following commits:
9727abe [Yin Huai] Address Josh's comments.
34b6f76 [Yin Huai] 1. UnsafeKVExternalSorter does not use 0 as the initialSize to create an UnsafeInMemorySorter if its BytesToBytesMap is empty. 2. Do not spill a InMemorySorter if it is empty. 3. Do not add spill to SpillMerger if this spill is empty.
This patches renames `RowOrdering` to `InterpretedOrdering` and updates SortMergeJoin to use the `SparkPlan` methods for constructing its ordering so that it may benefit from codegen.
This is an updated version of #7408.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7973 from JoshRosen/SPARK-9054 and squashes the following commits:
e610655 [Josh Rosen] Add comment RE: Ascending ordering
34b8e0c [Josh Rosen] Import ordering
be19a0f [Josh Rosen] [SPARK-9054] [SQL] Rename RowOrdering to InterpretedOrdering; use newOrdering in more places.
This continues tarekauel's work in #7778.
Author: Liang-Chi Hsieh <viirya@appier.com>
Author: Tarek Auel <tarek.auel@googlemail.com>
Closes#7893 from viirya/codegen_in and squashes the following commits:
81ff97b [Liang-Chi Hsieh] For comments.
47761c6 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into codegen_in
cf4bf41 [Liang-Chi Hsieh] For comments.
f532b3c [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into codegen_in
446bbcd [Liang-Chi Hsieh] Fix bug.
b3d0ab4 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into codegen_in
4610eff [Liang-Chi Hsieh] Relax the types of references and update optimizer test.
224f18e [Liang-Chi Hsieh] Beef up the test cases for In and InSet to include all primitive data types.
86dc8aa [Liang-Chi Hsieh] Only convert In to InSet when the number of items in set is more than the threshold.
b7ded7e [Tarek Auel] [SPARK-9403][SQL] codeGen in / inSet
Currently we collapse successive projections that are added by `withColumn`. However, this optimization violates the constraint that adding nodes to a plan will never change its analyzed form and thus breaks caching. Instead of doing early optimization, in this PR I just fix some low-hanging slowness in the analyzer. In particular, I add a mechanism for skipping already analyzed subplans, `resolveOperators` and `resolveExpression`. Since trees are generally immutable after construction, it's safe to annotate a plan as already analyzed as any transformation will create a new tree with this bit no longer set.
Together these result in a faster analyzer than before, even with added timing instrumentation.
```
Original Code
[info] 3430ms
[info] 2205ms
[info] 1973ms
[info] 1982ms
[info] 1916ms
Without Project Collapsing in DataFrame
[info] 44610ms
[info] 45977ms
[info] 46423ms
[info] 46306ms
[info] 54723ms
With analyzer optimizations
[info] 6394ms
[info] 4630ms
[info] 4388ms
[info] 4093ms
[info] 4113ms
With resolveOperators
[info] 2495ms
[info] 1380ms
[info] 1685ms
[info] 1414ms
[info] 1240ms
```
Author: Michael Armbrust <michael@databricks.com>
Closes#7920 from marmbrus/withColumnCache and squashes the following commits:
2145031 [Michael Armbrust] fix hive udfs tests
5a5a525 [Michael Armbrust] remove wrong comment
7a507d5 [Michael Armbrust] style
b59d710 [Michael Armbrust] revert small change
1fa5949 [Michael Armbrust] move logic into LogicalPlan, add tests
0e2cb43 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into withColumnCache
c926e24 [Michael Armbrust] naming
e593a2d [Michael Armbrust] style
f5a929e [Michael Armbrust] [SPARK-9141][SQL] Remove project collapsing from DataFrame API
38b1c83 [Michael Armbrust] WIP
Support partitioning for the JSON data source.
Still 2 open issues for the `HadoopFsRelation`
- `refresh()` will invoke the `discoveryPartition()`, which will auto infer the data type for the partition columns, and maybe conflict with the given partition columns. (TODO enable `HadoopFsRelationSuite.Partition column type casting"
- When insert data into a cached HadoopFsRelation based table, we need to invalidate the cache after the insertion (TODO enable `InsertSuite.Caching`)
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7696 from chenghao-intel/json and squashes the following commits:
d90b104 [Cheng Hao] revert the change for JacksonGenerator.apply
307111d [Cheng Hao] fix bug in the unit test
8738c8a [Cheng Hao] fix bug in unit testing
35f2cde [Cheng Hao] support partition for json format
The user specified schema is currently ignored when loading Parquet files.
One workaround is to use the `format` and `load` methods instead of `parquet`, e.g.:
```
val schema = ???
// schema is ignored
sqlContext.read.schema(schema).parquet("hdfs:///test")
// schema is retained
sqlContext.read.schema(schema).format("parquet").load("hdfs:///test")
```
The fix is simple, but I wonder if the `parquet` method should instead be written in a similar fashion to `orc`:
```
def parquet(path: String): DataFrame = format("parquet").load(path)
```
Author: Nathan Howell <nhowell@godaddy.com>
Closes#7947 from NathanHowell/SPARK-9618 and squashes the following commits:
d1ea62c [Nathan Howell] [SPARK-9618] [SQL] Use the specified schema when reading Parquet files
This PR includes the following changes:
### SPARK-8862: Add basic instrumentation to each SparkPlan operator
A SparkPlan can override `def accumulators: Map[String, Accumulator[_]]` to expose its metrics that can be displayed in UI. The UI will use them to track the updates and show them in the web page in real-time.
### SparkSQLExecution and SQLSparkListener
`SparkSQLExecution.withNewExecutionId` will set `spark.sql.execution.id` to the local properties so that we can use it to track all jobs that belong to the same query.
SQLSparkListener is a listener to track all accumulator updates of all tasks for a query. It receives them from heartbeats can the UI can query them in real-time.
When running a query, `SQLSparkListener.onExecutionStart` will be called. When a query is finished, `SQLSparkListener.onExecutionEnd` will be called. And the Spark jobs with the same execution id will be tracked and stored with this query.
`SQLSparkListener` has to store all accumulator updates for tasks separately. When a task fails and starts to retry, we need to drop the old accumulator updates. Because we can not revert our changes to an accumulator, we have to maintain these accumulator updates by ourselves so as to drop accumulator updates for a failed task.
### SPARK-8862: A new SQL tab
Includes two pages:
#### A page for all DataFrame/SQL queries
It will show the running, completed and failed queries in 3 tables. It also displays the jobs and their links for a query in each row.
#### A detail page for a DataFrame/SQL query
In this page, it also shows the SparkPlan metrics in real-time. Run a long-running query, such as
```
val testData = sc.parallelize((1 to 1000000).map(i => (i, i.toString))).toDF()
testData.select($"_1").filter($"_1" < 1000).foreach(_ => Thread.sleep(60))
```
and you will see the metrics keep updating in real-time.
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Author: zsxwing <zsxwing@gmail.com>
Closes#7774 from zsxwing/sql-ui and squashes the following commits:
5a2bc99 [zsxwing] Remove UISeleniumSuite and its dependency
57d4cd2 [zsxwing] Use VisibleForTesting annotation
cc1c736 [zsxwing] Add SparkPlan.trackNumOfRowsEnabled to make subclasses easy to track the number of rows; fix the issue that the "save" action cannot collect metrics
3771ab0 [zsxwing] Register SQL metrics accmulators
3a101c0 [zsxwing] Change prepareCalled's type to AtomicBoolean for thread-safety
b8d5605 [zsxwing] Make prepare idempotent; call children's prepare in SparkPlan.prepare; change doPrepare to def
4ed11a1 [zsxwing] var -> val
332639c [zsxwing] Ignore UISeleniumSuite and SQLListenerSuite."no memory leak" because of SPARK-9580
bb52359 [zsxwing] Address other commens in SQLListener
c4d0f5d [zsxwing] Move newPredicate out of the iterator loop
957473c [zsxwing] Move STATIC_RESOURCE_DIR to object SQLTab
7ab4816 [zsxwing] Make SparkPlan accumulator API private[sql]
dae195e [zsxwing] Fix the code style and comments
3a66207 [zsxwing] Ignore irrelevant accumulators
b8484a1 [zsxwing] Merge branch 'master' into sql-ui
9406592 [zsxwing] Implement the SparkPlan viz
4ebce68 [zsxwing] Add SparkPlan.prepare to support BroadcastHashJoin to run background work in parallel
ca1811f [zsxwing] Merge branch 'master' into sql-ui
fef6fc6 [zsxwing] Fix a corner case
25f335c [zsxwing] Fix the code style
6eae828 [zsxwing] SQLSparkListener -> SQLListener; SparkSQLExecutionUIData -> SQLExecutionUIData; SparkSQLExecution -> SQLExecution
822af75 [zsxwing] Add SQLSparkListenerSuite and fix the issue about onExecutionEnd and onJobEnd
6be626f [zsxwing] Add UISeleniumSuite to test UI
d02a24d [zsxwing] Make ExecutionPage private
23abf73 [zsxwing] [SPARK-8862][SPARK-8862][SQL] Add basic instrumentation to each SparkPlan operator and add a new SQL tab
The current implementation of UnsafeExternalSort uses NoOpPrefixComparator for binary-typed data.
So, we need to add BinaryPrefixComparator in PrefixComparators.
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes#7676 from maropu/BinaryTypePrefixComparator and squashes the following commits:
fe6f31b [Takeshi YAMAMURO] Apply comments
d943c04 [Takeshi YAMAMURO] Add a codegen'd entry for BinaryType in SortPrefix
ecf3ac5 [Takeshi YAMAMURO] Support BinaryType in PrefixComparator
Let Decimal carry the correct precision and scale with DecimalType.
cc rxin yhuai
Author: Davies Liu <davies@databricks.com>
Closes#7925 from davies/decimal_scale and squashes the following commits:
e19701a [Davies Liu] some tweaks
57d78d2 [Davies Liu] fix tests
5d5bc69 [Davies Liu] match precision and scale with DecimalType
This PR is based on #7580 , thanks to EntilZha
PR for work on https://issues.apache.org/jira/browse/SPARK-8231
Currently, I have an initial implementation for contains. Based on discussion on JIRA, it should behave same as Hive: https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFArrayContains.java#L102-L128
Main points are:
1. If the array is empty, null, or the value is null, return false
2. If there is a type mismatch, throw error
3. If comparison is not supported, throw error
Closes#7580
Author: Pedro Rodriguez <prodriguez@trulia.com>
Author: Pedro Rodriguez <ski.rodriguez@gmail.com>
Author: Davies Liu <davies@databricks.com>
Closes#7949 from davies/array_contains and squashes the following commits:
d3c08bc [Davies Liu] use foreach() to avoid copy
bc3d1fe [Davies Liu] fix array_contains
719e37d [Davies Liu] Merge branch 'master' of github.com:apache/spark into array_contains
e352cf9 [Pedro Rodriguez] fixed diff from master
4d5b0ff [Pedro Rodriguez] added docs and another type check
ffc0591 [Pedro Rodriguez] fixed unit test
7a22deb [Pedro Rodriguez] Changed test to use strings instead of long/ints which are different between python 2 an 3
b5ffae8 [Pedro Rodriguez] fixed pyspark test
4e7dce3 [Pedro Rodriguez] added more docs
3082399 [Pedro Rodriguez] fixed unit test
46f9789 [Pedro Rodriguez] reverted change
d3ca013 [Pedro Rodriguez] Fixed type checking to match hive behavior, then added tests to insure this
8528027 [Pedro Rodriguez] added more tests
686e029 [Pedro Rodriguez] fix scala style
d262e9d [Pedro Rodriguez] reworked type checking code and added more tests
2517a58 [Pedro Rodriguez] removed unused import
28b4f71 [Pedro Rodriguez] fixed bug with type conversions and re-added tests
12f8795 [Pedro Rodriguez] fix scala style checks
e8a20a9 [Pedro Rodriguez] added python df (broken atm)
65b562c [Pedro Rodriguez] made array_contains nullable false
33b45aa [Pedro Rodriguez] reordered test
9623c64 [Pedro Rodriguez] fixed test
4b4425b [Pedro Rodriguez] changed Arrays in tests to Seqs
72cb4b1 [Pedro Rodriguez] added checkInputTypes and docs
69c46fb [Pedro Rodriguez] added tests and codegen
9e0bfc4 [Pedro Rodriguez] initial attempt at implementation
This adds Python API for those DataFrame functions that is introduced in 1.5.
There is issue with serialize byte_array in Python 3, so some of functions (for BinaryType) does not have tests.
cc rxin
Author: Davies Liu <davies@databricks.com>
Closes#7922 from davies/python_functions and squashes the following commits:
8ad942f [Davies Liu] fix test
5fb6ec3 [Davies Liu] fix bugs
3495ed3 [Davies Liu] fix issues
ea5f7bb [Davies Liu] Add python API for DataFrame functions
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7932 from cloud-fan/generic-getter and squashes the following commits:
c60de4c [Wenchen Fan] do not expose generic getter in internal row
This patch extends UnsafeExternalSorter to support records larger than the page size. The basic strategy is the same as in #7762: store large records in their own overflow pages.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7891 from JoshRosen/large-records-in-sql-sorter and squashes the following commits:
967580b [Josh Rosen] Merge remote-tracking branch 'origin/master' into large-records-in-sql-sorter
948c344 [Josh Rosen] Add large records tests for KV sorter.
3c17288 [Josh Rosen] Combine memory and disk cleanup into general cleanupResources() method
380f217 [Josh Rosen] Merge remote-tracking branch 'origin/master' into large-records-in-sql-sorter
27eafa0 [Josh Rosen] Fix page size in PackedRecordPointerSuite
a49baef [Josh Rosen] Address initial round of review comments
3edb931 [Josh Rosen] Remove accidentally-committed debug statements.
2b164e2 [Josh Rosen] Support large records in UnsafeExternalSorter.
This is based on #7485 , thanks to NathanHowell
Tests were copied from Hive, but do not seem to be super comprehensive. I've generally replicated Hive's unusual behavior rather than following a JSONPath reference, except for one case (as noted in the comments). I don't know if there is a way of fully replicating Hive's behavior without a slower TreeNode implementation, so I've erred on the side of performance instead.
Author: Davies Liu <davies@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Author: Nathan Howell <nhowell@godaddy.com>
Closes#7901 from davies/get_json_object and squashes the following commits:
3ace9b9 [Davies Liu] Merge branch 'get_json_object' of github.com:davies/spark into get_json_object
98766fc [Davies Liu] Merge branch 'master' of github.com:apache/spark into get_json_object
a7dc6d0 [Davies Liu] Update JsonExpressionsSuite.scala
c818519 [Yin Huai] new results.
18ce26b [Davies Liu] fix tests
6ac29fb [Yin Huai] Golden files.
25eebef [Davies Liu] use HiveQuerySuite
e0ac6ec [Yin Huai] Golden answer files.
940c060 [Davies Liu] tweat code style
44084c5 [Davies Liu] Merge branch 'master' of github.com:apache/spark into get_json_object
9192d09 [Nathan Howell] Match Hive’s behavior for unwrapping arrays of one element
8dab647 [Nathan Howell] [SPARK-8246] [SQL] Implement get_json_object
This PR is based on #7186 (just fix the conflict), thanks to tarekauel .
find_in_set(string str, string strList): int
Returns the first occurance of str in strList where strList is a comma-delimited string. Returns null if either argument is null. Returns 0 if the first argument contains any commas. For example, find_in_set('ab', 'abc,b,ab,c,def') returns 3.
Only add this to SQL, not DataFrame.
Closes#7186
Author: Tarek Auel <tarek.auel@googlemail.com>
Author: Davies Liu <davies@databricks.com>
Closes#7900 from davies/find_in_set and squashes the following commits:
4334209 [Davies Liu] Merge branch 'master' of github.com:apache/spark into find_in_set
8f00572 [Davies Liu] Merge branch 'master' of github.com:apache/spark into find_in_set
243ede4 [Tarek Auel] [SPARK-8244][SQL] hive compatibility
1aaf64e [Tarek Auel] [SPARK-8244][SQL] unit test fix
e4093a4 [Tarek Auel] [SPARK-8244][SQL] final modifier for COMMA_UTF8
0d05df5 [Tarek Auel] Merge branch 'master' into SPARK-8244
208d710 [Tarek Auel] [SPARK-8244] address comments & bug fix
71b2e69 [Tarek Auel] [SPARK-8244] find_in_set
66c7fda [Tarek Auel] Merge branch 'master' into SPARK-8244
61b8ca2 [Tarek Auel] [SPARK-8224] removed loop and split; use unsafe String comparison
4f75a65 [Tarek Auel] Merge branch 'master' into SPARK-8244
e3b20c8 [Tarek Auel] [SPARK-8244] added type check
1c2bbb7 [Tarek Auel] [SPARK-8244] findInSet
Enable most javac lint warnings; fix a lot of build warnings. In a few cases, touch up surrounding code in the process.
I'll explain several of the changes inline in comments.
Author: Sean Owen <sowen@cloudera.com>
Closes#7862 from srowen/SPARK-9534 and squashes the following commits:
ea51618 [Sean Owen] Enable most javac lint warnings; fix a lot of build warnings. In a few cases, touch up surrounding code in the process.
We often return abstract iterator types in various sort-related classes (e.g. UnsafeKVExternalSorter). It is actually better to return a more concrete type, so the callsite uses that type and JIT can inline the iterator calls.
Author: Reynold Xin <rxin@databricks.com>
Closes#7911 from rxin/surface-concrete-type and squashes the following commits:
0422add [Reynold Xin] [SPARK-9577][SQL] Surface concrete iterator types in various sort classes.
Cherry picked the parts of the initial SPARK-8064 WiP branch needed to get sql/hive to compile against hive 1.2.1. That's the ASF release packaged under org.apache.hive, not any fork.
Tests not run yet: that's what the machines are for
Author: Steve Loughran <stevel@hortonworks.com>
Author: Cheng Lian <lian@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Author: Patrick Wendell <patrick@databricks.com>
Closes#7191 from steveloughran/stevel/feature/SPARK-8064-hive-1.2-002 and squashes the following commits:
7556d85 [Cheng Lian] Updates .q files and corresponding golden files
ef4af62 [Steve Loughran] Merge commit '6a92bb09f46a04d6cd8c41bdba3ecb727ebb9030' into stevel/feature/SPARK-8064-hive-1.2-002
6a92bb0 [Cheng Lian] Overrides HiveConf time vars
dcbb391 [Cheng Lian] Adds com.twitter:parquet-hadoop-bundle:1.6.0 for Hive Parquet SerDe
0bbe475 [Steve Loughran] SPARK-8064 scalastyle rejects the standard Hadoop ASF license header...
fdf759b [Steve Loughran] SPARK-8064 classpath dependency suite to be in sync with shading in final (?) hive-exec spark
7a6c727 [Steve Loughran] SPARK-8064 switch to second staging repo of the spark-hive artifacts. This one has the protobuf-shaded hive-exec jar
376c003 [Steve Loughran] SPARK-8064 purge duplicate protobuf declaration
2c74697 [Steve Loughran] SPARK-8064 switch to the protobuf shaded hive-exec jar with tests to chase it down
cc44020 [Steve Loughran] SPARK-8064 remove hadoop.version from runtest.py, as profile will fix that automatically.
6901fa9 [Steve Loughran] SPARK-8064 explicit protobuf import
da310dc [Michael Armbrust] Fixes for Hive tests.
a775a75 [Steve Loughran] SPARK-8064 cherry-pick-incomplete
7404f34 [Patrick Wendell] Add spark-hive staging repo
832c164 [Steve Loughran] SPARK-8064 try to supress compiler warnings on Complex.java pasted-thrift-code
312c0d4 [Steve Loughran] SPARK-8064 maven/ivy dependency purge; calcite declaration needed
fa5ae7b [Steve Loughran] HIVE-8064 fix up hive-thriftserver dependencies and cut back on evicted references in the hive- packages; this keeps mvn and ivy resolution compatible, as the reconciliation policy is "by hand"
c188048 [Steve Loughran] SPARK-8064 manage the Hive depencencies to that -things that aren't needed are excluded -sql/hive built with ivy is in sync with the maven reconciliation policy, rather than latest-first
4c8be8d [Cheng Lian] WIP: Partial fix for Thrift server and CLI tests
314eb3c [Steve Loughran] SPARK-8064 deprecation warning noise in one of the tests
17b0341 [Steve Loughran] SPARK-8064 IDE-hinted cleanups of Complex.java to reduce compiler warnings. It's all autogenerated code, so still ugly.
d029b92 [Steve Loughran] SPARK-8064 rely on unescaping to have already taken place, so go straight to map of serde options
23eca7e [Steve Loughran] HIVE-8064 handle raw and escaped property tokens
54d9b06 [Steve Loughran] SPARK-8064 fix compilation regression surfacing from rebase
0b12d5f [Steve Loughran] HIVE-8064 use subset of hive complex type whose types deserialize
fce73b6 [Steve Loughran] SPARK-8064 poms rely implicitly on the version of kryo chill provides
fd3aa5d [Steve Loughran] SPARK-8064 version of hive to d/l from ivy is 1.2.1
dc73ece [Steve Loughran] SPARK-8064 revert to master's determinstic pushdown strategy
d3c1e4a [Steve Loughran] SPARK-8064 purge UnionType
051cc21 [Steve Loughran] SPARK-8064 switch to an unshaded version of hive-exec-core, which must have been built with Kryo 2.21. This currently looks for a (locally built) version 1.2.1.spark
6684c60 [Steve Loughran] SPARK-8064 ignore RTE raised in blocking process.exitValue() call
e6121e5 [Steve Loughran] SPARK-8064 address review comments
aa43dc6 [Steve Loughran] SPARK-8064 more robust teardown on JavaMetastoreDatasourcesSuite
f2bff01 [Steve Loughran] SPARK-8064 better takeup of asynchronously caught error text
8b1ef38 [Steve Loughran] SPARK-8064: on failures executing spark-submit in HiveSparkSubmitSuite, print command line and all logged output.
5a9ce6b [Steve Loughran] SPARK-8064 add explicit reason for kv split failure, rather than array OOB. *does not address the issue*
642b63a [Steve Loughran] SPARK-8064 reinstate something cut briefly during rebasing
97194dc [Steve Loughran] SPARK-8064 add extra logging to the YarnClusterSuite classpath test. There should be no reason why this is failing on jenkins, but as it is (and presumably its CP-related), improve the logging including any exception raised.
335357f [Steve Loughran] SPARK-8064 fail fast on thrive process spawning tests on exit codes and/or error string patterns seen in log.
3ed872f [Steve Loughran] SPARK-8064 rename field double to dbl
bca55e5 [Steve Loughran] SPARK-8064 missed one of the `date` escapes
41d6479 [Steve Loughran] SPARK-8064 wrap tests with withTable() calls to avoid table-exists exceptions
2bc29a4 [Steve Loughran] SPARK-8064 ParquetSuites to escape `date` field name
1ab9bc4 [Steve Loughran] SPARK-8064 TestHive to use sered2.thrift.test.Complex
bf3a249 [Steve Loughran] SPARK-8064: more resubmit than fix; tighten startup timeout to 60s. Still no obvious reason why jersey server code in spark-assembly isn't being picked up -it hasn't been shaded
c829b8f [Steve Loughran] SPARK-8064: reinstate yarn-rm-server dependencies to hive-exec to ensure that jersey server is on classpath on hadoop versions < 2.6
0b0f738 [Steve Loughran] SPARK-8064: thrift server startup to fail fast on any exception in the main thread
13abaf1 [Steve Loughran] SPARK-8064 Hive compatibilty tests sin sync with explain/show output from Hive 1.2.1
d14d5ea [Steve Loughran] SPARK-8064: DATE is now a predicate; you can't use it as a field in select ops
26eef1c [Steve Loughran] SPARK-8064: HIVE-9039 renamed TOK_UNION => TOK_UNIONALL while adding TOK_UNIONDISTINCT
3d64523 [Steve Loughran] SPARK-8064 improve diagns on uknown token; fix scalastyle failure
d0360f6 [Steve Loughran] SPARK-8064: delicate merge in of the branch vanzin/hive-1.1
1126e5a [Steve Loughran] SPARK-8064: name of unrecognized file format wasn't appearing in error text
8cb09c4 [Steve Loughran] SPARK-8064: test resilience/assertion improvements. Independent of the rest of the work; can be backported to earlier versions
dec12cb [Steve Loughran] SPARK-8064: when a CLI suite test fails include the full output text in the raised exception; this ensures that the stdout/stderr is included in jenkins reports, so it becomes possible to diagnose the cause.
463a670 [Steve Loughran] SPARK-8064 run-tests.py adds a hadoop-2.6 profile, and changes info messages to say "w/Hive 1.2.1" in console output
2531099 [Steve Loughran] SPARK-8064 successful attempt to get rid of pentaho as a transitive dependency of hive-exec
1d59100 [Steve Loughran] SPARK-8064 (unsuccessful) attempt to get rid of pentaho as a transitive dependency of hive-exec
75733fc [Steve Loughran] SPARK-8064 change thrift binary startup message to "Starting ThriftBinaryCLIService on port"
3ebc279 [Steve Loughran] SPARK-8064 move strings used to check for http/bin thrift services up into constants
c80979d [Steve Loughran] SPARK-8064: SparkSQLCLIDriver drops remote mode support. CLISuite Tests pass instead of timing out: undetected regression?
27e8370 [Steve Loughran] SPARK-8064 fix some style & IDE warnings
00e50d6 [Steve Loughran] SPARK-8064 stop excluding hive shims from dependency (commented out , for now)
cb4f142 [Steve Loughran] SPARK-8054 cut pentaho dependency from calcite
f7aa9cb [Steve Loughran] SPARK-8064 everything compiles with some commenting and moving of classes into a hive package
6c310b4 [Steve Loughran] SPARK-8064 subclass Hive ServerOptionsProcessor to make it public again
f61a675 [Steve Loughran] SPARK-8064 thrift server switched to Hive 1.2.1, though it doesn't compile everywhere
4890b9d [Steve Loughran] SPARK-8064, build against Hive 1.2.1
Author: Cheng Lian <lian@databricks.com>
Closes#7895 from liancheng/spark-9554/enable-in-memory-partition-pruning and squashes the following commits:
67c403e [Cheng Lian] Enables in-memory partition pruning by default
Author: Reynold Xin <rxin@databricks.com>
Closes#7897 from rxin/calculateBitSetWidthInBytes and squashes the following commits:
2e73b3a [Reynold Xin] [SQL][minor] Simplify UnsafeRow.calculateBitSetWidthInBytes.
The issue was that the tokenizer was parsing "1one" into the numeric 1 using the code on line 110. I added another case to accept strings that start with a number and then have a letter somewhere else in it as well.
Author: Joseph Batchik <joseph.batchik@cloudera.com>
Closes#7844 from JDrit/parse_error and squashes the following commits:
b8ca12f [Joseph Batchik] fixed parsing issue by adding another case
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7885 from cloud-fan/cheap-copy and squashes the following commits:
0900ca1 [Wenchen Fan] replace == with ===
73f4ada [Wenchen Fan] add tests
07b865a [Wenchen Fan] add a cheap version of copy
This PR adds a base aggregation iterator `AggregationIterator`, which is used to create `SortBasedAggregationIterator` (for sort-based aggregation) and `UnsafeHybridAggregationIterator` (first it tries hash-based aggregation and falls back to the sort-based aggregation (using external sorter) if we cannot allocate memory for the map). With these two iterators, we will not need existing iterators and I am removing those. Also, we can use a single physical `Aggregate` operator and it internally determines what iterators to used.
https://issues.apache.org/jira/browse/SPARK-9240
Author: Yin Huai <yhuai@databricks.com>
Closes#7813 from yhuai/AggregateOperator and squashes the following commits:
e317e2b [Yin Huai] Remove unnecessary change.
74d93c5 [Yin Huai] Merge remote-tracking branch 'upstream/master' into AggregateOperator
ba6afbc [Yin Huai] Add a little bit more comments.
c9cf3b6 [Yin Huai] update
0f1b06f [Yin Huai] Remove unnecessary code.
21fd15f [Yin Huai] Remove unnecessary change.
964f88b [Yin Huai] Implement fallback strategy.
b1ea5cf [Yin Huai] wip
7fcbd87 [Yin Huai] Add a flag to control what iterator to use.
533d5b2 [Yin Huai] Prepare for fallback!
33b7022 [Yin Huai] wip
bd9282b [Yin Huai] UDAFs now supports UnsafeRow.
f52ee53 [Yin Huai] wip
3171f44 [Yin Huai] wip
d2c45a0 [Yin Huai] wip
f60cc83 [Yin Huai] Also check input schema.
af32210 [Yin Huai] Check iter.hasNext before we create an iterator because the constructor of the iterato will read at least one row from a non-empty input iter.
299008c [Yin Huai] First round cleanup.
3915bac [Yin Huai] Create a base iterator class for aggregation iterators and add the initial version of the hybrid iterator.
JIRA: https://issues.apache.org/jira/browse/SPARK-9549
This PR fix the following bugs:
1. `UnaryMinus`'s codegen version would fail to compile when the input is `Long.MinValue`
2. `BinaryComparison` would fail to compile in codegen mode when comparing Boolean types.
3. `AddMonth` would fail if passed a huge negative month, which would lead accessing negative index of `monthDays` array.
4. `Nanvl` with different type operands.
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#7882 from yjshen/minor_bug_fix and squashes the following commits:
41bbd2c [Yijie Shen] fix bug in Nanvl type coercion
3dee204 [Yijie Shen] address comments
4fa5de0 [Yijie Shen] fix bugs in expressions
This PR adds an optimization rule, `FilterNullsInJoinKey`, to add `Filter` before join operators to filter out rows having null values for join keys.
This optimization is guarded by a new SQL conf, `spark.sql.advancedOptimization`.
The code in this PR was authored by yhuai; I'm opening this PR to factor out this change from #7685, a larger pull request which contains two other optimizations.
Author: Yin Huai <yhuai@databricks.com>
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7768 from JoshRosen/filter-nulls-in-join-key and squashes the following commits:
c02fc3f [Yin Huai] Address Josh's comments.
0a8e096 [Yin Huai] Update comments.
ea7d5a6 [Yin Huai] Make sure we do not keep adding filters.
be88760 [Yin Huai] Make it clear that FilterNullsInJoinKeySuite.scala is used to test FilterNullsInJoinKey.
8bb39ad [Yin Huai] Fix non-deterministic tests.
303236b [Josh Rosen] Revert changes that are unrelated to null join key filtering
40eeece [Josh Rosen] Merge remote-tracking branch 'origin/master' into filter-nulls-in-join-key
c57a954 [Yin Huai] Bug fix.
d3d2e64 [Yin Huai] First round of cleanup.
f9516b0 [Yin Huai] Style
c6667e7 [Yin Huai] Add PartitioningCollection.
e616d3b [Yin Huai] wip
7c2d2d8 [Yin Huai] Bug fix and refactoring.
69bb072 [Yin Huai] Introduce NullSafeHashPartitioning and NullUnsafePartitioning.
d5b84c3 [Yin Huai] Do not add unnessary filters.
2201129 [Yin Huai] Filter out rows that will not be joined in equal joins early.
This PR adds `PartitioningCollection`, which is used to represent the `outputPartitioning` for SparkPlans with multiple children (e.g. `ShuffledHashJoin`). So, a `SparkPlan` can have multiple descriptions of its partitioning schemes. Taking `ShuffledHashJoin` as an example, it has two descriptions of its partitioning schemes, i.e. `left.outputPartitioning` and `right.outputPartitioning`. So when we have a query like `select * from t1 join t2 on (t1.x = t2.x) join t3 on (t2.x = t3.x)` will only have three Exchange operators (when shuffled joins are needed) instead of four.
The code in this PR was authored by yhuai; I'm opening this PR to factor out this change from #7685, a larger pull request which contains two other optimizations.
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Author: Yin Huai <yhuai@databricks.com>
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7773 from JoshRosen/multi-way-join-planning-improvements and squashes the following commits:
5c45924 [Josh Rosen] Merge remote-tracking branch 'origin/master' into multi-way-join-planning-improvements
cd8269b [Josh Rosen] Refactor test to use SQLTestUtils
2963857 [Yin Huai] Revert unnecessary SqlConf change.
73913f7 [Yin Huai] Add comments and test. Also, revert the change in ShuffledHashOuterJoin for now.
4a99204 [Josh Rosen] Delete unrelated expression change
884ab95 [Josh Rosen] Carve out only SPARK-2205 changes.
247e5fa [Josh Rosen] Merge remote-tracking branch 'origin/master' into multi-way-join-planning-improvements
c57a954 [Yin Huai] Bug fix.
d3d2e64 [Yin Huai] First round of cleanup.
f9516b0 [Yin Huai] Style
c6667e7 [Yin Huai] Add PartitioningCollection.
e616d3b [Yin Huai] wip
7c2d2d8 [Yin Huai] Bug fix and refactoring.
69bb072 [Yin Huai] Introduce NullSafeHashPartitioning and NullUnsafePartitioning.
d5b84c3 [Yin Huai] Do not add unnessary filters.
2201129 [Yin Huai] Filter out rows that will not be joined in equal joins early.
This pull request creates two isOrderable functions in RowOrdering that can be used to check whether a data type or a sequence of expressions can be used in sorting.
Author: Reynold Xin <rxin@databricks.com>
Closes#7880 from rxin/SPARK-9546 and squashes the following commits:
f9e322d [Reynold Xin] Fixed tests.
0439b43 [Reynold Xin] [SPARK-9546][SQL] Centralize orderable data type checking.
The detailed approach is documented in UnsafeKVExternalSorterSuite.testKVSorter(), working as follows:
1. Create input by generating data randomly based on the given key/value schema (which is also randomly drawn from a list of candidate types)
2. Run UnsafeKVExternalSorter on the generated data
3. Collect the output from the sorter, and make sure the keys are sorted in ascending order
4. Sort the input by both key and value, and sort the sorter output also by both key and value. Compare the sorted input and sorted output together to make sure all the key/values match.
5. Check memory allocation to make sure there is no memory leak.
There is also a spill flag. When set to true, the sorter will spill probabilistically roughly every 100 records.
Author: Reynold Xin <rxin@databricks.com>
Closes#7873 from rxin/kvsorter-randomized-test and squashes the following commits:
a08c251 [Reynold Xin] Resource cleanup.
0488b5c [Reynold Xin] [SPARK-9543][SQL] Add randomized testing for UnsafeKVExternalSorter.
This pull request adds a destructAndCreateExternalSorter method to UnsafeFixedWidthAggregationMap. The new method does the following:
1. Creates a new external sorter UnsafeKVExternalSorter
2. Adds all the data into an in-memory sorter, sorts them
3. Spills the sorted in-memory data to disk
This method can be used to fallback to sort-based aggregation when under memory pressure.
The pull request also includes accounting fixes from JoshRosen.
TODOs (that can be done in follow-up PRs)
- [x] Address Josh's feedbacks from #7849
- [x] More documentation and test cases
- [x] Make sure we are doing memory accounting correctly with test cases (e.g. did we release the memory in BytesToBytesMap twice?)
- [ ] Look harder at possible memory leaks and exception handling
- [ ] Randomized tester for the KV sorter as well as the aggregation map
Author: Reynold Xin <rxin@databricks.com>
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7860 from rxin/kvsorter and squashes the following commits:
986a58c [Reynold Xin] Bug fix.
599317c [Reynold Xin] Style fix and slightly more compact code.
fe7bd4e [Reynold Xin] Bug fixes.
fd71bef [Reynold Xin] Merge remote-tracking branch 'josh/large-records-in-sql-sorter' into kvsorter-with-josh-fix
3efae38 [Reynold Xin] More fixes and documentation.
45f1b09 [Josh Rosen] Ensure that spill files are cleaned up
f6a9bd3 [Reynold Xin] Josh feedback.
9be8139 [Reynold Xin] Remove testSpillFrequency.
7cbe759 [Reynold Xin] [SPARK-9531][SQL] UnsafeFixedWidthAggregationMap.destructAndCreateExternalSorter.
ae4a8af [Josh Rosen] Detect leaked unsafe memory in UnsafeExternalSorterSuite.
52f9b06 [Josh Rosen] Detect ShuffleMemoryManager leaks in UnsafeExternalSorter.
Author: Reynold Xin <rxin@databricks.com>
Closes#7861 from rxin/api-audit and squashes the following commits:
7200256 [Reynold Xin] [SPARK-9208][SQL] Sort DataFrame functions alphabetically.
Generate prefix for DecimalType, fix the random generator of decimal
cc JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#7857 from davies/sort_decimal and squashes the following commits:
2433959 [Davies Liu] Merge branch 'master' of github.com:apache/spark into sort_decimal
de24253 [Davies Liu] fix style
0a54c1a [Davies Liu] sort decimal
When accessing a column in UnsafeRow, it's good to avoid the copy, then we should do deep copy when turn the UnsafeRow into generic Row, this PR brings generated FromUnsafeProjection to do that.
This PR also fix the expressions that cache the UTF8String, which should also copy it.
Author: Davies Liu <davies@databricks.com>
Closes#7840 from davies/avoid_copy and squashes the following commits:
230c8a1 [Davies Liu] address comment
fd797c9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into avoid_copy
e095dd0 [Davies Liu] rollback rename
8ef5b0b [Davies Liu] copy String in Columnar
81360b8 [Davies Liu] fix class name
9aecb88 [Davies Liu] use FromUnsafeProjection to do deep copy for UTF8String and struct
This PR is based on #7643 , thanks to adrian-wang
Author: Davies Liu <davies@databricks.com>
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#7847 from davies/datediff and squashes the following commits:
74333d7 [Davies Liu] fix bug
22d8a8c [Davies Liu] optimize
85cdd21 [Davies Liu] remove unnecessary tests
241d90c [Davies Liu] Merge branch 'master' of github.com:apache/spark into datediff
e9dc0f5 [Davies Liu] fix datediff/to_utc_timestamp/from_utc_timestamp
c360447 [Daoyuan Wang] function datediff, to_utc_timestamp, from_utc_timestamp (commits merged)
This PR is based on #7208 , thanks to HuJiayin
Closes#7208
Author: HuJiayin <jiayin.hu@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7850 from davies/initcap and squashes the following commits:
54472e9 [Davies Liu] fix python test
17ffe51 [Davies Liu] Merge branch 'master' of github.com:apache/spark into initcap
ca46390 [Davies Liu] Merge branch 'master' of github.com:apache/spark into initcap
3a906e4 [Davies Liu] implement title case in UTF8String
8b2506a [HuJiayin] Update functions.py
2cd43e5 [HuJiayin] fix python style check
b616c0e [HuJiayin] add python api
1f5a0ef [HuJiayin] add codegen
7e0c604 [HuJiayin] Merge branch 'master' of https://github.com/apache/spark into initcap
6a0b958 [HuJiayin] add column
c79482d [HuJiayin] support soundex
7ce416b [HuJiayin] support initcap rebase code
cc rxin
Author: Davies Liu <davies@databricks.com>
Closes#7856 from davies/sort_improve and squashes the following commits:
5fc81bd [Davies Liu] support DateType/TimestampType
This pull request adds a sortedIterator method to UnsafeFixedWidthAggregationMap that sorts its data in-place by the grouping key.
This is needed so we can fallback to external sorting for aggregation.
Author: Reynold Xin <rxin@databricks.com>
Closes#7849 from rxin/bytes2bytes-sorting and squashes the following commits:
75018c6 [Reynold Xin] Updated documentation.
81a8694 [Reynold Xin] [SPARK-9520][SQL] Support in-place sort in UnsafeFixedWidthAggregationMap.
This is based on #7641, thanks to zhichao-li
Closes#7641
Author: zhichao.li <zhichao.li@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7848 from davies/substr and squashes the following commits:
461b709 [Davies Liu] remove bytearry from tests
b45377a [Davies Liu] Merge branch 'master' of github.com:apache/spark into substr
01d795e [zhichao.li] scala style
99aa130 [zhichao.li] add substring to dataframe
4f68bfe [zhichao.li] add binary type support for substring
This PR is based on #7581 , just fix the conflict.
Author: Cheng Hao <hao.cheng@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7851 from davies/sort_array and squashes the following commits:
a80ef66 [Davies Liu] fix conflict
7cfda65 [Davies Liu] Merge branch 'master' of github.com:apache/spark into sort_array
664c960 [Cheng Hao] update the sort_array by using the ArrayData
276d2d5 [Cheng Hao] add empty line
0edab9c [Cheng Hao] Add asending/descending support for sort_array
80fc0f8 [Cheng Hao] Add type checking
a42b678 [Cheng Hao] Add sort_array support
This PR adds a `MapData` as internal representation of map type in Spark SQL, and provides a default implementation with just 2 `ArrayData`.
After that, we have specialized getters for all internal type, so I removed generic getter in `ArrayData` and added specialized `toArray` for it.
Also did some refactor and cleanup for `InternalRow` and its subclasses.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7799 from cloud-fan/map-data and squashes the following commits:
77d482f [Wenchen Fan] fix python
e8f6682 [Wenchen Fan] skip MapData equality check in HiveInspectorSuite
40cc9db [Wenchen Fan] add toString
6e06ec9 [Wenchen Fan] some more cleanup
a90aca1 [Wenchen Fan] add MapData
BytesToBytesMap current encodes key/value data in the following format:
```
8B key length, key data, 8B value length, value data
```
UnsafeExternalSorter, on the other hand, encodes data this way:
```
4B record length, data
```
As a result, we cannot pass records encoded by BytesToBytesMap directly into UnsafeExternalSorter for sorting. However, if we rearrange data slightly, we can then pass the key/value records directly into UnsafeExternalSorter:
```
4B key+value length, 4B key length, key data, value data
```
Author: Reynold Xin <rxin@databricks.com>
Closes#7845 from rxin/kvsort-rebase and squashes the following commits:
5716b59 [Reynold Xin] Fixed test.
2e62ccb [Reynold Xin] Updated BytesToBytesMap's data encoding to put the key first.
a51b641 [Reynold Xin] Added a KV sorter interface.
Add expression `sort_array` support.
Author: Cheng Hao <hao.cheng@intel.com>
This patch had conflicts when merged, resolved by
Committer: Davies Liu <davies.liu@gmail.com>
Closes#7581 from chenghao-intel/sort_array and squashes the following commits:
664c960 [Cheng Hao] update the sort_array by using the ArrayData
276d2d5 [Cheng Hao] add empty line
0edab9c [Cheng Hao] Add asending/descending support for sort_array
80fc0f8 [Cheng Hao] Add type checking
a42b678 [Cheng Hao] Add sort_array support
JIRA: https://issues.apache.org/jira/browse/SPARK-9415
Following up #7787. We shouldn't use MapType as grouping keys and join keys too.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7819 from viirya/map_join_groupby and squashes the following commits:
005ee0c [Liang-Chi Hsieh] For comments.
7463398 [Liang-Chi Hsieh] MapType can't be used as join keys, grouping keys.
This PR is based on #7533 , thanks to zhichao-li
Closes#7533
Author: zhichao.li <zhichao.li@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7843 from davies/str_index and squashes the following commits:
391347b [Davies Liu] add python api
3ce7802 [Davies Liu] fix substringIndex
f2d29a1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into str_index
515519b [zhichao.li] add foldable and remove null checking
9546991 [zhichao.li] scala style
67c253a [zhichao.li] hide some apis and clean code
b19b013 [zhichao.li] add codegen and clean code
ac863e9 [zhichao.li] reduce the calling of numChars
12e108f [zhichao.li] refine unittest
d92951b [zhichao.li] add lastIndexOf
52d7b03 [zhichao.li] add substring_index function
This patch creates a code generated unsafe row concatenator that can be used to concatenate/join two UnsafeRows into a single UnsafeRow.
Since it is inherently hard to test these low level stuff, the test suites employ randomized testing heavily in order to guarantee correctness.
Author: Reynold Xin <rxin@databricks.com>
Closes#7821 from rxin/rowconcat and squashes the following commits:
8717f35 [Reynold Xin] Rebase and code review.
72c5d8e [Reynold Xin] Fixed a bug.
a84ed2e [Reynold Xin] Fixed offset.
40c3fb2 [Reynold Xin] Reset random data generator.
f0913aa [Reynold Xin] Test fixes.
6687b6f [Reynold Xin] Updated documentation.
00354b9 [Reynold Xin] Support concat data as well.
e9a4347 [Reynold Xin] Updated.
6269f96 [Reynold Xin] Fixed a bug .
0f89716 [Reynold Xin] [SPARK-9358][SQL][WIP] Code generation for UnsafeRow concat.
This patch adds support for entries larger than the default page size in BytesToBytesMap. These large rows are handled by allocating special overflow pages to hold individual entries.
In addition, this patch integrates BytesToBytesMap with the ShuffleMemoryManager:
- Move BytesToBytesMap from `unsafe` to `core` so that it can import `ShuffleMemoryManager`.
- Before allocating new data pages, ask the ShuffleMemoryManager to reserve the memory:
- `putNewKey()` now returns a boolean to indicate whether the insert succeeded or failed due to a lack of memory. The caller can use this value to respond to the memory pressure (e.g. by spilling).
- `UnsafeFixedWidthAggregationMap. getAggregationBuffer()` now returns `null` to signal failure due to a lack of memory.
- Updated all uses of these classes to handle these error conditions.
- Added new tests for allocating large records and for allocations which fail due to memory pressure.
- Extended the `afterAll()` test teardown methods to detect ShuffleMemoryManager leaks.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7762 from JoshRosen/large-rows and squashes the following commits:
ae7bc56 [Josh Rosen] Fix compilation
82fc657 [Josh Rosen] Merge remote-tracking branch 'origin/master' into large-rows
34ab943 [Josh Rosen] Remove semi
31a525a [Josh Rosen] Integrate BytesToBytesMap with ShuffleMemoryManager.
626b33c [Josh Rosen] Move code to sql/core and spark/core packages so that ShuffleMemoryManager can be integrated
ec4484c [Josh Rosen] Move BytesToBytesMap from unsafe package to core.
642ed69 [Josh Rosen] Rename size to numElements
bea1152 [Josh Rosen] Add basic test.
2cd3570 [Josh Rosen] Remove accidental duplicated code
07ff9ef [Josh Rosen] Basic support for large rows in BytesToBytesMap.
This PR brings SQL function soundex(), see https://issues.apache.org/jira/browse/HIVE-9738
It's based on #7115 , thanks to HuJiayin
Author: HuJiayin <jiayin.hu@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7812 from davies/soundex and squashes the following commits:
fa75941 [Davies Liu] Merge branch 'master' of github.com:apache/spark into soundex
a4bd6d8 [Davies Liu] fix soundex
2538908 [HuJiayin] add codegen soundex
d15d329 [HuJiayin] add back ut
ded1a14 [HuJiayin] Merge branch 'master' of https://github.com/apache/spark
e2dec2c [HuJiayin] support soundex rebase code
This PR enables the processing of multiple window frames in a single window operator. This should improve the performance of processing multiple window expressions wich share partition by/order by clauses, because it will be more efficient with respect to memory use and group processing.
Author: Herman van Hovell <hvanhovell@questtec.nl>
Closes#7515 from hvanhovell/SPARK-8640 and squashes the following commits:
f0e1c21 [Herman van Hovell] Changed Window Logical/Physical plans to use partition by/order by specs directly instead of using WindowSpec.
e1711c2 [Herman van Hovell] Enabled the processing of multiple window frames in a single Window operator.
This PR address the comments in #7805
cc rxin
Author: Davies Liu <davies@databricks.com>
Closes#7817 from davies/trunc and squashes the following commits:
f729d5f [Davies Liu] rollback
cb7f7832 [Davies Liu] genCode() is protected
31e52ef [Davies Liu] fix style
ed1edc7 [Davies Liu] address comments for #7805
This PR is based on #6988 , thanks to adrian-wang .
This brings two SQL functions: to_date() and trunc().
Closes#6988
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7805 from davies/to_date and squashes the following commits:
2c7beba [Davies Liu] Merge branch 'master' of github.com:apache/spark into to_date
310dd55 [Daoyuan Wang] remove dup test in rebase
980b092 [Daoyuan Wang] resolve rebase conflict
a476c5a [Daoyuan Wang] address comments from davies
d44ea5f [Daoyuan Wang] function to_date, trunc
While reviewing yhuai's patch for SPARK-2205 (#7773), I noticed that Exchange's `compatible` check may be incorrectly returning `false` in many cases. As far as I know, this is not actually a problem because the `compatible`, `meetsRequirements`, and `needsAnySort` checks are serving only as short-circuit performance optimizations that are not necessary for correctness.
In order to reduce code complexity, I think that we should remove these checks and unconditionally rewrite the operator's children. This should be safe because we rewrite the tree in a single bottom-up pass.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7807 from JoshRosen/SPARK-9489 and squashes the following commits:
9d76ce9 [Josh Rosen] [SPARK-9489] Remove compatibleWith, meetsRequirements, and needsAnySort checks from Exchange
JIRA: https://issues.apache.org/jira/browse/SPARK-6319
Spark SQL uses plain byte arrays to represent binary values. However, the arrays are compared by reference rather than by values. Thus, we should not use BinaryType on Join and Aggregate in current implementation.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7787 from viirya/agg_no_binary_type and squashes the following commits:
4f76cac [Liang-Chi Hsieh] Throw AnalysisException when using BinaryType on Join and Aggregate.
This PR brings the support of DecimalType in UnsafeRow, for precision <= 18, it's settable, otherwise it's not settable.
Author: Davies Liu <davies@databricks.com>
Closes#7758 from davies/unsafe_decimal and squashes the following commits:
478b1ba [Davies Liu] address comments
536314c [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_decimal
7c2e77a [Davies Liu] fix JoinedRow
76d6fa4 [Davies Liu] fix tests
99d3151 [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_decimal
d49c6ae [Davies Liu] support DecimalType in UnsafeRow
Author: Reynold Xin <rxin@databricks.com>
Closes#7803 from rxin/SPARK-9458 and squashes the following commits:
5b032dc [Reynold Xin] Fix string.
b670dbb [Reynold Xin] [SPARK-9458][SPARK-9469][SQL] Code generate prefix computation in sorting & moves unsafe conversion out of TungstenSort.
This was previously committed but then reverted due to test failures (see #6769).
Author: Xiangrui Meng <meng@databricks.com>
Closes#7755 from rxin/SPARK-7157 and squashes the following commits:
fbf9044 [Xiangrui Meng] fix python test
542bd37 [Xiangrui Meng] update test
604fe6d [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157
f051afd [Xiangrui Meng] use udf instead of building expression
f4e9425 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157
8fb990b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157
103beb3 [Xiangrui Meng] add Java-friendly sampleBy
991f26f [Xiangrui Meng] fix seed
4a14834 [Xiangrui Meng] move sampleBy to stat
832f7cc [Xiangrui Meng] add sampleBy to DataFrame
This PR is based on #7589 , thanks to adrian-wang
Added SQL function date_add, date_sub, add_months, month_between, also add a rule for
add/subtract of date/timestamp and interval.
Closes#7589
cc rxin
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7754 from davies/date_add and squashes the following commits:
e8c633a [Davies Liu] Merge branch 'master' of github.com:apache/spark into date_add
9e8e085 [Davies Liu] Merge branch 'master' of github.com:apache/spark into date_add
6224ce4 [Davies Liu] fix conclict
bd18cd4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into date_add
e47ff2c [Davies Liu] add python api, fix date functions
01943d0 [Davies Liu] Merge branch 'master' into date_add
522e91a [Daoyuan Wang] fix
e8a639a [Daoyuan Wang] fix
42df486 [Daoyuan Wang] fix style
87c4b77 [Daoyuan Wang] function add_months, months_between and some fixes
1a68e03 [Daoyuan Wang] poc of time interval calculation
c506661 [Daoyuan Wang] function date_add , date_sub
unix_timestamp(): long
Gets current Unix timestamp in seconds.
unix_timestamp(string|date): long
Converts time string in format yyyy-MM-dd HH:mm:ss to Unix timestamp (in seconds), using the default timezone and the default locale, return null if fail: unix_timestamp('2009-03-20 11:30:01') = 1237573801
unix_timestamp(string date, string pattern): long
Convert time string with given pattern (see [http://docs.oracle.com/javase/tutorial/i18n/format/simpleDateFormat.html]) to Unix time stamp (in seconds), return null if fail: unix_timestamp('2009-03-20', 'yyyy-MM-dd') = 1237532400.
from_unixtime(bigint unixtime[, string format]): string
Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the format of "1970-01-01 00:00:00".
Jira:
https://issues.apache.org/jira/browse/SPARK-8174https://issues.apache.org/jira/browse/SPARK-8175
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#7644 from adrian-wang/udfunixtime and squashes the following commits:
2fe20c4 [Daoyuan Wang] util.Date
ea2ec16 [Daoyuan Wang] use util.Date for better performance
a2cf929 [Daoyuan Wang] doc return null instead of 0
f6f070a [Daoyuan Wang] address comments from davies
6a4cbb3 [Daoyuan Wang] temp
56ded53 [Daoyuan Wang] rebase and address comments
14a8b37 [Daoyuan Wang] function unix_timestamp, from_unixtime
This pull request enables Unsafe mode by default in Spark SQL. In order to do this, we had to fix a number of small issues:
**List of fixed blockers**:
- [x] Make some default buffer sizes configurable so that HiveCompatibilitySuite can run properly (#7741).
- [x] Memory leak on grouped aggregation of empty input (fixed by #7560 to fix this)
- [x] Update planner to also check whether codegen is enabled before planning unsafe operators.
- [x] Investigate failing HiveThriftBinaryServerSuite test. This turns out to be caused by a ClassCastException that occurs when Exchange tries to apply an interpreted RowOrdering to an UnsafeRow when range partitioning an RDD. This could be fixed by #7408, but a shorter-term fix is to just skip the Unsafe exchange path when RangePartitioner is used.
- [x] Memory leak exceptions masking exceptions that actually caused tasks to fail (will be fixed by #7603).
- [x] ~~https://issues.apache.org/jira/browse/SPARK-9162, to implement code generation for ScalaUDF. This is necessary for `UDFSuite` to pass. For now, I've just ignored this test in order to try to find other problems while we wait for a fix.~~ This is no longer necessary as of #7682.
- [x] Memory leaks from Limit after UnsafeExternalSort cause the memory leak detector to fail tests. This is a huge problem in the HiveCompatibilitySuite (fixed by f4ac642a4e5b2a7931c5e04e086bb10e263b1db6).
- [x] Tests in `AggregationQuerySuite` are failing due to NaN-handling issues in UnsafeRow, which were fixed in #7736.
- [x] `org.apache.spark.sql.ColumnExpressionSuite.rand` needs to be updated so that the planner check also matches `TungstenProject`.
- [x] After having lowered the buffer sizes to 4MB so that most of HiveCompatibilitySuite runs:
- [x] Wrong answer in `join_1to1` (fixed by #7680)
- [x] Wrong answer in `join_nulls` (fixed by #7680)
- [x] Managed memory OOM / leak in `lateral_view`
- [x] Seems to hang indefinitely in `partcols1`. This might be a deadlock in script transformation or a bug in error-handling code? The hang was fixed by #7710.
- [x] Error while freeing memory in `partcols1`: will be fixed by #7734.
- [x] After fixing the `partcols1` hang, it appears that a number of later tests have issues as well.
- [x] Fix thread-safety bug in codegen fallback expression evaluation (#7759).
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7564 from JoshRosen/unsafe-by-default and squashes the following commits:
83c0c56 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-by-default
f4cc859 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-by-default
963f567 [Josh Rosen] Reduce buffer size for R tests
d6986de [Josh Rosen] Lower page size in PySpark tests
013b9da [Josh Rosen] Also match TungstenProject in checkNumProjects
5d0b2d3 [Josh Rosen] Add task completion callback to avoid leak in limit after sort
ea250da [Josh Rosen] Disable unsafe Exchange path when RangePartitioning is used
715517b [Josh Rosen] Enable Unsafe by default
JIRA: https://issues.apache.org/jira/browse/SPARK-9361
Currently, we call `aggregate.Utils.tryConvert` in many places to check it the logical.Aggregate can be run with new aggregation. But looks like `aggregate.Utils.tryConvert` will cost considerable time to run. We should only call `tryConvert` once and keep it value in `logical.Aggregate` and reuse it.
In `org.apache.spark.sql.execution.aggregate.Utils`, the codes involving with `tryConvert` should be moved to catalyst because it actually doesn't deal with execution details.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7677 from viirya/refactor_aggregate and squashes the following commits:
babea30 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into refactor_aggregate
9a589d7 [Liang-Chi Hsieh] Fix scala style.
0a91329 [Liang-Chi Hsieh] Refactor new aggregation code to reduce the times to call tryConvert.
JIRA: https://issues.apache.org/jira/browse/SPARK-8838
Currently all part-files are merged when merging parquet schema. However, in case there are many part-files and we can make sure that all the part-files have the same schema as their summary file. If so, we provide a configuration to disable merging part-files when merging parquet schema.
In short, we need to merge parquet schema because different summary files may contain different schema. But the part-files are confirmed to have the same schema with summary files.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7238 from viirya/option_partfile_merge and squashes the following commits:
71d5b5f [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into option_partfile_merge
8816f44 [Liang-Chi Hsieh] For comments.
dbc8e6b [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into option_partfile_merge
afc2fa1 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into option_partfile_merge
d4ed7e6 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into option_partfile_merge
df43027 [Liang-Chi Hsieh] Get dataStatuses' partitions based on all paths.
4eb2f00 [Liang-Chi Hsieh] Use given parameter.
ea8f6e5 [Liang-Chi Hsieh] Correct the code comments.
a57be0e [Liang-Chi Hsieh] Merge part-files if there are no summary files.
47df981 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into option_partfile_merge
4caf293 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into option_partfile_merge
0e734e0 [Liang-Chi Hsieh] Use correct API.
3b6be5b [Liang-Chi Hsieh] Fix key not found.
4bdd7e0 [Liang-Chi Hsieh] Don't read footer files if we can skip them.
8bbebcb [Liang-Chi Hsieh] Figure out how to test the config.
bbd4ce7 [Liang-Chi Hsieh] Add config to enable/disable merging part-files when merging parquet schema.
SparkEnv might not have been set in local unit tests.
Author: Reynold Xin <rxin@databricks.com>
Closes#7784 from rxin/HashedRelationSuite and squashes the following commits:
435d64b [Reynold Xin] Fix flaky HashedRelationSuite
Users can now get the file name of the partition being read in. A thread local variable is in `SQLNewHadoopRDD` and is set when the partition is computed. `SQLNewHadoopRDD` is moved to core so that the catalyst package can reach it.
This supports:
`df.select(inputFileName())`
and
`sqlContext.sql("select input_file_name() from table")`
Author: Joseph Batchik <josephbatchik@gmail.com>
Closes#7743 from JDrit/input_file_name and squashes the following commits:
abb8609 [Joseph Batchik] fixed failing test and changed the default value to be an empty string
d2f323d [Joseph Batchik] updates per review
102061f [Joseph Batchik] updates per review
75313f5 [Joseph Batchik] small fixes
c7f7b5a [Joseph Batchik] addeding input file name to Spark SQL
JIRA: https://issues.apache.org/jira/browse/SPARK-9428
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#7748 from yjshen/string_cleanup and squashes the following commits:
e0c2b3d [Yijie Shen] update codegen in RegExpExtract and RegExpReplace
26614d2 [Yijie Shen] MathFunctionSuite
a402859 [Yijie Shen] complex_create, conditional and cast
6e4e608 [Yijie Shen] arithmetic and cast
52593c1 [Yijie Shen] null input test cases for StringExpressionSuite
Also we could create a Python UDT without having a Scala one, it's important for Python users.
cc mengxr JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#7453 from davies/class_in_main and squashes the following commits:
4dfd5e1 [Davies Liu] add tests for Python and Scala UDT
793d9b2 [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
dc65f19 [Davies Liu] address comment
a9a3c40 [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
a86e1fc [Davies Liu] fix serialization
ad528ba [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
63f52ef [Davies Liu] fix pylint check
655b8a9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
316a394 [Davies Liu] support Python UDT with UTF
0bcb3ef [Davies Liu] fix bug in mllib
de986d6 [Davies Liu] fix test
83d65ac [Davies Liu] fix bug in StructType
55bb86e [Davies Liu] support Python UDT in __main__ (without Scala one)
In our existing sort prefix generation code, we use expression's eval method to generate the prefix, which results in object allocation for every prefix. We can use the specialized getters available on InternalRow directly to avoid the object allocation.
I also removed the FLOAT prefix, opting for converting float directly to double.
Author: Reynold Xin <rxin@databricks.com>
Closes#7763 from rxin/sort-prefix and squashes the following commits:
5dc2f06 [Reynold Xin] [SPARK-9458] Avoid object allocation in prefix generation.
We need to make page sizes configurable so we can reduce them in unit tests and increase them in real production workloads. These sizes are now controlled by a new configuration, `spark.buffer.pageSize`. The new default is 64 megabytes.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7741 from JoshRosen/SPARK-9411 and squashes the following commits:
a43c4db [Josh Rosen] Fix pow
2c0eefc [Josh Rosen] Fix MAXIMUM_PAGE_SIZE_BYTES comment + value
bccfb51 [Josh Rosen] Lower page size to 4MB in TestHive
ba54d4b [Josh Rosen] Make UnsafeExternalSorter's page size configurable
0045aa2 [Josh Rosen] Make UnsafeShuffle's page size configurable
bc734f0 [Josh Rosen] Rename configuration
e614858 [Josh Rosen] Makes BytesToBytesMap page size configurable
We want to introduce a new IntervalType in 1.6 that is based on only the number of microseoncds,
so interval can be compared.
Renaming the existing IntervalType to CalendarIntervalType so we can do that in the future.
Author: Reynold Xin <rxin@databricks.com>
Closes#7745 from rxin/calendarintervaltype and squashes the following commits:
99f64e8 [Reynold Xin] One more line ...
13466c8 [Reynold Xin] Fixed tests.
e20f24e [Reynold Xin] [SPARK-9430][SQL] Rename IntervalType to CalendarIntervalType.
as an offline discussion with rxin , it's weird to be computing stuff while doing sorting, we should only order by bound reference during execution.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7593 from cloud-fan/sort and squashes the following commits:
7b1bef7 [Wenchen Fan] add test
daf206d [Wenchen Fan] add more comments
289bee0 [Wenchen Fan] do not order by expressions which still need evaluation
Right now, we use double to parse all the float number in SQL. When it's used in expression together with DecimalType, it will turn the decimal into double as well. Also it will loss some precision when using double.
This PR change to parse float number to decimal or double, based on it's using scientific notation or not, see https://msdn.microsoft.com/en-us/library/ms179899.aspx
This is a break change, should we doc it somewhere?
Author: Davies Liu <davies@databricks.com>
Closes#7642 from davies/parse_decimal and squashes the following commits:
1f576d9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into parse_decimal
5e142b6 [Davies Liu] fix scala style
eca99de [Davies Liu] fix tests
2afe702 [Davies Liu] Merge branch 'master' of github.com:apache/spark into parse_decimal
f4a320b [Davies Liu] Update SqlParser.scala
1c48e34 [Davies Liu] use decimal or double when parsing SQL
We will do local projection for LocalRelation, and thus reuse the same Expression object among multiply evaluations. We should reset the mutable states of Expression before evaluate it.
Fix `PullOutNondeterministic` rule to make it work for `Sort`.
Also got a chance to cleanup the dataframe test suite.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7674 from cloud-fan/show and squashes the following commits:
888934f [Wenchen Fan] fix sort
c0e93e8 [Wenchen Fan] local DataFrame with random columns should return same value when call `show`
https://issues.apache.org/jira/browse/SPARK-9422
Author: Yin Huai <yhuai@databricks.com>
Closes#7737 from yhuai/removePlaceHolder and squashes the following commits:
ec29b44 [Yin Huai] Remove placeholder attributes.
UnsafeRow.getDouble and getFloat() return NaN when called on columns that are null, which is inconsistent with the behavior of other row classes (which is to return 0.0).
In addition, the generic get(ordinal, dataType) method should always return null for a null literal, but currently it handles nulls by calling the type-specific accessors.
This patch addresses both of these issues and adds a regression test.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7736 from JoshRosen/unsafe-row-null-fixes and squashes the following commits:
c8eb2ee [Josh Rosen] Fix test in UnsafeRowConverterSuite
6214682 [Josh Rosen] Fixes to null handling in UnsafeRow
Sort-merge join is more robust in Spark since sorting can be made using the Tungsten sort operator.
Author: Reynold Xin <rxin@databricks.com>
Closes#7733 from rxin/smj and squashes the following commits:
61e4d34 [Reynold Xin] Fixed test case.
5ffd731 [Reynold Xin] Fixed JoinSuite.
a137dc0 [Reynold Xin] [SPARK-9418][SQL] Use sort-merge join as the default shuffle join.
Since catalyst package already depends on Spark core, we can move those expressions
into catalyst, and simplify function registry.
This is a followup of #7478.
Author: Reynold Xin <rxin@databricks.com>
Closes#7735 from rxin/SPARK-8003 and squashes the following commits:
2ffbdc3 [Reynold Xin] [SPARK-8003][SQL] Move expressions in sql/core package to catalyst.
SparkSQL's ScriptTransform operator has several serious bugs which make debugging fairly difficult:
- If exceptions are thrown in the writing thread then the child process will not be killed, leading to a deadlock because the reader thread will block while waiting for input that will never arrive.
- TaskContext is not propagated to the writer thread, which may cause errors in upstream pipelined operators.
- Exceptions which occur in the writer thread are not propagated to the main reader thread, which may cause upstream errors to be silently ignored instead of killing the job. This can lead to silently incorrect query results.
- The writer thread is not a daemon thread, but it should be.
In addition, the code in this file is extremely messy:
- Lots of fields are nullable but the nullability isn't clearly explained.
- Many confusing variable names: for instance, there are variables named `ite` and `iterator` that are defined in the same scope.
- Some code was misindented.
- The `*serdeClass` variables are actually expected to be single-quoted strings, which is really confusing: I feel that this parsing / extraction should be performed in the analyzer, not in the operator itself.
- There were no unit tests for the operator itself, only end-to-end tests.
This pull request addresses these issues, borrowing some error-handling techniques from PySpark's PythonRDD.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7710 from JoshRosen/script-transform and squashes the following commits:
16c44e2 [Josh Rosen] Update some comments
983f200 [Josh Rosen] Use unescapeSQLString instead of stripQuotes
6a06a8c [Josh Rosen] Clean up handling of quotes in serde class name
494cde0 [Josh Rosen] Propagate TaskContext to writer thread
323bb2b [Josh Rosen] Fix error-swallowing bug
b31258d [Josh Rosen] Rename iterator variables to disambiguate.
88278de [Josh Rosen] Split ScriptTransformation writer thread into own class.
8b162b6 [Josh Rosen] Add failing test which demonstrates exception masking issue
4ee36a2 [Josh Rosen] Kill script transform subprocess when error occurs in input writer.
bd4c948 [Josh Rosen] Skip launching of external command for empty partitions.
b43e4ec [Josh Rosen] Clean up nullability in ScriptTransformation
fa18d26 [Josh Rosen] Add basic unit test for script transform with 'cat' command.
This PR introduce BytesToBytesMap to UnsafeHashedRelation, use it in executor for better performance.
It serialize all the key and values from java HashMap, put them into a BytesToBytesMap while deserializing. All the values for a same key are stored continuous to have better memory locality.
This PR also address the comments for #7480 , do some clean up.
Author: Davies Liu <davies@databricks.com>
Closes#7592 from davies/unsafe_map2 and squashes the following commits:
42c578a [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_map2
fd09528 [Davies Liu] remove thread local cache and update docs
1c5ad8d [Davies Liu] fix test
5eb1b5a [Davies Liu] address comments in #7480
46f1f22 [Davies Liu] fix style
fc221e0 [Davies Liu] use BytesToBytesMap for broadcast join
This test is flaky. https://issues.apache.org/jira/browse/SPARK-9196 will track the fix of it. For now, let's disable this test.
Author: Yin Huai <yhuai@databricks.com>
Closes#7727 from yhuai/SPARK-9196-ignore and squashes the following commits:
f92bded [Yin Huai] Ignore current_timestamp.
Certain applications would benefit from being able to inspect DataFrames that are straightforwardly produced by data sources that stem from files, and find out their source data. For example, one might want to display to a user the size of the data underlying a table, or to copy or mutate it.
This PR exposes an `inputFiles` method on DataFrame which attempts to discover the source data in a best-effort manner, by inspecting HadoopFsRelations and JSONRelations.
Author: Aaron Davidson <aaron@databricks.com>
Closes#7717 from aarondav/paths and squashes the following commits:
ff67430 [Aaron Davidson] inputFiles
0acd3ad [Aaron Davidson] [SPARK-9397] DataFrame should provide an API to find source data files if applicable
The original patch didn't handle nulls correctly for next_day.
Author: Reynold Xin <rxin@databricks.com>
Closes#7718 from rxin/next_day and squashes the following commits:
616a425 [Reynold Xin] Merged DatetimeExpressionsSuite into DateFunctionsSuite.
faa78cf [Reynold Xin] Merged DatetimeFunctionsSuite into DateExpressionsSuite.
6c4fb6a [Reynold Xin] [SPARK-8196][SQL] Fix null handling & documentation for next_day.
Author: Reynold Xin <rxin@databricks.com>
Closes#7720 from rxin/struct-followup and squashes the following commits:
d9757f5 [Reynold Xin] [SPARK-9373][SQL] follow up for StructType support in Tungsten projection.
This is actually contains 3 minor issues:
1) Enable the unit test(codegen) for mutable expressions (FormatNumber, Regexp_Replace/Regexp_Extract)
2) Use the `PlatformDependent.copyMemory` instead of the `System.arrayCopy`
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7566 from chenghao-intel/codegen_ut and squashes the following commits:
24f43ea [Cheng Hao] enable codegen for mutable expression & UTF8String performance
This pull request updates GenerateUnsafeProjection to support StructType. If an input struct type is backed already by an UnsafeRow, GenerateUnsafeProjection copies the bytes directly into its buffer space without any conversion. However, if the input is not an UnsafeRow, GenerateUnsafeProjection runs the code generated recursively to convert the input into an UnsafeRow and then copies it into the buffer space.
Also create a TungstenProject operator that projects data directly into UnsafeRow. Note that I'm not sure if this is the way we want to structure Unsafe+codegen operators, but we can defer that decision to follow-up pull requests.
Author: Reynold Xin <rxin@databricks.com>
Closes#7689 from rxin/tungsten-struct-type and squashes the following commits:
9162f42 [Reynold Xin] Support IntervalType in UnsafeRow's getter.
be9f377 [Reynold Xin] Fixed tests.
10c4b7c [Reynold Xin] Format generated code.
77e8d0e [Reynold Xin] Fixed NondeterministicSuite.
ac4951d [Reynold Xin] Yay.
ac203bf [Reynold Xin] More comments.
9f36216 [Reynold Xin] Updated comment.
6b781fe [Reynold Xin] Reset the change in DataFrameSuite.
525b95b [Reynold Xin] Merged with master, more documentation & test cases.
321859a [Reynold Xin] [SPARK-9373][SQL] Support StructType in Tungsten projection [WIP]
next_day, returns next certain dayofweek.
last_day, returns the last day of the month which given date belongs to.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#6986 from adrian-wang/udfnlday and squashes the following commits:
ef7e3da [Daoyuan Wang] fix
02b3426 [Daoyuan Wang] address 2 comments
dc69630 [Daoyuan Wang] address comments from rxin
8846086 [Daoyuan Wang] address comments from rxin
d09bcce [Daoyuan Wang] multi fix
1a9de3d [Daoyuan Wang] function next_day and last_day
Since we have been seeing a lot of failures related to this new feature, lets put it behind a flag and turn it off by default.
Author: Michael Armbrust <michael@databricks.com>
Closes#7703 from marmbrus/optionalMetastorePruning and squashes the following commits:
6ad128c [Michael Armbrust] style
8447835 [Michael Armbrust] [SPARK-9386][SQL] Feature flag for metastore partition pruning
fd37b87 [Michael Armbrust] add config flag
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7673 from cloud-fan/row-generic-getter-columnar and squashes the following commits:
88b1170 [Wenchen Fan] fix style
eeae712 [Wenchen Fan] Remove Internal.get generic getter call in columnar cache code
https://issues.apache.org/jira/browse/SPARK-9349
With this PR, we only expose `UserDefinedAggregateFunction` (an abstract class) and `MutableAggregationBuffer` (an interface). Other internal wrappers and helper classes are moved to `org.apache.spark.sql.execution.aggregate` and marked as `private[sql]`.
Author: Yin Huai <yhuai@databricks.com>
Closes#7687 from yhuai/UDAF-cleanup and squashes the following commits:
db36542 [Yin Huai] Add comments to UDAF examples.
ae17f66 [Yin Huai] Address comments.
9c9fa5f [Yin Huai] UDAF cleanup.
literals in grouping expressions have no effect at all, only make our grouping key bigger, so we should remove them in Optimizer.
I also make old and new aggregation code consistent about literals in grouping here. In old aggregation, actually literals in grouping are already removed but new aggregation is not. So I explicitly make it a rule in Optimizer.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7583 from cloud-fan/minor and squashes the following commits:
471adff [Wenchen Fan] add test
0839925 [Wenchen Fan] use transformDown when rewrite final result expressions
This PR is based on #6796 authored by rtreffer.
To support large decimal precisions (> 18), we do the following things in this PR:
1. Making `CatalystSchemaConverter` support large decimal precision
Decimal types with large precision are always converted to fixed-length byte array.
2. Making `CatalystRowConverter` support reading decimal values with large precision
When the precision is > 18, constructs `Decimal` values with an unscaled `BigInteger` rather than an unscaled `Long`.
3. Making `RowWriteSupport` support writing decimal values with large precision
In this PR we always write decimals as fixed-length byte array, because Parquet write path hasn't been refactored to conform Parquet format spec (see SPARK-6774 & SPARK-8848).
Two follow-up tasks should be done in future PRs:
- [ ] Writing decimals as `INT32`, `INT64` when possible while fixing SPARK-8848
- [ ] Adding compatibility tests as part of SPARK-5463
Author: Cheng Lian <lian@databricks.com>
Closes#7455 from liancheng/spark-4176 and squashes the following commits:
a543d10 [Cheng Lian] Fixes errors introduced while rebasing
9e31cdf [Cheng Lian] Supports decimals with precision > 18 for Parquet
This PR fixes a set of issues related to multi-database. A new data structure `TableIdentifier` is introduced to identify a table among multiple databases. We should stop using a single `String` (table name without database name), or `Seq[String]` (optional database name plus table name) to identify tables internally.
Author: Cheng Lian <lian@databricks.com>
Closes#7623 from liancheng/spark-8131-multi-db and squashes the following commits:
f3bcd4b [Cheng Lian] Addresses PR comments
e0eb76a [Cheng Lian] Fixes styling issues
41e2207 [Cheng Lian] Fixes multi-database support
d4d1ec2 [Cheng Lian] Adds multi-database test cases
JIRA: https://issues.apache.org/jira/browse/SPARK-9306
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7645 from viirya/smj_unsortable and squashes the following commits:
a240707 [Liang-Chi Hsieh] Use forall instead of exists for readability.
55221fa [Liang-Chi Hsieh] Shouldn't use SortMergeJoin when joining on unsortable columns.
As Hive does, we need to list all of the registered UDF and its usage for user.
We add the annotation to describe a UDF, so we can get the literal description info while registering the UDF.
e.g.
```scala
ExpressionDescription(
usage = "_FUNC_(expr) - Returns the absolute value of the numeric value",
extended = """> SELECT _FUNC_('-1')
1""")
case class Abs(child: Expression) extends UnaryArithmetic {
...
```
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7259 from chenghao-intel/desc_function and squashes the following commits:
cf29bba [Cheng Hao] fixing the code style issue
5193855 [Cheng Hao] Add more powerful parser for show functions
c645a6b [Cheng Hao] fix bug in unit test
78d40f1 [Cheng Hao] update the padding issue for usage
48ee4b3 [Cheng Hao] update as feedback
70eb4e9 [Cheng Hao] add show/describe function support
This PR removes the old Parquet support:
- Removes the old `ParquetRelation` together with related SQL configuration, plan nodes, strategies, utility classes, and test suites.
- Renames `ParquetRelation2` to `ParquetRelation`
- Renames `RowReadSupport` and `RowRecordMaterializer` to `CatalystReadSupport` and `CatalystRecordMaterializer` respectively, and moved them to separate files.
This follows naming convention used in other Parquet data models implemented in parquet-mr. It should be easier for developers who are familiar with Parquet to follow.
There's still some other code that can be cleaned up. Especially `RowWriteSupport`. But I'd like to leave this part to SPARK-8848.
Author: Cheng Lian <lian@databricks.com>
Closes#7441 from liancheng/spark-9095 and squashes the following commits:
c7b6e38 [Cheng Lian] Removes WriteToFile
2d688d6 [Cheng Lian] Renames ParquetRelation2 to ParquetRelation
ca9e1b7 [Cheng Lian] Removes old Parquet support
JIRA: https://issues.apache.org/jira/browse/SPARK-9356
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#7671 from yjshen/deprecated_unlimit and squashes the following commits:
c707f56 [Yijie Shen] remove pattern matching in changePrecision
4a1823c [Yijie Shen] remove internal occurrence of Decimal.Unlimited
Currently UnsafeRow cannot support a generic getter. However, if the data type is known, we can support a generic getter.
Author: Reynold Xin <rxin@databricks.com>
Closes#7666 from rxin/generic-getter-with-datatype and squashes the following commits:
ee2874c [Reynold Xin] Add a default implementation for getStruct.
1e109a0 [Reynold Xin] [SPARK-9350][SQL] Introduce an InternalRow generic getter that requires a DataType.
033ee88 [Reynold Xin] Removed getAs in non test code.
Author: Reynold Xin <rxin@databricks.com>
Closes#7665 from rxin/remove-row-apply and squashes the following commits:
0b43001 [Reynold Xin] support getString in UnsafeRow.
176d633 [Reynold Xin] apply -> get.
2941324 [Reynold Xin] [SPARK-9348][SQL] Remove apply method on InternalRow.
Currently nondeterministic expression is broken without a explicit initialization phase.
Let me take `MonotonicallyIncreasingID` as an example. This expression need a mutable state to remember how many times it has been evaluated, so we use `transient var count: Long` there. By being transient, the `count` will be reset to 0 and **only** to 0 when serialize and deserialize it, as deserialize transient variable will result to default value. There is *no way* to use another initial value for `count`, until we add the explicit initialization phase.
Another use case is local execution for `LocalRelation`, there is no serialize and deserialize phase and thus we can't reset mutable states for it.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7535 from cloud-fan/init and squashes the following commits:
6c6f332 [Wenchen Fan] add test
ef68ff4 [Wenchen Fan] fix comments
9eac85e [Wenchen Fan] move init code to interpreted class
bb7d838 [Wenchen Fan] pulls out nondeterministic expressions into a project
b4a4fc7 [Wenchen Fan] revert a refactor
86fee36 [Wenchen Fan] add initialization phase for nondeterministic expression
This is a follow-up of #7626. It fixes `Row`/`InternalRow` conversion for data sources extending `HadoopFsRelation` with `needConversion` being `true`.
Author: Cheng Lian <lian@databricks.com>
Closes#7649 from liancheng/spark-9285-conversion-fix and squashes the following commits:
036a50c [Cheng Lian] Addresses PR comment
f6d7c6a [Cheng Lian] Fixes Row/InternalRow conversion for HadoopFsRelation
The two are redundant.
Once this patch is merged, I plan to remove the inbound conversions from unsafe aggregates.
Author: Reynold Xin <rxin@databricks.com>
Closes#7658 from rxin/unsafeconverters and squashes the following commits:
ed19e6c [Reynold Xin] Updated support types.
2a56d7e [Reynold Xin] [SPARK-9334][SQL] Remove UnsafeRowConverter in favor of UnsafeProjection.
They were added to improve performance (so JIT can inline the JoinedRow calls). However, we can also just improve it by projecting output out to UnsafeRow in Tungsten variant of the operators.
Author: Reynold Xin <rxin@databricks.com>
Closes#7659 from rxin/remove-joinedrows and squashes the following commits:
7510447 [Reynold Xin] [SPARK-9336][SQL] Remove extra JoinedRows
Author: JD <jd@csh.rit.edu>
Author: Joseph Batchik <josephbatchik@gmail.com>
Closes#7606 from JDrit/expr and squashes the following commits:
ad7f607 [Joseph Batchik] fixing python linter error
9d6daea [Joseph Batchik] removed order by per @rxin's comment
707d5c6 [Joseph Batchik] Added expr to fuctions.py
79df83c [JD] added example to the docs
b89eec8 [JD] moved function up as per @rxin's comment
4960909 [JD] updated per @JoshRosen's comment
2cb329c [JD] updated per @rxin's comment
9a9ad0c [JD] removing unused import
6dc26d0 [JD] removed split
7f2222c [JD] Adding expr function as per SPARK-8668
JIRA: https://issues.apache.org/jira/browse/SPARK-9067
According to the description of the JIRA ticket, calling `reader.close()` only after the task is finished will cause memory and file open limit problem since these resources are occupied even we don't need that anymore.
This PR simply closes the reader early when we know there is no more data to read.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7424 from viirya/close_reader and squashes the following commits:
3ff64e5 [Liang-Chi Hsieh] For comments.
3d20267 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into close_reader
e152182 [Liang-Chi Hsieh] For comments.
5116cbe [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into close_reader
3ceb755 [Liang-Chi Hsieh] For comments.
e34d98e [Liang-Chi Hsieh] For comments.
50ed729 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into close_reader
216912f [Liang-Chi Hsieh] Fix it.
f429016 [Liang-Chi Hsieh] Release reader if we don't need it.
a305621 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into close_reader
67569da [Liang-Chi Hsieh] Close reader early if there is no more data.
I also changed InternalRow's size/length function to numFields, to make it more obvious that it is not about bytes, but the number of fields.
Author: Reynold Xin <rxin@databricks.com>
Closes#7626 from rxin/internalRow and squashes the following commits:
e124daf [Reynold Xin] Fixed test case.
805ceb7 [Reynold Xin] Commented out the failed test suite.
f8a9ca5 [Reynold Xin] Fixed more bugs. Still at least one more remaining.
76d9081 [Reynold Xin] Fixed data sources.
7807f70 [Reynold Xin] Fixed DataFrameSuite.
cb60cd2 [Reynold Xin] Code review & small bug fixes.
0a2948b [Reynold Xin] Fixed style.
3280d03 [Reynold Xin] [SPARK-9285][SQL] Remove InternalRow's inheritance from Row.
JIRA: https://issues.apache.org/jira/browse/SPARK-8756
Currently, in ParquetRelation2, footers are re-read every time refresh() is called. But we can check if it is possibly changed before we do the reading because reading all footers will be expensive when there are too many partitions. This pr fixes this by keeping some cached information to check it.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7154 from viirya/cached_footer_parquet_relation and squashes the following commits:
92e9347 [Liang-Chi Hsieh] Fix indentation.
ae0ec64 [Liang-Chi Hsieh] Fix wrong assignment.
c8fdfb7 [Liang-Chi Hsieh] Fix it.
a52b6d1 [Liang-Chi Hsieh] For comments.
c2a2420 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cached_footer_parquet_relation
fa5458f [Liang-Chi Hsieh] Use Map to cache FileStatus and do merging previously loaded schema and newly loaded one.
6ae0911 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cached_footer_parquet_relation
21bbdec [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cached_footer_parquet_relation
12a0ed9 [Liang-Chi Hsieh] Add check of FileStatus's modification time.
186429d [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cached_footer_parquet_relation
0ef8caf [Liang-Chi Hsieh] Keep cached information and avoid re-calculating footers.
fix some comments and code style for https://github.com/apache/spark/pull/7458
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7619 from cloud-fan/agg-clean and squashes the following commits:
3925457 [Wenchen Fan] one more...
cc78357 [Wenchen Fan] one more cleanup
26f6a93 [Wenchen Fan] some minor cleanup for the new aggregation
Romove Decimal.Unlimited (change to support precision up to 38, to match with Hive and other databases).
In order to keep backward source compatibility, Decimal.Unlimited is still there, but change to Decimal(38, 18).
If no precision and scale is provide, it's Decimal(10, 0) as before.
Author: Davies Liu <davies@databricks.com>
Closes#7605 from davies/decimal_unlimited and squashes the following commits:
aa3f115 [Davies Liu] fix tests and style
fb0d20d [Davies Liu] address comments
bfaae35 [Davies Liu] fix style
df93657 [Davies Liu] address comments and clean up
06727fd [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_unlimited
4c28969 [Davies Liu] fix tests
8d783cc [Davies Liu] fix tests
788631c [Davies Liu] fix double with decimal in Union/except
1779bde [Davies Liu] fix scala style
c9c7c78 [Davies Liu] remove Decimal.Unlimited
PARQUET-136 and PARQUET-173 have been fixed in parquet-mr 1.7.0. It's time to enable filter push-down by default now.
Author: Cheng Lian <lian@databricks.com>
Closes#7612 from liancheng/spark-9207 and squashes the following commits:
77e6b5e [Cheng Lian] Enables Parquet filter push-down by default
Author: David Arroyo Cazorla <darroyo@stratio.com>
Closes#7618 from darroyocazorla/master and squashes the following commits:
5f91379 [David Arroyo Cazorla] [SPARK-5447][SQL] Replace reference 'schema rdd' with DataFrame
We forgot to update doc. brkyvz
Author: Xiangrui Meng <meng@databricks.com>
Closes#7608 from mengxr/SPARK-9243 and squashes the following commits:
0ea3236 [Xiangrui Meng] null -> zero in crosstab doc
Reverts ObjectPool. As it stands, it has a few problems:
1. ObjectPool doesn't work with spilling and memory accounting.
2. I don't think in the long run the idea of an object pool is what we want to support, since it essentially goes back to unmanaged memory, and creates pressure on GC, and is hard to account for the total in memory size.
3. The ObjectPool patch removed the specialized getters for strings and binary, and as a result, actually introduced branches when reading non primitive data types.
If we do want to support arbitrary user defined types in the future, I think we can just add an object array in UnsafeRow, rather than relying on indirect memory addressing through a pool. We also need to pick execution strategies that are optimized for those, rather than keeping a lot of unserialized JVM objects in memory during aggregation.
This is probably the hardest thing I had to revert in Spark, due to recent patches that also change the same part of the code. Would be great to get a careful look.
Author: Reynold Xin <rxin@databricks.com>
Closes#7591 from rxin/revert-object-pool and squashes the following commits:
01db0bc [Reynold Xin] Scala style.
eda89fc [Reynold Xin] Fixed describe.
2967118 [Reynold Xin] Fixed accessor for JoinedRow.
e3294eb [Reynold Xin] Merge branch 'master' into revert-object-pool
657855f [Reynold Xin] Temp commit.
c20f2c8 [Reynold Xin] Style fix.
fe37079 [Reynold Xin] Revert "[SPARK-8579] [SQL] support arbitrary object in UnsafeRow"
Spark has an option called spark.localExecution.enabled; according to the docs:
> Enables Spark to run certain jobs, such as first() or take() on the driver, without sending tasks to the cluster. This can make certain jobs execute very quickly, but may require shipping a whole partition of data to the driver.
This feature ends up adding quite a bit of complexity to DAGScheduler, especially in the runLocallyWithinThread method, but as far as I know nobody uses this feature (I searched the mailing list and haven't seen any recent mentions of the configuration nor stacktraces including the runLocally method). As a step towards scheduler complexity reduction, I propose that we remove this feature and all code related to it for Spark 1.5.
This pull request simply brings #7484 up to date.
Author: Josh Rosen <joshrosen@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#7585 from rxin/remove-local-exec and squashes the following commits:
84bd10e [Reynold Xin] Python fix.
1d9739a [Reynold Xin] Merge pull request #7484 from JoshRosen/remove-localexecution
eec39fa [Josh Rosen] Remove allowLocal(); deprecate user-facing uses of it.
b0835dc [Josh Rosen] Remove local execution code in DAGScheduler
8975d96 [Josh Rosen] Remove local execution tests.
ffa8c9b [Josh Rosen] Remove documentation for configuration
I've seen a few cases in the past few weeks that the compiler is throwing warnings that are caused by legitimate bugs. This patch upgrades warnings to errors, except deprecation warnings.
Note that ideally we should be able to mark deprecation warnings as errors as well. However, due to the lack of ability to suppress individual warning messages in the Scala compiler, we cannot do that (since we do need to access deprecated APIs in Hadoop).
Most of the work are done by ericl.
Author: Reynold Xin <rxin@databricks.com>
Author: Eric Liang <ekl@databricks.com>
Closes#7598 from rxin/warnings and squashes the following commits:
beb311b [Reynold Xin] Fixed tests.
542c031 [Reynold Xin] Fixed one more warning.
87c354a [Reynold Xin] Fixed all non-deprecation warnings.
78660ac [Eric Liang] first effort to fix warnings
This PR introduce unsafe version (using UnsafeRow) of HashJoin, HashOuterJoin and HashSemiJoin, including the broadcast one and shuffle one (except FullOuterJoin, which is better to be implemented using SortMergeJoin).
It use HashMap to store UnsafeRow right now, will change to use BytesToBytesMap for better performance (in another PR).
Author: Davies Liu <davies@databricks.com>
Closes#7480 from davies/unsafe_join and squashes the following commits:
6294b1e [Davies Liu] fix projection
10583f1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_join
dede020 [Davies Liu] fix test
84c9807 [Davies Liu] address comments
a05b4f6 [Davies Liu] support UnsafeRow in LeftSemiJoinBNL and BroadcastNestedLoopJoin
611d2ed [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_join
9481ae8 [Davies Liu] return UnsafeRow after join()
ca2b40f [Davies Liu] revert unrelated change
68f5cd9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_join
0f4380d [Davies Liu] ada a comment
69e38f5 [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_join
1a40f02 [Davies Liu] refactor
ab1690f [Davies Liu] address comments
60371f2 [Davies Liu] use UnsafeRow in SemiJoin
a6c0b7d [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_join
184b852 [Davies Liu] fix style
6acbb11 [Davies Liu] fix tests
95d0762 [Davies Liu] remove println
bea4a50 [Davies Liu] Unsafe HashJoin
This is the first PR for the aggregation improvement, which is tracked by https://issues.apache.org/jira/browse/SPARK-4366 (umbrella JIRA). This PR contains work for its subtasks, SPARK-3056, SPARK-3947, SPARK-4233, and SPARK-4367.
This PR introduces a new code path for evaluating aggregate functions. This code path is guarded by `spark.sql.useAggregate2` and by default the value of this flag is true.
This new code path contains:
* A new aggregate function interface (`AggregateFunction2`) and 7 built-int aggregate functions based on this new interface (`AVG`, `COUNT`, `FIRST`, `LAST`, `MAX`, `MIN`, `SUM`)
* A UDAF interface (`UserDefinedAggregateFunction`) based on the new code path and two example UDAFs (`MyDoubleAvg` and `MyDoubleSum`).
* A sort-based aggregate operator (`Aggregate2Sort`) for the new aggregate function interface .
* A sort-based aggregate operator (`FinalAndCompleteAggregate2Sort`) for distinct aggregations (for distinct aggregations the query plan will use `Aggregate2Sort` and `FinalAndCompleteAggregate2Sort` together).
With this change, `spark.sql.useAggregate2` is `true`, the flow of compiling an aggregation query is:
1. Our analyzer looks up functions and returns aggregate functions built based on the old aggregate function interface.
2. When our planner is compiling the physical plan, it tries try to convert all aggregate functions to the ones built based on the new interface. The planner will fallback to the old code path if any of the following two conditions is true:
* code-gen is disabled.
* there is any function that cannot be converted (right now, Hive UDAFs).
* the schema of grouping expressions contain any complex data type.
* There are multiple distinct columns.
Right now, the new code path handles a single distinct column in the query (you can have multiple aggregate functions using that distinct column). For a query having a aggregate function with DISTINCT and regular aggregate functions, the generated plan will do partial aggregations for those regular aggregate function.
Thanks chenghao-intel for his initial work on it.
Author: Yin Huai <yhuai@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#7458 from yhuai/UDAF and squashes the following commits:
7865f5e [Yin Huai] Put the catalyst expression in the comment of the generated code for it.
b04d6c8 [Yin Huai] Remove unnecessary change.
f1d5901 [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
35b0520 [Yin Huai] Use semanticEquals to replace grouping expressions in the output of the aggregate operator.
3b43b24 [Yin Huai] bug fix.
00eb298 [Yin Huai] Make it compile.
a3ca551 [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
e0afca3 [Yin Huai] Gracefully fallback to old aggregation code path.
8a8ac4a [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
88c7d4d [Yin Huai] Enable spark.sql.useAggregate2 by default for testing purpose.
dc96fd1 [Yin Huai] Many updates:
85c9c4b [Yin Huai] newline.
43de3de [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
c3614d7 [Yin Huai] Handle single distinct column.
68b8ee9 [Yin Huai] Support single distinct column set. WIP
3013579 [Yin Huai] Format.
d678aee [Yin Huai] Remove AggregateExpressionSuite.scala since our built-in aggregate functions will be based on AlgebraicAggregate and we need to have another way to test it.
e243ca6 [Yin Huai] Add aggregation iterators.
a101960 [Yin Huai] Change MyJavaUDAF to MyDoubleSum.
594cdf5 [Yin Huai] Change existing AggregateExpression to AggregateExpression1 and add an AggregateExpression as the common interface for both AggregateExpression1 and AggregateExpression2.
380880f [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
0a827b3 [Yin Huai] Add comments and doc. Move some classes to the right places.
a19fea6 [Yin Huai] Add UDAF interface.
262d4c4 [Yin Huai] Make it compile.
b2e358e [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
6edb5ac [Yin Huai] Format update.
70b169c [Yin Huai] Remove groupOrdering.
4721936 [Yin Huai] Add CheckAggregateFunction to extendedCheckRules.
d821a34 [Yin Huai] Cleanup.
32aea9c [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
5b46d41 [Yin Huai] Bug fix.
aff9534 [Yin Huai] Make Aggregate2Sort work with both algebraic AggregateFunctions and non-algebraic AggregateFunctions.
2857b55 [Yin Huai] Merge remote-tracking branch 'upstream/master' into UDAF
4435f20 [Yin Huai] Add ConvertAggregateFunction to HiveContext's analyzer.
1b490ed [Michael Armbrust] make hive test
8cfa6a9 [Michael Armbrust] add test
1b0bb3f [Yin Huai] Do not bind references in AlgebraicAggregate and use code gen for all places.
072209f [Yin Huai] Bug fix: Handle expressions in grouping columns that are not attribute references.
f7d9e54 [Michael Armbrust] Merge remote-tracking branch 'apache/master' into UDAF
39ee975 [Yin Huai] Code cleanup: Remove unnecesary AttributeReferences.
b7720ba [Yin Huai] Add an analysis rule to convert aggregate function to the new version.
5c00f3f [Michael Armbrust] First draft of codegen
6bbc6ba [Michael Armbrust] now with correct answers\!
f7996d0 [Michael Armbrust] Add AlgebraicAggregate
dded1c5 [Yin Huai] wip
Author: Andrew Or <andrew@databricks.com>
Closes#7576 from andrewor14/clean-up-json-relation and squashes the following commits:
ea80803 [Andrew Or] Clean up duplicate code
Also make format_string the canonical form, rather than printf.
Author: Reynold Xin <rxin@databricks.com>
Closes#7579 from rxin/format_strings and squashes the following commits:
53ee54f [Reynold Xin] Fixed unit tests.
52357e1 [Reynold Xin] Add format_string alias.
b40a42a [Reynold Xin] [SPARK-9154][SQL] Rename formatString to format_string.
Jira: https://issues.apache.org/jira/browse/SPARK-9154
fixes bug of #7546
marmbrus I can't reopen the other PR, because I didn't closed it. Can you trigger Jenkins?
Author: Tarek Auel <tarek.auel@googlemail.com>
Closes#7571 from tarekauel/SPARK-9154 and squashes the following commits:
dcae272 [Tarek Auel] [SPARK-9154][SQL] build fix
1487602 [Tarek Auel] Merge remote-tracking branch 'upstream/master' into SPARK-9154
f512c5f [Tarek Auel] [SPARK-9154][SQL] build fix
a943d3e [Tarek Auel] [SPARK-9154] implicit input cast, added tests for null, support for null primitives
10b4de8 [Tarek Auel] [SPARK-9154][SQL] codegen removed fallback trait
cd8322b [Tarek Auel] [SPARK-9154][SQL] codegen string format
086caba [Tarek Auel] [SPARK-9154][SQL] codegen string format
This way, the sources package contains only public facing interfaces.
Author: Reynold Xin <rxin@databricks.com>
Closes#7565 from rxin/move-ds and squashes the following commits:
7661aff [Reynold Xin] Mima
9d5196a [Reynold Xin] Rearranged imports.
3dd7174 [Reynold Xin] [SPARK-8906][SQL] Move all internal data source classes into execution.datasources.
This patch fixes a managed memory leak in GeneratedAggregate. The leak occurs when the unsafe aggregation path is used to perform grouped aggregation on an empty input; in this case, GeneratedAggregate allocates an UnsafeFixedWidthAggregationMap that is never cleaned up because `next()` is never called on the aggregate result iterator.
This patch fixes this by short-circuiting on empty inputs.
This patch is an updated version of #6810.
Closes#6810.
Author: navis.ryu <navis@apache.org>
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7560 from JoshRosen/SPARK-8357 and squashes the following commits:
3486ce4 [Josh Rosen] Some minor cleanup
c649310 [Josh Rosen] Revert SparkPlan change:
3c7db0f [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-8357
adc8239 [Josh Rosen] Back out Projection changes.
c5419b3 [navis.ryu] addressed comments
143e1ef [navis.ryu] fixed format & added test for CCE case
735972f [navis.ryu] used new conf apis
1a02a55 [navis.ryu] Rolled-back test-conf cleanup & fixed possible CCE & added more tests
51178e8 [navis.ryu] addressed comments
4d326b9 [navis.ryu] fixed test fails
15c5afc [navis.ryu] added a test as suggested by JoshRosen
d396589 [navis.ryu] added comments
1b07556 [navis.ryu] [SPARK-8357] [SQL] Memory leakage on unsafe aggregation path with empty input
This reverts commit 7f072c3d5e.
Revert #7546
Author: Michael Armbrust <michael@databricks.com>
Closes#7570 from marmbrus/revert9154 and squashes the following commits:
ed2c32a [Michael Armbrust] Revert "[SPARK-9154] [SQL] codegen StringFormat"
JIRA:
https://issues.apache.org/jira/browse/SPARK-9081https://issues.apache.org/jira/browse/SPARK-9168
This PR target at two modifications:
1. Change `isNaN` to return `false` on `null` input
2. Make `dropna` and `fillna` to fill/drop NaN values as well
3. Implement `nanvl`
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#7523 from yjshen/fillna_dropna and squashes the following commits:
f0a51db [Yijie Shen] make coalesce untouched and implement nanvl
1d3e35f [Yijie Shen] make Coalesce aware of NaN in order to support fillna
2760cbc [Yijie Shen] change isNaN(null) to false as well as implement dropna
Pull Request for: https://issues.apache.org/jira/browse/SPARK-8230
Primary issue resolved is to implement array/map size for Spark SQL. Code is ready for review by a committer. Chen Hao is on the JIRA ticket, but I don't know his username on github, rxin is also on JIRA ticket.
Things to review:
1. Where to put added functions namespace wise, they seem to be part of a few operations on collections which includes `sort_array` and `array_contains`. Hence the name given `collectionOperations.scala` and `_collection_functions` in python.
2. In Python code, should it be in a `1.5.0` function array or in a collections array?
3. Are there any missing methods on the `Size` case class? Looks like many of these functions have generated Java code, is that also needed in this case?
4. Something else?
Author: Pedro Rodriguez <ski.rodriguez@gmail.com>
Author: Pedro Rodriguez <prodriguez@trulia.com>
Closes#7462 from EntilZha/SPARK-8230 and squashes the following commits:
9a442ae [Pedro Rodriguez] fixed functions and sorted __all__
9aea3bb [Pedro Rodriguez] removed imports from python docs
15d4bf1 [Pedro Rodriguez] Added null test case and changed to nullSafeCodeGen
d88247c [Pedro Rodriguez] removed python code
bd5f0e4 [Pedro Rodriguez] removed duplicate function from rebase/merge
59931b4 [Pedro Rodriguez] fixed compile bug instroduced when merging
c187175 [Pedro Rodriguez] updated code to add size to __all__ directly and removed redundent pretty print
130839f [Pedro Rodriguez] fixed failing test
aa9bade [Pedro Rodriguez] fix style
e093473 [Pedro Rodriguez] updated python code with docs, switched classes/traits implemented, added (failing) expression tests
0449377 [Pedro Rodriguez] refactored code to use better abstract classes/traits and implementations
9a1a2ff [Pedro Rodriguez] added unit tests for map size
2bfbcb6 [Pedro Rodriguez] added unit test for size
20df2b4 [Pedro Rodriguez] Finished working version of size function and added it to python
b503e75 [Pedro Rodriguez] First attempt at implementing size for maps and arrays
99a6a5c [Pedro Rodriguez] fixed failing test
cac75ac [Pedro Rodriguez] fix style
933d843 [Pedro Rodriguez] updated python code with docs, switched classes/traits implemented, added (failing) expression tests
42bb7d4 [Pedro Rodriguez] refactored code to use better abstract classes/traits and implementations
f9c3b8a [Pedro Rodriguez] added unit tests for map size
2515d9f [Pedro Rodriguez] added documentation
0e60541 [Pedro Rodriguez] added unit test for size
acf9853 [Pedro Rodriguez] Finished working version of size function and added it to python
84a5d38 [Pedro Rodriguez] First attempt at implementing size for maps and arrays
Add expressions `regex_extract` & `regex_replace`
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7468 from chenghao-intel/regexp and squashes the following commits:
e5ea476 [Cheng Hao] minor update for documentation
ef96fd6 [Cheng Hao] update the code gen
72cf28f [Cheng Hao] Add more log for compilation error
4e11381 [Cheng Hao] Add regexp_replace / regexp_extract support
This PR adds DataFrame reader/writer shortcut methods for ORC in both Scala and Python.
Author: Cheng Lian <lian@databricks.com>
Closes#7444 from liancheng/spark-9100 and squashes the following commits:
284d043 [Cheng Lian] Fixes PySpark test cases and addresses PR comments
e0b09fb [Cheng Lian] Adds DataFrame reader/writer shortcut methods for ORC
This patch addresses code review feedback from #7456.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7551 from JoshRosen/unsafe-exchange-followup and squashes the following commits:
76dbdf8 [Josh Rosen] Add comments + more methods to UnsafeRowSerializer
3d7a1f2 [Josh Rosen] Add writeToStream() method to UnsafeRow
It can be ambiguous whether that is a string literal or a column name.
cc marmbrus
Author: Reynold Xin <rxin@databricks.com>
Closes#7556 from rxin/str-exprs and squashes the following commits:
92afa83 [Reynold Xin] [SPARK-9208][SQL] Remove variant of DataFrame string functions that accept column names.
This patch addresses an issue where queries that sorted float or double columns containing NaN values could fail with "Comparison method violates its general contract!" errors from TimSort. The root of this problem is that `NaN > anything`, `NaN == anything`, and `NaN < anything` all return `false`.
Per the design specified in SPARK-9079, we have decided that `NaN = NaN` should return true and that NaN should appear last when sorting in ascending order (i.e. it is larger than any other numeric value).
In addition to implementing these semantics, this patch also adds canonicalization of NaN values in UnsafeRow, which is necessary in order to be able to do binary equality comparisons on equal NaNs that might have different bit representations (see SPARK-9147).
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7194 from JoshRosen/nan and squashes the following commits:
983d4fc [Josh Rosen] Merge remote-tracking branch 'origin/master' into nan
88bd73c [Josh Rosen] Fix Row.equals()
a702e2e [Josh Rosen] normalization -> canonicalization
a7267cf [Josh Rosen] Normalize NaNs in UnsafeRow
fe629ae [Josh Rosen] Merge remote-tracking branch 'origin/master' into nan
fbb2a29 [Josh Rosen] Fix NaN comparisons in BinaryComparison expressions
c1fd4fe [Josh Rosen] Fold NaN test into existing test framework
b31eb19 [Josh Rosen] Uncomment failing tests
7fe67af [Josh Rosen] Support NaN == NaN (SPARK-9145)
58bad2c [Josh Rosen] Revert "Compare rows' string representations to work around NaN incomparability."
fc6b4d2 [Josh Rosen] Update CodeGenerator
3998ef2 [Josh Rosen] Remove unused code
a2ba2e7 [Josh Rosen] Fix prefix comparision for NaNs
a30d371 [Josh Rosen] Compare rows' string representations to work around NaN incomparability.
6f03f85 [Josh Rosen] Fix bug in Double / Float ordering
42a1ad5 [Josh Rosen] Stop filtering NaNs in UnsafeExternalSortSuite
bfca524 [Josh Rosen] Change ordering so that NaN is maximum value.
8d7be61 [Josh Rosen] Update randomized test to use ScalaTest's assume()
b20837b [Josh Rosen] Add failing test for new NaN comparision ordering
5b88b2b [Josh Rosen] Fix compilation of CodeGenerationSuite
d907b5b [Josh Rosen] Merge remote-tracking branch 'origin/master' into nan
630ebc5 [Josh Rosen] Specify an ordering for NaN values.
9bf195a [Josh Rosen] Re-enable NaNs in CodeGenerationSuite to produce more regression tests
13fc06a [Josh Rosen] Add regression test for NaN sorting issue
f9efbb5 [Josh Rosen] Fix ORDER BY NULL
e7dc4fb [Josh Rosen] Add very generic test for ordering
7d5c13e [Josh Rosen] Add regression test for SPARK-8782 (ORDER BY NULL)
b55875a [Josh Rosen] Generate doubles and floats over entire possible range.
5acdd5c [Josh Rosen] Infinity and NaN are interesting.
ab76cbd [Josh Rosen] Move code to Catalyst package.
d2b4a4a [Josh Rosen] Add random data generator test utilities to Spark SQL.
This PR tries to accelerate Parquet schema discovery and `HadoopFsRelation` partition discovery. The acceleration is done by the following means:
- Turning off schema merging by default
Schema merging is not the most common case, but requires reading footers of all Parquet part-files and can be very slow.
- Avoiding `FileSystem.globStatus()` call when possible
`FileSystem.globStatus()` may issue multiple synchronous RPC calls, and can be very slow (esp. on S3). This PR adds `SparkHadoopUtil.globPathIfNecessary()`, which only issues RPC calls when the path contain glob-pattern specific character(s) (`{}[]*?\`).
This is especially useful when converting a metastore Parquet table with lots of partitions, since Spark SQL adds all partition directories as the input paths, and currently we do a `globStatus` call on each input path sequentially.
- Listing leaf files in parallel when the number of input paths exceeds a threshold
Listing leaf files is required by partition discovery. Currently it is done on driver side, and can be slow when there are lots of (nested) directories, since each `FileSystem.listStatus()` call issues an RPC. In this PR, we list leaf files in a BFS style, and resort to a Spark job once we found that the number of directories need to be listed exceed a threshold.
The threshold is controlled by `SQLConf` option `spark.sql.sources.parallelPartitionDiscovery.threshold`, which defaults to 32.
- Discovering Parquet schema in parallel
Currently, schema merging is also done on driver side, and needs to read footers of all part-files. This PR uses a Spark job to do schema merging. Together with task side metadata reading in Parquet 1.7.0, we never read any footers on driver side now.
Author: Cheng Lian <lian@databricks.com>
Closes#7396 from liancheng/accel-parquet and squashes the following commits:
5598efc [Cheng Lian] Uses ParquetInputFormat[InternalRow] instead of ParquetInputFormat[Row]
ff32cd0 [Cheng Lian] Excludes directories while listing leaf files
3c580f1 [Cheng Lian] Fixes test failure caused by making "mergeSchema" default to "false"
b1646aa [Cheng Lian] Should allow empty input paths
32e5f0d [Cheng Lian] Moves schema merging to executor side
This PR also remove the duplicated code between registerFunction and UserDefinedFunction.
cc JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#7450 from davies/fix_return_type and squashes the following commits:
e80bf9f [Davies Liu] remove debugging code
f94b1f6 [Davies Liu] fix mima
8f9c58b [Davies Liu] convert returned object from UDF into internal type
I don't think this function is useful at all in Scala/Java, since users can easily compute n * space easily.
Author: Reynold Xin <rxin@databricks.com>
Closes#7530 from rxin/remove-space and squashes the following commits:
c147873 [Reynold Xin] [SQL] Remove space from DataFrame Scala/Java API.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7525 from cloud-fan/deterministic and squashes the following commits:
4189bfa [Wenchen Fan] make deterministic describing the tree rather than the expression
This pull request aims to improve the performance of SQL's Exchange operator when shuffling UnsafeRows. It also makes several general efficiency improvements to Exchange.
Key changes:
- When performing hash partitioning, the old Exchange projected the partitioning columns into a new row then passed a `(partitioningColumRow: InternalRow, row: InternalRow)` pair into the shuffle. This is very inefficient because it ends up redundantly serializing the partitioning columns only to immediately discard them after the shuffle. After this patch's changes, Exchange now shuffles `(partitionId: Int, row: InternalRow)` pairs. This still isn't optimal, since we're still shuffling extra data that we don't need, but it's significantly more efficient than the old implementation; in the future, we may be able to further optimize this once we implement a new shuffle write interface that accepts non-key-value-pair inputs.
- Exchange's `compute()` method has been significantly simplified; the new code has less duplication and thus is easier to understand.
- When the Exchange's input operator produces UnsafeRows, Exchange will use a specialized `UnsafeRowSerializer` to serialize these rows. This serializer is significantly more efficient since it simply copies the UnsafeRow's underlying bytes. Note that this approach does not work for UnsafeRows that use the ObjectPool mechanism; I did not add support for this because we are planning to remove ObjectPool in the next few weeks.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7456 from JoshRosen/unsafe-exchange and squashes the following commits:
7e75259 [Josh Rosen] Fix cast in SparkSqlSerializer2Suite
0082515 [Josh Rosen] Some additional comments + small cleanup to remove an unused parameter
a27cfc1 [Josh Rosen] Add missing newline
741973c [Josh Rosen] Add simple test of UnsafeRow shuffling in Exchange.
359c6a4 [Josh Rosen] Remove println() and add comments
93904e7 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-exchange
8dd3ff2 [Josh Rosen] Exchange outputs UnsafeRows when its child outputs them
dd9c66d [Josh Rosen] Fix for copying logic
035af21 [Josh Rosen] Add logic for choosing when to use UnsafeRowSerializer
7876f31 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-shuffle
cbea80b [Josh Rosen] Add UnsafeRowSerializer
0f2ac86 [Josh Rosen] Import ordering
3ca8515 [Josh Rosen] Big code simplification in Exchange
3526868 [Josh Rosen] Iniitial cut at removing shuffle on KV pairs
Catch this while reading the code
Author: Jacky Li <lee.unreal@gmail.com>
Author: Jacky Li <jackylk@users.noreply.github.com>
Closes#7524 from jackylk/patch-11 and squashes the following commits:
b679011 [Jacky Li] fix doc
e10e211 [Jacky Li] [SQL] Minor document fix in HadoopFsRelationProvider
Sometimes we need more than one step to initialize the mutable states in code gen like https://github.com/apache/spark/pull/7516
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7521 from cloud-fan/init and squashes the following commits:
2106445 [Wenchen Fan] improve code gen for mutable states
I also changed the semantics of concat w.r.t. null back to the same behavior as Hive.
That is to say, concat now returns null if any input is null.
Author: Reynold Xin <rxin@databricks.com>
Closes#7504 from rxin/concat_ws and squashes the following commits:
83fd950 [Reynold Xin] Fixed type casting.
3ae85f7 [Reynold Xin] Write null better.
cdc7be6 [Reynold Xin] Added code generation for pure string mode.
a61c4e4 [Reynold Xin] Updated comments.
2d51406 [Reynold Xin] [SPARK-8241][SQL] string function: concat_ws.
This PR contains a few clean-ups that are a part of SPARK-8638: a few style issues got fixed, and a few tests were moved.
Git commit message is wrong BTW :(...
Author: Herman van Hovell <hvanhovell@questtec.nl>
Closes#7513 from hvanhovell/SPARK-8638-cleanup and squashes the following commits:
4e69d08 [Herman van Hovell] Fixed Perfomance Regression for Shrinking Window Frames (+Rebase)
This pull request fixes some of the problems in #6981.
- Added date functions to `__all__` so they get exposed
- Rename day_of_month -> dayofmonth
- Rename day_in_year -> dayofyear
- Rename week_of_year -> weekofyear
- Removed "day" from Scala/Python API since it is ambiguous. Only leaving the alias in SQL.
Author: Reynold Xin <rxin@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@databricks.com>
Closes#7506 from rxin/datetime and squashes the following commits:
0cb24d9 [Reynold Xin] Export all functions in Python.
e44a4a0 [Reynold Xin] Removed day function from Scala and Python.
9c08fdc [Reynold Xin] [SQL] Make date/time functions more consistent with other database systems.
## Description
Performance improvements for Spark Window functions. This PR will also serve as the basis for moving away from Hive UDAFs to Spark UDAFs. See JIRA tickets SPARK-8638 and SPARK-7712 for more information.
## Improvements
* Much better performance (10x) in running cases (e.g. BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) and UNBOUDED FOLLOWING cases. The current implementation in spark uses a sliding window approach in these cases. This means that an aggregate is maintained for every row, so space usage is N (N being the number of rows). This also means that all these aggregates all need to be updated separately, this takes N*(N-1)/2 updates. The running case differs from the Sliding case because we are only adding data to an aggregate function (no reset is required), we only need to maintain one aggregate (like in the UNBOUNDED PRECEDING AND UNBOUNDED case), update the aggregate for each row, and get the aggregate value after each update. This is what the new implementation does. This approach only uses 1 buffer, and only requires N updates; I am currently working on data with window sizes of 500-1000 doing running sums and this saves a lot of time. The CURRENT ROW AND UNBOUNDED FOLLOWING case also uses this approach and the fact that aggregate operations are communitative, there is one twist though it will process the input buffer in reverse.
* Fewer comparisons in the sliding case. The current implementation determines frame boundaries for every input row. The new implementation makes more use of the fact that the window is sorted, maintains the boundaries, and only moves them when the current row order changes. This is a minor improvement.
* A single Window node is able to process all types of Frames for the same Partitioning/Ordering. This saves a little time/memory spent buffering and managing partitions. This will be enabled in a follow-up PR.
* A lot of the staging code is moved from the execution phase to the initialization phase. Minor performance improvement, and improves readability of the execution code.
## Benchmarking
I have done a small benchmark using [on time performance](http://www.transtats.bts.gov) data of the month april. I have used the origin as a partioning key, as a result there is quite some variation in window sizes. The code for the benchmark can be found in the JIRA ticket. These are the results per Frame type:
Frame | Master | SPARK-8638
----- | ------ | ----------
Entire Frame | 2 s | 1 s
Sliding | 18 s | 1 s
Growing | 14 s | 0.9 s
Shrinking | 13 s | 1 s
Author: Herman van Hovell <hvanhovell@questtec.nl>
Closes#7057 from hvanhovell/SPARK-8638 and squashes the following commits:
3bfdc49 [Herman van Hovell] Fixed Perfomance Regression for Shrinking Window Frames (+Rebase)
2eb3b33 [Herman van Hovell] Corrected reverse range frame processing.
2cd2d5b [Herman van Hovell] Corrected reverse range frame processing.
b0654d7 [Herman van Hovell] Tests for exotic frame specifications.
e75b76e [Herman van Hovell] More docs, added support for reverse sliding range frames, and some reorganization of code.
1fdb558 [Herman van Hovell] Changed Data In HiveDataFrameWindowSuite.
ac2f682 [Herman van Hovell] Added a few more comments.
1938312 [Herman van Hovell] Added Documentation to the createBoundOrdering methods.
bb020e6 [Herman van Hovell] Major overhaul of Window operator.
It is very hard to track which expressions have code gen implemented or not. This patch removes the default fallback gencode implementation from Expression, and moves that into a new trait called CodegenFallback. Each concrete expression needs to either implement code generation, or mix in CodegenFallback. This makes it very easy to track which expressions have code generation implemented already.
Additionally, this patch creates an Unevaluable trait that can be used to track expressions that don't support evaluation (e.g. Star).
Author: Reynold Xin <rxin@databricks.com>
Closes#7487 from rxin/codegenfallback and squashes the following commits:
14ebf38 [Reynold Xin] Fixed Conv
6c1c882 [Reynold Xin] Fixed Alias.
b42611b [Reynold Xin] [SPARK-9150][SQL] Create a trait to track code generation for expressions.
cb5c066 [Reynold Xin] Removed extra import.
39cbe40 [Reynold Xin] [SPARK-8240][SQL] string function: concat
Author: Reynold Xin <rxin@databricks.com>
Closes#7500 from rxin/sqlconf and squashes the following commits:
a5726c8 [Reynold Xin] [SPARK-9174][SQL] Add documentation for all public SQLConfs.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7496 from cloud-fan/tests and squashes the following commits:
0958f90 [Wenchen Fan] improve test for nondeterministic expressions
a follow up of https://github.com/apache/spark/pull/7479.
The `TreeNode` is the root case of the requirement of `self: Product =>` stuff, so why not make `TreeNode` extend `Product`?
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7495 from cloud-fan/self-type and squashes the following commits:
8676af7 [Wenchen Fan] remove more self type
Now that we have two different internal row formats, UnsafeRow and the old Java-object-based row format, we end up having to perform conversions between these two formats. These conversions should not be performed by the operators themselves; instead, the planner should be responsible for inserting appropriate format conversions when they are needed.
This patch makes the following changes:
- Add two new physical operators for performing row format conversions, `ConvertToUnsafe` and `ConvertFromUnsafe`.
- Add new methods to `SparkPlan` to allow operators to express whether they output UnsafeRows and whether they can handle safe or unsafe rows as inputs.
- Implement an `EnsureRowFormats` rule to automatically insert converter operators where necessary.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7482 from JoshRosen/unsafe-converter-planning and squashes the following commits:
7450fa5 [Josh Rosen] Resolve conflicts in favor of choosing UnsafeRow
5220cce [Josh Rosen] Add roundtrip converter test
2bb8da8 [Josh Rosen] Add Union unsafe support + tests to bump up test coverage
6f79449 [Josh Rosen] Add even more assertions to execute()
08ce199 [Josh Rosen] Rename ConvertFromUnsafe -> ConvertToSafe
0e2d548 [Josh Rosen] Add assertion if operators' input rows are in different formats
cabb703 [Josh Rosen] Add tests for Filter
3b11ce3 [Josh Rosen] Add missing test file.
ae2195a [Josh Rosen] Fixes
0fef0f8 [Josh Rosen] Rename file.
d5f9005 [Josh Rosen] Finish writing EnsureRowFormats planner rule
b5df19b [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-converter-planning
9ba3038 [Josh Rosen] WIP
When the `condition` extracted by `ExtractEquiJoinKeys` contain join Predicate for left semi join, we can not plan it as semiJoin. Such as
SELECT * FROM testData2 x
LEFT SEMI JOIN testData2 y
ON x.b = y.b
AND x.a >= y.a + 2
Condition `x.a >= y.a + 2` can not evaluate on table `x`, so it throw errors
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#5643 from adrian-wang/spark7026 and squashes the following commits:
cc09809 [Daoyuan Wang] refactor semijoin and add plan test
575a7c8 [Daoyuan Wang] fix notserializable
27841de [Daoyuan Wang] fix rebase
10bf124 [Daoyuan Wang] fix style
72baa02 [Daoyuan Wang] fix style
8e0afca [Daoyuan Wang] merge commits for rebase
JIRA: https://issues.apache.org/jira/browse/SPARK-9080
cc rxin
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#7464 from yijieshen/isNaN and squashes the following commits:
11ae039 [Yijie Shen] add isNaN in functions
666718e [Yijie Shen] add isNaN predicate expression
Just a small change to add Product type to the base expression/plan abstract classes, based on suggestions on #7434 and offline discussions.
Author: Reynold Xin <rxin@databricks.com>
Closes#7479 from rxin/remove-self-types and squashes the following commits:
e407ffd [Reynold Xin] [SPARK-9142][SQL] Removing unnecessary self types in Catalyst.
cc chenghao-intel adrian-wang
Author: zhichao.li <zhichao.li@intel.com>
Closes#6872 from zhichao-li/conv and squashes the following commits:
6ef3b37 [zhichao.li] add unittest and comments
78d9836 [zhichao.li] polish dataframe api and add unittest
e2bace3 [zhichao.li] update to use ImplicitCastInputTypes
cbcad3f [zhichao.li] add function conv
Currently we will stop project collapse when the lower projection has nondeterministic expressions. However it's overkill sometimes, we should be able to optimize `df.select(Rand(10)).select('a)` to `df.select('a)`
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7445 from cloud-fan/non-deterministic and squashes the following commits:
0deaef6 [Wenchen Fan] Improve project collapse with nondeterministic expressions
This builds on #7433 but also removes LeafNode/UnaryNode. These are slightly more complicated to remove. I had to change some abstract classes to traits in order for it to work.
The problem with LeafNode/UnaryNode is that they are often mixed in at the end of an Expression, and then the toString function actually gets resolved to the ones defined in TreeNode, rather than in Expression.
Author: Reynold Xin <rxin@databricks.com>
Closes#7434 from rxin/remove-binary-unary-leaf-node and squashes the following commits:
9e8a4de [Reynold Xin] Generator should not be foldable.
3135a8b [Reynold Xin] SortOrder should not be foldable.
9c589cf [Reynold Xin] Fixed one more test case...
2225331 [Reynold Xin] Aggregate expressions should not be foldable.
16b5c90 [Reynold Xin] [SPARK-9085][SQL] Remove LeafNode, UnaryNode, BinaryNode from TreeNode.
JIRA: https://issues.apache.org/jira/browse/SPARK-6941
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#7342 from yijieshen/SPARK-6941 and squashes the following commits:
f82cbe7 [Yijie Shen] reorder import
dd67e40 [Yijie Shen] resolve comments
09518af [Yijie Shen] fix import order in DataframeSuite
0c635d4 [Yijie Shen] make match more specific
9df388d [Yijie Shen] move check into PreWriteCheck
847ab20 [Yijie Shen] Detect insertion error in DataSourceStrategy
Cleanup maven for a clean import in scala-ide / eclipse.
* remove groovy plugin which is really not needed at all
* add-source from build-helper-maven-plugin is not needed as recent version of scala-maven-plugin do it automatically
* add lifecycle-mapping plugin to hide a few useless warnings from ide
Author: Jan Prach <jendap@gmail.com>
Closes#7375 from jendap/clean-project-import-in-scala-ide and squashes the following commits:
c4b4c0f [Jan Prach] fix whitespaces
5a83e07 [Jan Prach] Revert "remove java compiler warnings from java tests"
312007e [Jan Prach] scala-maven-plugin itself add scala sources by default
f47d856 [Jan Prach] remove spark-1.4-staging repository
c8a54db [Jan Prach] remove java compiler warnings from java tests
999a068 [Jan Prach] remove some maven warnings in scala ide
80fbdc5 [Jan Prach] remove groovy and gmavenplus plugin
- `BinaryType` for `Length`
- `FormatNumber`
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7034 from chenghao-intel/expression and squashes the following commits:
e534b87 [Cheng Hao] python api style issue
601bbf5 [Cheng Hao] add python API support
3ebe288 [Cheng Hao] update as feedback
52274f7 [Cheng Hao] add support for udf_format_number and length for binary
These traits are not super useful, and yet cause problems with toString in expressions due to the orders they are mixed in.
Author: Reynold Xin <rxin@databricks.com>
Closes#7433 from rxin/remove-binary-node and squashes the following commits:
1881f78 [Reynold Xin] [SPARK-9086][SQL] Remove BinaryNode from TreeNode.
I also took the chance to more explicitly define the semantics of deterministic.
Author: Reynold Xin <rxin@databricks.com>
Closes#7428 from rxin/non-deterministic and squashes the following commits:
a760827 [Reynold Xin] [SPARK-9071][SQL] MonotonicallyIncreasingID and SparkPartitionID should be marked as nondeterministic.
https://issues.apache.org/jira/browse/SPARK-8221
One concern is the result would be negative if the divisor is not positive( i.e pmod(7, -3) ), but the behavior is the same as hive.
Author: zhichao.li <zhichao.li@intel.com>
Closes#6783 from zhichao-li/pmod2 and squashes the following commits:
7083eb9 [zhichao.li] update to the latest type checking
d26dba7 [zhichao.li] add pmod
We can keep expressions' mutable states in generated class(like `SpecificProjection`) as member variables, so that we can read and modify them inside codegened expressions.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7392 from cloud-fan/mutable-state and squashes the following commits:
eb3a221 [Wenchen Fan] fix order
73144d8 [Wenchen Fan] naming improvement
318f41d [Wenchen Fan] address more comments
d43b65d [Wenchen Fan] address comments
fd45c7a [Wenchen Fan] Support mutable state in code gen expressions
JIRA: https://issues.apache.org/jira/browse/SPARK-8840
Currently the type coercion rules don't include float type. This PR simply adds it.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7280 from viirya/add_r_float_coercion and squashes the following commits:
c86dc0e [Liang-Chi Hsieh] For comments.
dbf0c1b [Liang-Chi Hsieh] Implicitly convert Double to Float based on provided schema.
733015a [Liang-Chi Hsieh] Add test case for DataFrame with float type.
30c2a40 [Liang-Chi Hsieh] Update test case.
52b5294 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into add_r_float_coercion
6f9159d [Liang-Chi Hsieh] Add another test case.
8db3244 [Liang-Chi Hsieh] schema also needs to support float. add test case.
0dcc992 [Liang-Chi Hsieh] Add float coercion on SparkR.
This patch makes the following changes:
1. ExpectsInputTypes only defines expected input types, but does not perform any implicit type casting.
2. ImplicitCastInputTypes is a new trait that defines both expected input types, as well as performs implicit type casting.
3. BinaryOperator has a new abstract function "inputType", which defines the expected input type for both left/right. Concrete BinaryOperator expressions no longer perform any implicit type casting.
4. For BinaryOperators, convert NullType (i.e. null literals) into some accepted type so BinaryOperators don't need to handle NullTypes.
TODOs needed: fix unit tests for error reporting.
I'm intentionally not changing anything in aggregate expressions because yhuai is doing a big refactoring on that right now.
Author: Reynold Xin <rxin@databricks.com>
Closes#7348 from rxin/typecheck and squashes the following commits:
8fcf814 [Reynold Xin] Fixed ordering of cases.
3bb63e7 [Reynold Xin] Style fix.
f45408f [Reynold Xin] Comment update.
aa7790e [Reynold Xin] Moved RemoveNullTypes into ImplicitTypeCasts.
438ea07 [Reynold Xin] space
d55c9e5 [Reynold Xin] Removes NullTypes.
360d124 [Reynold Xin] Fixed the rule.
fb66657 [Reynold Xin] Convert NullType into some accepted type for BinaryOperators.
2e22330 [Reynold Xin] Fixed unit tests.
4932d57 [Reynold Xin] Style fix.
d061691 [Reynold Xin] Rename existing ExpectsInputTypes -> ImplicitCastInputTypes.
e4727cc [Reynold Xin] BinaryOperator should not be doing implicit cast.
d017861 [Reynold Xin] Improve expression type checking.
SPARK-8317 changed the SQL Exchange operator so that it no longer pushed sorting into Spark's shuffle layer, a change which allowed more efficient SQL-specific sorters to be used.
This patch performs some leftover cleanup based on those changes:
- Exchange's constructor should no longer accept a `newOrdering` since it's no longer used and no longer works as expected.
- `addOperatorsIfNecessary` looked at shuffle input's output ordering to decide whether to sort, but this is the wrong node to be examining: it needs to look at whether the post-shuffle node has the right ordering, since shuffling will not preserve row orderings. Thanks to davies for spotting this.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7407 from JoshRosen/SPARK-9050 and squashes the following commits:
e70be50 [Josh Rosen] No need to wrap line
e866494 [Josh Rosen] Refactor addOperatorsIfNecessary to make code clearer
2e467da [Josh Rosen] Remove `newOrdering` from Exchange.
This pull request adds a Scalastyle regex rule which fails the style check if `Class.forName` is used directly. `Class.forName` always loads classes from the default / system classloader, but in a majority of cases, we should be using Spark's own `Utils.classForName` instead, which tries to load classes from the current thread's context classloader and falls back to the classloader which loaded Spark when the context classloader is not defined.
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Author: Josh Rosen <joshrosen@databricks.com>
Closes#7350 from JoshRosen/ban-Class.forName and squashes the following commits:
e3e96f7 [Josh Rosen] Merge remote-tracking branch 'origin/master' into ban-Class.forName
c0b7885 [Josh Rosen] Hopefully fix the last two cases
d707ba7 [Josh Rosen] Fix uses of Class.forName that I missed in my first cleanup pass
046470d [Josh Rosen] Merge remote-tracking branch 'origin/master' into ban-Class.forName
62882ee [Josh Rosen] Fix uses of Class.forName or add exclusion.
d9abade [Josh Rosen] Add stylechecker rule to ban uses of Class.forName
This is a follow up of remaining comments from #6851
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#7387 from adrian-wang/udflgfollow and squashes the following commits:
6163e62 [Daoyuan Wang] add skipping null values
e8c2e09 [Daoyuan Wang] use seq
8362966 [Daoyuan Wang] pr6851 follow up
chenghao-intel zhichao-li qiansl127
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#6851 from adrian-wang/udflg and squashes the following commits:
0f1bff2 [Daoyuan Wang] address comments from davis
7a6bdbb [Daoyuan Wang] add '.' for hex()
c1f6824 [Daoyuan Wang] add codegen, test for all types
ec625b0 [Daoyuan Wang] conditional function: least/greatest
This is a follow-up of [SPARK-8888] [1], which also aims to optimize writing dynamic partitions.
Three more changes can be made here:
1. Using `InternalRow` instead of `Row` in `BaseWriterContainer.outputWriterForRow`
2. Using `Cast` expressions to convert partition columns to strings, so that we can leverage code generation.
3. Replacing the FP-style `zip` and `map` calls with a faster imperative `while` loop.
[1]: https://issues.apache.org/jira/browse/SPARK-8888
Author: Cheng Lian <lian@databricks.com>
Closes#7331 from liancheng/spark-8961 and squashes the following commits:
b5ab9ae [Cheng Lian] Casts Java iterator to Scala iterator explicitly
719e63b [Cheng Lian] Makes BaseWriterContainer.outputWriterForRow accepts InternalRow instead of Row
Author: Cheng Lian <lian@databricks.com>
Closes#7347 from liancheng/spark-8990 and squashes the following commits:
045698c [Cheng Lian] SPARK-8990 DataFrameReader.parquet() should respect user specified options
This patch adds a cache-friendly external sorter which operates on serialized bytes and uses this sorter to implement a new sort operator for Spark SQL and DataFrames.
### Overview of the new sorter
The new sorter design is inspired by [Alphasort](http://research.microsoft.com/pubs/68249/alphasort.doc) and implements a key-prefix optimization in order to improve the cache friendliness of the sort. In naive sort implementations, the sorting algorithm operates on an array of record pointers. To compare two records for ordering, the sorter must dereference these pointers, which likely involves random memory access, then compare the objects themselves.
In a key-prefix sort, the sort operates on an array which stores the record pointer alongside a prefix of the record's key. When comparing two records for ordering, the sorter first compares the the stored key prefixes. If the ordering can be determined from the key prefixes (i.e. the prefixes are unequal), then the sort can avoid directly comparing the records, avoiding random memory accesses and full record comparisons. For example, if we're sorting a list of strings then we can store the first 8 bytes of the UTF-8 encoded string as the key-prefix and can perform unsigned byte-at-a-time comparisons to determine the ordering of strings based on their prefixes, only resorting to full comparisons for strings that share a common prefix. In cases where the sort key can fit entirely in the space allotted for the key prefix (e.g. the sorting key is an integer), we completely avoid direct record comparison.
In this patch's implementation of key-prefix sorting, our sorter's internal array stores a 64-bit long and 64-bit pointer for each record being sorted. The key prefixes are generated by the user when inserting records into the sorter, which uses a user-defined comparison function for comparing them. The `PrefixComparators` object implements a set of comparators for many common types, including primitive numeric types and UTF-8 strings.
The actual sorting is implemented by `UnsafeInMemorySorter`. Most consumers will not use this directly, but instead will use `UnsafeExternalSorter`, a class which implements a sort that can spill to disk in response to memory pressure. Internally, `UnsafeExternalSorter` creates `UnsafeInMemorySorters` to perform sorting and uses `UnsafeSortSpillReader/Writer` to spill and read back runs of sorted records and `UnsafeSortSpillMerger` to merge multiple sorted spills into a single sorted iterator. This external sorter integrates with Spark's existing ShuffleMemoryManager for controlling spilling.
Many parts of this sorter's design are based on / copied from the more specialized external sort implementation that I designed for the new UnsafeShuffleManager write path; see #5868 for more details on that patch.
### Sorting rows in Spark SQL
For now, `UnsafeExternalSorter` is only used by Spark SQL, which uses it to implement a new sort operator, `UnsafeExternalSort`. This sort operator uses a SQL-specific class called `UnsafeExternalRowSorter` that configures an `UnsafeExternalSorter` to use prefix generators and comparators that operate on rows encoded in the UnsafeRow format that was designed for Project Tungsten.
I used some interesting unit-testing techniques to test this patch's SQL-specific components. `UnsafeExternalSortSuite` uses the SQL random data generators introduced in #7176 to test the UnsafeSort operator with all atomic types both with and without nullability and in both ascending and descending sort orders. `PrefixComparatorsSuite` contains a cool use of ScalaCheck + ScalaTest's `GeneratorDrivenPropertyChecks` in order to test UTF8String prefix comparison.
### Misc. additional improvements made in this patch
This patch made several miscellaneous improvements to related code in Spark SQL:
- The logic for selecting physical sort operator implementations, which was partially duplicated in both `Exchange` and `SparkStrategies, has now been consolidated into a `getSortOperator()` helper function in `SparkStrategies`.
- The `SparkPlanTest` unit testing helper trait has been extended with new methods for comparing the output produced by two different physical plans. This makes it easy to write tests which assert that two physical operator implementations should produce the same output. I also added a method for disabling the implicit sorting of outputs prior to comparing them, a change which is necessary in order to be able to write proper SparkPlan tests for sort operators.
### Tasks deferred to followup patches
While most of this patch's features are reasonably well-tested and complete, there are a number of tasks that are intentionally being deferred to followup patches:
- Add tests which mock the ShuffleMemoryManager to check that memory pressure properly triggers spilling (there are examples of this type of test in #5868).
- Add tests to ensure that spill files are properly cleaned up after errors. I'd like to do this in the context of a patch which introduces more general metrics for ensuring proper cleanup of tasks' temporary files; see https://issues.apache.org/jira/browse/SPARK-8966 for more details.
- Metrics integration: there are some open questions regarding how to track / report spill metrics for non-shuffle operations, so I've deferred most of the IO / shuffle metrics integration for now.
- Performance profiling.
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Author: Josh Rosen <joshrosen@databricks.com>
Closes#6444 from JoshRosen/sql-external-sort and squashes the following commits:
6beb467 [Josh Rosen] Remove a bunch of overloaded methods to avoid default args. issue
2bbac9c [Josh Rosen] Merge remote-tracking branch 'origin/master' into sql-external-sort
35dad9f [Josh Rosen] Make sortAnswers = false the default in SparkPlanTest
5135200 [Josh Rosen] Fix spill reading for large rows; add test
2f48777 [Josh Rosen] Add test and fix bug for sorting empty arrays
d1e28bc [Josh Rosen] Merge remote-tracking branch 'origin/master' into sql-external-sort
cd05866 [Josh Rosen] Fix scalastyle
3947fc1 [Josh Rosen] Merge remote-tracking branch 'origin/master' into sql-external-sort
d13ac55 [Josh Rosen] Hacky approach to copying of UnsafeRows for sort followed by limit.
845bea3 [Josh Rosen] Remove unnecessary zeroing of row conversion buffer
c56ec18 [Josh Rosen] Clean up final row copying code.
d31f180 [Josh Rosen] Re-enable NullType sorting test now that SPARK-8868 is fixed
844f4ca [Josh Rosen] Merge remote-tracking branch 'origin/master' into sql-external-sort
293f109 [Josh Rosen] Add missing license header.
f99a612 [Josh Rosen] Fix bugs in string prefix comparison.
9d00afc [Josh Rosen] Clean up prefix comparators for integral types
88aff18 [Josh Rosen] NULL_PREFIX has to be negative infinity for floating point types
613e16f [Josh Rosen] Test with larger data.
1d7ffaa [Josh Rosen] Somewhat hacky fix for descending sorts
08701e7 [Josh Rosen] Fix prefix comparison of null primitives.
b86e684 [Josh Rosen] Set global = true in UnsafeExternalSortSuite.
1c7bad8 [Josh Rosen] Make sorting of answers explicit in SparkPlanTest.checkAnswer().
b81a920 [Josh Rosen] Temporarily enable only the passing sort tests
5d6109d [Josh Rosen] Fix inconsistent handling / encoding of record lengths.
87b6ed9 [Josh Rosen] Fix critical issues in test which led to false negatives.
8d7fbe7 [Josh Rosen] Fixes to multiple spilling-related bugs.
82e21c1 [Josh Rosen] Force spilling in UnsafeExternalSortSuite.
88b72db [Josh Rosen] Test ascending and descending sort orders.
f27be09 [Josh Rosen] Fix tests by binding attributes.
0a79d39 [Josh Rosen] Revert "Undo part of a SparkPlanTest change in #7162 that broke my test."
7c3c864 [Josh Rosen] Undo part of a SparkPlanTest change in #7162 that broke my test.
9969c14 [Josh Rosen] Merge remote-tracking branch 'origin/master' into sql-external-sort
5822e6f [Josh Rosen] Fix test compilation issue
939f824 [Josh Rosen] Remove code gen experiment.
0dfe919 [Josh Rosen] Implement prefix sort for strings (albeit inefficiently).
66a813e [Josh Rosen] Prefix comparators for float and double
b310c88 [Josh Rosen] Integrate prefix comparators for Int and Long (others coming soon)
95058d9 [Josh Rosen] Add missing SortPrefixUtils file
4c37ba6 [Josh Rosen] Add tests for sorting on all primitive types.
6890863 [Josh Rosen] Fix memory leak on empty inputs.
d246e29 [Josh Rosen] Fix consideration of column types when choosing sort implementation.
6b156fb [Josh Rosen] Some WIP work on prefix comparison.
7f875f9 [Josh Rosen] Commit failing test demonstrating bug in handling objects in spills
41b8881 [Josh Rosen] Get UnsafeInMemorySorterSuite to pass (WIP)
90c2b6a [Josh Rosen] Update test name
6d6a1e6 [Josh Rosen] Centralize logic for picking sort operator implementations
9869ec2 [Josh Rosen] Clean up Exchange code a bit
82bb0ec [Josh Rosen] Fix IntelliJ complaint due to negated if condition
1db845a [Josh Rosen] Many more changes to harmonize with shuffle sorter
ebf9eea [Josh Rosen] Harmonization with shuffle's unsafe sorter
206bfa2 [Josh Rosen] Add some missing newlines at the ends of files
26c8931 [Josh Rosen] Back out some Hive changes that aren't needed anymore
62f0bb8 [Josh Rosen] Update to reflect SparkPlanTest changes
21d7d93 [Josh Rosen] Back out of BlockObjectWriter change
7eafecf [Josh Rosen] Port test to SparkPlanTest
d468a88 [Josh Rosen] Update for InternalRow refactoring
269cf86 [Josh Rosen] Back out SMJ operator change; isolate changes to selection of sort op.
1b841ca [Josh Rosen] WIP towards copying
b420a71 [Josh Rosen] Move most of the existing SMJ code into Java.
dfdb93f [Josh Rosen] SparkFunSuite change
73cc761 [Josh Rosen] Fix whitespace
9cc98f5 [Josh Rosen] Move more code to Java; fix bugs in UnsafeRowConverter length type.
c8792de [Josh Rosen] Remove some debug logging
dda6752 [Josh Rosen] Commit some missing code from an old git stash.
58f36d0 [Josh Rosen] Merge in a sketch of a unit test for the new sorter (now failing).
2bd8c9a [Josh Rosen] Import my original tests and get them to pass.
d5d3106 [Josh Rosen] WIP towards external sorter for Spark SQL.
Author: Jonathan Alter <jonalter@users.noreply.github.com>
Closes#7093 from jonalter/SPARK-7977 and squashes the following commits:
ccd44cc [Jonathan Alter] Changed println to log in ThreadingSuite
7fcac3e [Jonathan Alter] Reverting to println in ThreadingSuite
10724b6 [Jonathan Alter] Changing some printlns to logs in tests
eeec1e7 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
0b1dcb4 [Jonathan Alter] More println cleanup
aedaf80 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
925fd98 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
0c16fa3 [Jonathan Alter] Replacing some printlns with logs
45c7e05 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
5c8e283 [Jonathan Alter] Allowing println in audit-release examples
5b50da1 [Jonathan Alter] Allowing printlns in example files
ca4b477 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
83ab635 [Jonathan Alter] Fixing new printlns
54b131f [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
1cd8a81 [Jonathan Alter] Removing some unnecessary comments and printlns
b837c3a [Jonathan Alter] Disallowing println
These two dependencies were introduced in #7231 to help testing Parquet compatibility with `parquet-thrift`. However, they somehow crash the Scala compiler in Maven builds.
This PR fixes this issue by:
1. Removing these two dependencies, and
2. Instead of generating the testing Parquet file programmatically, checking in an actual testing Parquet file generated by `parquet-thrift` as a test resource.
This is just a quick fix to bring back Maven builds. Need to figure out the root case as binary Parquet files are harder to maintain.
Author: Cheng Lian <lian@databricks.com>
Closes#7330 from liancheng/spark-8959 and squashes the following commits:
cf69512 [Cheng Lian] Brings back Maven builds
This PR fix the long standing issue of serialization between Python RDD and DataFrame, it change to using a customized Pickler for InternalRow to enable customized unpickling (type conversion, especially for UDT), now we can support UDT for UDF, cc mengxr .
There is no generated `Row` anymore.
Author: Davies Liu <davies@databricks.com>
Closes#7301 from davies/sql_ser and squashes the following commits:
81bef71 [Davies Liu] address comments
e9217bd [Davies Liu] add regression tests
db34167 [Davies Liu] Refactor of serialization for Python DataFrame
Author: Cheng Hao <hao.cheng@intel.com>
Closes#6762 from chenghao-intel/str_funcs and squashes the following commits:
b09a909 [Cheng Hao] update the code as feedback
7ebbf4c [Cheng Hao] Add more string expressions
Exception will not be catched during tests.
cc marmbrus rxin
Author: Davies Liu <davies@databricks.com>
Closes#7309 from davies/fallback and squashes the following commits:
969a612 [Davies Liu] throw exception during tests
f844f77 [Davies Liu] fallback
a3091bc [Davies Liu] Merge branch 'master' of github.com:apache/spark into fallback
364a0d6 [Davies Liu] fallback to interpret mode if failed to compile
This PR is based on #7209 authored by Sephiroth-Lin.
Author: Weizhong Lin <linweizhong@huawei.com>
Closes#7314 from liancheng/spark-8928 and squashes the following commits:
75267fe [Cheng Lian] Makes CatalystSchemaConverter sticking to 1.4.x- when handling LISTs in compatible mode
This PR is based on #7209 authored by Sephiroth-Lin.
Author: Weizhong Lin <linweizhong@huawei.com>
Closes#7304 from liancheng/spark-8928 and squashes the following commits:
75267fe [Cheng Lian] Makes CatalystSchemaConverter sticking to 1.4.x- when handling LISTs in compatible mode
Due to the way MiMa works, we currently start a `SQLContext` pretty early on. This causes us to start a `SparkUI` that attempts to bind to port 4040. Because many tests run in parallel on the Jenkins machines, this causes port contention sometimes and fails the MiMa tests.
Note that we already disabled the SparkUI for scalatests. However, the MiMa test is run before we even have a chance to load the default scalatest settings, so we need to explicitly disable the UI ourselves.
Author: Andrew Or <andrew@databricks.com>
Closes#7300 from andrewor14/mima-flaky and squashes the following commits:
b55a547 [Andrew Or] Do not enable SparkUI during tests
JIRA: https://issues.apache.org/jira/browse/SPARK-8866
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#7283 from yijieshen/micro_timestamp and squashes the following commits:
dc735df [Yijie Shen] update CastSuite to avoid round error
714eaea [Yijie Shen] add timestamp_udf into blacklist due to precision lose
c3ca2f4 [Yijie Shen] fix unhandled case in CurrentTimestamp
8d4aa6b [Yijie Shen] use 1us precision for timestamp type
This PR fixes the converter for Python DataFrame, especially for DecimalType
Closes#7106
Author: Davies Liu <davies@databricks.com>
Closes#7131 from davies/decimal_python and squashes the following commits:
4d3c234 [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python
20531d6 [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python
7d73168 [Davies Liu] fix conflit
6cdd86a [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python
7104e97 [Davies Liu] improve type infer
9cd5a21 [Davies Liu] run python tests with SPARK_PREPEND_CLASSES
829a05b [Davies Liu] fix UDT in python
c99e8c5 [Davies Liu] fix mima
c46814a [Davies Liu] convert decimal for Python DataFrames
As rxin suggested in #7298 , we should consider to remove `RDDApi`.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#7302 from sarutak/remove-rddapi and squashes the following commits:
e495d35 [Kousuke Saruta] Fixed mima
cb7ebb9 [Kousuke Saruta] Removed overriding RDDApi
This PR is a follow-up of #6617 and is part of [SPARK-6774] [2], which aims to ensure interoperability and backwards-compatibility for Spark SQL Parquet support. And this one fixes the read path. Now Spark SQL is expected to be able to read legacy Parquet data files generated by most (if not all) common libraries/tools like parquet-thrift, parquet-avro, and parquet-hive. However, we still need to refactor the write path to write standard Parquet LISTs and MAPs ([SPARK-8848] [4]).
### Major changes
1. `CatalystConverter` class hierarchy refactoring
- Replaces `CatalystConverter` trait with a much simpler `ParentContainerUpdater`.
Now instead of extending the original `CatalystConverter` trait, every converter class accepts an updater which is responsible for propagating the converted value to some parent container. For example, appending array elements to a parent array buffer, appending a key-value pairs to a parent mutable map, or setting a converted value to some specific field of a parent row. Root converter doesn't have a parent and thus uses a `NoopUpdater`.
This simplifies the design since converters don't need to care about details of their parent converters anymore.
- Unifies `CatalystRootConverter`, `CatalystGroupConverter` and `CatalystPrimitiveRowConverter` into `CatalystRowConverter`
Specifically, now all row objects are represented by `SpecificMutableRow` during conversion.
- Refactors `CatalystArrayConverter`, and removes `CatalystArrayContainsNullConverter` and `CatalystNativeArrayConverter`
`CatalystNativeArrayConverter` was probably designed with the intention of avoiding boxing costs. However, the way it uses Scala generics actually doesn't achieve this goal.
The new `CatalystArrayConverter` handles both nullable and non-nullable array elements in a consistent way.
- Implements backwards-compatibility rules in `CatalystArrayConverter`
When Parquet records are being converted, schema of Parquet files should have already been verified. So we only need to care about the structure rather than field names in the Parquet schema. Since all map objects represented in legacy systems have the same structure as the standard one (see [backwards-compatibility rules for MAP] [1]), we only need to deal with LIST (namely array) in `CatalystArrayConverter`.
2. Requested columns handling
When specifying requested columns in `RowReadSupport`, we used to use a Parquet `MessageType` converted from a Catalyst `StructType` which contains all requested columns. This is not preferable when taking compatibility and interoperability into consideration. Because the actual Parquet file may have different physical structure from the converted schema.
In this PR, the schema for requested columns is constructed using the following method:
- For a column that exists in the target Parquet file, we extract the column type by name from the full file schema, and construct a single-field `MessageType` for that column.
- For a column that doesn't exist in the target Parquet file, we create a single-field `StructType` and convert it to a `MessageType` using `CatalystSchemaConverter`.
- Unions all single-field `MessageType`s into a full schema containing all requested fields
With this change, we also fix [SPARK-6123] [3] by validating the global schema against each individual Parquet part-files.
### Testing
This PR also adds compatibility tests for parquet-avro, parquet-thrift, and parquet-hive. Please refer to `README.md` under `sql/core/src/test` for more information about these tests. To avoid build time code generation and adding extra complexity to the build system, Java code generated from testing Thrift schema and Avro IDL is also checked in.
[1]: https://github.com/apache/incubator-parquet-format/blob/master/LogicalTypes.md#backward-compatibility-rules-1
[2]: https://issues.apache.org/jira/browse/SPARK-6774
[3]: https://issues.apache.org/jira/browse/SPARK-6123
[4]: https://issues.apache.org/jira/browse/SPARK-8848
Author: Cheng Lian <lian@databricks.com>
Closes#7231 from liancheng/spark-6776 and squashes the following commits:
360fe18 [Cheng Lian] Adds ParquetHiveCompatibilitySuite
c6fbc06 [Cheng Lian] Removes WIP file committed by mistake
b8c1295 [Cheng Lian] Excludes the whole parquet package from MiMa
598c3e8 [Cheng Lian] Adds extra Maven repo for hadoop-lzo, which is a transitive dependency of parquet-thrift
926af87 [Cheng Lian] Simplifies Parquet compatibility test suites
7946ee1 [Cheng Lian] Fixes Scala styling issues
3d7ab36 [Cheng Lian] Fixes .rat-excludes
a8f13bb [Cheng Lian] Using Parquet writer API to do compatibility tests
f2208cd [Cheng Lian] Adds README.md for Thrift/Avro code generation
1d390aa [Cheng Lian] Adds parquet-thrift compatibility test
440f7b3 [Cheng Lian] Adds generated files to .rat-excludes
13b9121 [Cheng Lian] Adds ParquetAvroCompatibilitySuite
06cfe9d [Cheng Lian] Adds comments about TimestampType handling
a099d3e [Cheng Lian] More comments
0cc1b37 [Cheng Lian] Fixes MiMa checks
884d3e6 [Cheng Lian] Fixes styling issue and reverts unnecessary changes
802cbd7 [Cheng Lian] Fixes bugs related to schema merging and empty requested columns
38fe1e7 [Cheng Lian] Adds explicit return type
7fb21f1 [Cheng Lian] Reverts an unnecessary debugging change
1781dff [Cheng Lian] Adds test case for SPARK-8811
6437d4b [Cheng Lian] Assembles requested schema from Parquet file schema
bcac49f [Cheng Lian] Removes the 16-byte restriction of decimals
a74fb2c [Cheng Lian] More comments
0525346 [Cheng Lian] Removes old Parquet record converters
03c3bd9 [Cheng Lian] Refactors Parquet read path to implement backwards-compatibility rules
Adding `()` to the definition of `distinct` in DataFrame allows distinct to be called with parentheses, which is consistent with `dropDuplicates`.
Author: Cheolsoo Park <cheolsoop@netflix.com>
Closes#7298 from piaozhexiu/SPARK-8908 and squashes the following commits:
7f0d923 [Cheolsoo Park] Add () to distinct definition in dataframe
Just a baby step towards making it more efficient.
Author: Reynold Xin <rxin@databricks.com>
Closes#7282 from rxin/SPARK-8888 and squashes the following commits:
3da51ae [Reynold Xin] [SPARK-8888][SQL] Use java.util.HashMap in DynamicPartitionWriterContainer.
We need a new data type to represent time intervals. Because we can't determine how many days in a month, so we need 2 values for interval: a int `months`, a long `microseconds`.
The interval literal syntax looks like:
`interval 3 years -4 month 4 weeks 3 second`
Because we use number of 100ns as value of `TimestampType`, so it may not makes sense to support nano second unit.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7226 from cloud-fan/interval and squashes the following commits:
632062d [Wenchen Fan] address comments
ac348c3 [Wenchen Fan] use case class
0342d2e [Wenchen Fan] use array byte
df9256c [Wenchen Fan] fix style
fd6f18a [Wenchen Fan] address comments
1856af3 [Wenchen Fan] support interval type
Author: Davies Liu <davies@databricks.com>
Closes#7272 from davies/fix_projection and squashes the following commits:
075ef76 [Davies Liu] fix codegen with BroadcastHashJion
JIRA: https://issues.apache.org/jira/browse/SPARK-8785
Currently, the parquet schema merging (`ParquetRelation2.readSchema`) may spend much time to merge duplicate schema. We can select only non duplicate schema and merge them later.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7182 from viirya/improve_parquet_merging and squashes the following commits:
5cf934f [Liang-Chi Hsieh] Refactor it to make it faster.
f3411ea [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into improve_parquet_merging
a63c3ff [Liang-Chi Hsieh] Improve Parquet schema merging.
Remove the `OverrideFunctionRegistry` from the Spark SQL, as the subclasses of `FunctionRegistry` have their own way to the delegate to the right underlying `FunctionRegistry`.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7260 from chenghao-intel/override and squashes the following commits:
164d093 [Cheng Hao] enable the function registry
2ca8459 [Cheng Hao] remove the OverrideFunctionRegistry
https://issues.apache.org/jira/browse/SPARK-8868
Author: Yin Huai <yhuai@databricks.com>
Closes#7262 from yhuai/SPARK-8868 and squashes the following commits:
cb58780 [Yin Huai] Andrew's comment.
e456857 [Yin Huai] Josh's comments.
5122e65 [Yin Huai] If types of all columns are NullTypes, do not use serializer2.
The type alias was there because initially when I moved Row around, I didn't want to do massive changes to the expression code. But now it should be pretty easy to just remove it. One less concept to worry about.
Author: Reynold Xin <rxin@databricks.com>
Closes#7270 from rxin/internalrow and squashes the following commits:
72fc842 [Reynold Xin] [SPARK-8876][SQL] Remove InternalRow type alias in expressions package.
JIRA: https://issues.apache.org/jira/browse/SPARK-8463
Currently, at the reading path, `DriverRegistry` is used to load needed jdbc driver at executors. However, at the writing path, we also need `DriverRegistry` to load jdbc driver.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6900 from viirya/jdbc_write_driver and squashes the following commits:
16cd04b [Liang-Chi Hsieh] Use DriverRegistry to load jdbc driver at writing path.
Adding a function checkConstraints which will check for the constraints to be applied on the dataframe / dataframe schema. Function called before storing the dataframe to an external storage. Function added in the corresponding datasource API.
cc rxin marmbrus
Author: animesh <animesh@apache.spark>
This patch had conflicts when merged, resolved by
Committer: Michael Armbrust <michael@databricks.com>
Closes#7013 from animeshbaranawal/8072 and squashes the following commits:
f70dd0e [animesh] Change IO exception to Analysis Exception
fd45e1b [animesh] 8072: Fix Style Issues
a8a964f [animesh] 8072: Improving on previous commits
3cc4d2c [animesh] Fix Style Issues
1a89115 [animesh] Fix Style Issues
98b4399 [animesh] 8072 : Moved the exception handling to ResolvedDataSource specific to parquet format
7c3d928 [animesh] 8072: Adding check to DataFrameWriter.scala
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#7234 from adrian-wang/exchangeclean and squashes the following commits:
b093ec9 [Daoyuan Wang] remove unused code
This pull request
(1) extracts common functions used by hash outer joins and put it in interface HashOuterJoin
(2) adds ShuffledHashOuterJoin and BroadcastHashOuterJoin
(3) adds test cases for shuffled and broadcast hash outer join
(3) makes SparkPlanTest to support binary or more complex operators, and fixes bugs in plan composition in SparkPlanTest
Author: kai <kaizeng@eecs.berkeley.edu>
Closes#7162 from kai-zeng/outer and squashes the following commits:
3742359 [kai] Fix not-serializable exception for code-generated keys in broadcasted relations
14e4bf8 [kai] Use CanBroadcast in broadcast outer join planning
dc5127e [kai] code style fixes
b5a4efa [kai] (1) Add broadcast hash outer join, (2) Fix SparkPlanTest
Add Python API for hex/unhex, also cleanup Hex/Unhex
Author: Davies Liu <davies@databricks.com>
Closes#7223 from davies/hex and squashes the following commits:
6f1249d [Davies Liu] no explicit rule to cast string into binary
711a6ed [Davies Liu] fix test
f9fe5a3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into hex
f032fbb [Davies Liu] Merge branch 'hex' of github.com:davies/spark into hex
49e325f [Davies Liu] Merge branch 'master' of github.com:apache/spark into hex
b31fc9a [Davies Liu] Update math.scala
25156b7 [Davies Liu] address comments and fix test
c3af78c [Davies Liu] address commments
1a24082 [Davies Liu] Add Python API for hex and unhex
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7237 from cloud-fan/parser and squashes the following commits:
e7b49bb [Wenchen Fan] support using keyword in column name
When pruning partitions for a query plan, a message is logged indicating what how many partitions were selected based on predicate criteria, and what percent were pruned.
The current release erroneously uses `1 - total/selected` to compute this quantity, leading to nonsense messages like "pruned -1000% partitions". The fix is simple and obvious.
Author: Steve Lindemann <steve.lindemann@engineersgatelp.com>
Closes#7227 from srlindemann/master and squashes the following commits:
c788061 [Steve Lindemann] fix percentPruned log message
This is a the follow up of #6843.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#7230 from chenghao-intel/str_funcs2_followup and squashes the following commits:
52cc553 [Cheng Hao] update the code as comment
ping liancheng
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#7224 from viirya/few_fix_catalystschema and squashes the following commits:
d994330 [Liang-Chi Hsieh] Minor fix for CatalystSchemaConverter.
Jira: https://issues.apache.org/jira/browse/SPARK-8270
Info: I can not build the latest master, it stucks during the build process: `[INFO] Dependency-reduced POM written at: /Users/tarek/test/spark/bagel/dependency-reduced-pom.xml`
Author: Tarek Auel <tarek.auel@googlemail.com>
Closes#7214 from tarekauel/SPARK-8270 and squashes the following commits:
ab348b9 [Tarek Auel] Merge branch 'master' into SPARK-8270
a2ad318 [Tarek Auel] [SPARK-8270] changed order of fields
d91b12c [Tarek Auel] [SPARK-8270] python fix
adbd075 [Tarek Auel] [SPARK-8270] fixed typo
23185c9 [Tarek Auel] [SPARK-8270] levenshtein distance
Implemented type coercion for udf arguments in Scala. The changes include-
* Add `with ExpectsInputTypes ` to `ScalaUDF` class.
* Pass down argument types info from `UDFRegistration` and `functions`.
With this patch, the example query in [SPARK-8572](https://issues.apache.org/jira/browse/SPARK-8572) no longer throws a type cast error at runtime.
Also added a unit test to `UDFSuite` in which a decimal type is passed to a udf that expects an int.
Author: Cheolsoo Park <cheolsoop@netflix.com>
Closes#7203 from piaozhexiu/SPARK-8572 and squashes the following commits:
2d0ed15 [Cheolsoo Park] Incorporate comments
dce1efd [Cheolsoo Park] Fix unit tests and update the codegen script
066deed [Cheolsoo Park] Type coercion for udf inputs
One test for each of the GROUP BY, WHERE and HAVING clauses, and one that combines all three with an additional UDF in the SELECT.
(Since this is my first attempt at contributing to SPARK, meta-level guidance on anything I've screwed up would be greatly appreciated, whether important or minor.)
Author: Spiro Michaylov <spiro@michaylov.com>
Closes#7207 from spirom/udf-test-branch and squashes the following commits:
6bbba9e [Spiro Michaylov] Responded to review comments on UDF unit tests
1a3c5ff [Spiro Michaylov] Added several UDF unit tests for Spark SQL
cc rxin
Having back ticks or null as elements causes problems.
Since elements become column names, we have to drop them from the element as back ticks are special characters.
Having null throws exceptions, we could replace them with empty strings.
Handling back ticks should be improved for 1.5
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#7201 from brkyvz/weird-ct-elements and squashes the following commits:
e06b840 [Burak Yavuz] fix scalastyle
93a0d3f [Burak Yavuz] added tests for NaN and Infinity
9dba6ce [Burak Yavuz] address cr1
db71dbd [Burak Yavuz] handle special characters in elements in crosstab
This fixes code generation for queries containing `ORDER BY NULL`. Previously, the generated code would fail to compile.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7179 from JoshRosen/generate-order-fixes and squashes the following commits:
6ef49a6 [Josh Rosen] Fix ORDER BY NULL
0036696 [Josh Rosen] Add regression test for SPARK-8782 (ORDER BY NULL)
Also improve the performance of hex/unhex
Author: Davies Liu <davies@databricks.com>
Closes#7181 from davies/hex and squashes the following commits:
f032fbb [Davies Liu] Merge branch 'hex' of github.com:davies/spark into hex
49e325f [Davies Liu] Merge branch 'master' of github.com:apache/spark into hex
b31fc9a [Davies Liu] Update math.scala
25156b7 [Davies Liu] address comments and fix test
c3af78c [Davies Liu] address commments
1a24082 [Davies Liu] Add Python API for hex and unhex
This is a follow up of [SPARK-8283](https://issues.apache.org/jira/browse/SPARK-8283) ([PR-6828](https://github.com/apache/spark/pull/6828)), to support both `struct` and `named_struct` in Spark SQL.
After [#6725](https://github.com/apache/spark/pull/6828), the semantic of [`CreateStruct`](https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala#L56) methods have changed a little and do not limited to cols of `NamedExpressions`, it will name non-NamedExpression fields following the hive convention, col1, col2 ...
This PR would both loosen [`struct`](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/functions.scala#L723) to take children of `Expression` type and add `named_struct` support.
Author: Yijie Shen <henry.yijieshen@gmail.com>
Closes#6874 from yijieshen/SPARK-8283 and squashes the following commits:
4cd3375ac [Yijie Shen] change struct documentation
d599d0b [Yijie Shen] rebase code
9a7039e [Yijie Shen] fix reviews and regenerate golden answers
b487354 [Yijie Shen] replace assert using checkAnswer
f07e114 [Yijie Shen] tiny fix
9613be9 [Yijie Shen] review fix
7fef712 [Yijie Shen] Fix checkInputTypes' implementation using foldable and nullable
60812a7 [Yijie Shen] Fix type check
828d694 [Yijie Shen] remove unnecessary resolved assertion inside dataType method
fd3cd8e [Yijie Shen] remove type check from eval
7a71255 [Yijie Shen] tiny fix
ccbbd86 [Yijie Shen] Fix reviews
47da332 [Yijie Shen] remove nameStruct API from DataFrame
917e680 [Yijie Shen] Fix reviews
4bd75ad [Yijie Shen] loosen struct method in functions.scala to take Expression children
0acb7be [Yijie Shen] Add CreateNamedStruct in both DataFrame function API and FunctionRegistery
Jira:
https://issues.apache.org/jira/browse/SPARK-8223https://issues.apache.org/jira/browse/SPARK-8224
~~I am aware of #7174 and will update this pr, if it's merged.~~ Done
I don't know if #7034 can simplify this, but we can have a look on it, if it gets merged
rxin In the Jira ticket the function as no second argument. I added a `numBits` argument that allows to specify the number of bits. I guess this improves the usability. I wanted to add `shiftleft(value)` as well, but the `selectExpr` dataframe tests crashes, if I have both. I order to do this, I added the following to the functions.scala `def shiftRight(e: Column): Column = ShiftRight(e.expr, lit(1).expr)`, but as I mentioned this doesn't pass tests like `df.selectExpr("shiftRight(a)", ...` (not enough arguments exception).
If we need the bitwise shift in order to be hive compatible, I suggest to add `shiftLeft` and something like `shiftLeftX`
Author: Tarek Auel <tarek.auel@googlemail.com>
Closes#7178 from tarekauel/8223 and squashes the following commits:
8023bb5 [Tarek Auel] [SPARK-8223][SPARK-8224] fixed test
f3f64e6 [Tarek Auel] [SPARK-8223][SPARK-8224] Integer -> Int
f628706 [Tarek Auel] [SPARK-8223][SPARK-8224] removed toString; updated function description
3b56f2a [Tarek Auel] Merge remote-tracking branch 'origin/master' into 8223
5189690 [Tarek Auel] [SPARK-8223][SPARK-8224] minor fix and style fix
9434a28 [Tarek Auel] Merge remote-tracking branch 'origin/master' into 8223
44ee324 [Tarek Auel] [SPARK-8223][SPARK-8224] docu fix
ac7fe9d [Tarek Auel] [SPARK-8223][SPARK-8224] right and left bit shift
The detail problem story is in https://issues.apache.org/jira/browse/SPARK-8690
General speaking, I add a config spark.sql.parquet.mergeSchema to achieve the sqlContext.load("parquet" , Map( "path" -> "..." , "mergeSchema" -> "false" ))
It will become a simple flag and without any side affect.
Author: Wisely Chen <wiselychen@appier.com>
Closes#7070 from thegiive/SPARK8690 and squashes the following commits:
c6f3e86 [Wisely Chen] Refactor some code style and merge the test case to ParquetSchemaMergeConfigSuite
94c9307 [Wisely Chen] Remove some style problem
db8ef1b [Wisely Chen] Change config to SQLConf and add test case
b6806fb [Wisely Chen] remove text
c0edb8c [Wisely Chen] [SPARK-8690] add a config spark.sql.parquet.mergeSchema to disable datasource API schema merge feature.
Parameter order of deprecated annotation in package object sql is wrong
>>deprecated("1.3.0", "use DataFrame") .
This has to be changed to deprecated("use DataFrame", "1.3.0")
Author: Vinod K C <vinod.kc@huawei.com>
Closes#7183 from vinodkc/fix_deprecated_param_order and squashes the following commits:
1cbdbe8 [Vinod K C] Modified the message
700911c [Vinod K C] Changed order of parameters
It's a really minor issue but there is an example with wrong lambda-expression usage in `SQLContext.scala` like as follows.
```
sqlContext.udf().register("myUDF",
(Integer arg1, String arg2) -> arg2 + arg1), <- We have an extra `)` here.
DataTypes.StringType);
```
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#7187 from sarutak/fix-minor-wrong-lambda-expression and squashes the following commits:
a13196d [Kousuke Saruta] Fixed minor wrong lambda expression example.
cc chenghao-intel adrian-wang
Author: zhichao.li <zhichao.li@intel.com>
Closes#7113 from zhichao-li/unhex and squashes the following commits:
379356e [zhichao.li] remove exception checking
a4ae6dc [zhichao.li] add udf_unhex to whitelist
fe5c14a [zhichao.li] add todigit
607d7a3 [zhichao.li] use checkInputTypes
bffd37f [zhichao.li] change to use Hex in apache common package
cde73f5 [zhichao.li] update to use AutoCastInputTypes
11945c7 [zhichao.li] style
c852d46 [zhichao.li] Add function unhex
improve the empty check in `parseAttributeName` so that we can allow empty string as column name.
Close https://github.com/apache/spark/pull/7117
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7149 from cloud-fan/8621 and squashes the following commits:
efa9e3e [Wenchen Fan] support empty string
Author: Reynold Xin <rxin@databricks.com>
Closes#7148 from rxin/calludf-closure and squashes the following commits:
00df372 [Reynold Xin] Fixed index out of bound exception.
4beba76 [Reynold Xin] [SPARK-8750][SQL] Remove the closure in functions.callUdf.
Developers have already familiar with `queryExecution.toRDD` as internal row RDD, and we should not add new concept.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7116 from cloud-fan/internal-rdd and squashes the following commits:
24756ca [Wenchen Fan] remove internalRowRDD
Author: Reynold Xin <rxin@databricks.com>
Closes#7137 from rxin/SPARK-8741 and squashes the following commits:
32c7e75 [Reynold Xin] [SPARK-8741][SQL] Remove e and pi from DataFrame functions.
Hi Michael,
this Pull-Request is a follow-up to [PR-6242](https://github.com/apache/spark/pull/6242). I removed the two obsolete test cases from the HiveQuerySuite and deleted the corresponding golden answer files.
Thanks for your review!
Author: Christian Kadner <ckadner@us.ibm.com>
Closes#6983 from ckadner/SPARK-6785 and squashes the following commits:
ab1e79b [Christian Kadner] Merge remote-tracking branch 'origin/SPARK-6785' into SPARK-6785
1fed877 [Christian Kadner] [SPARK-6785][SQL] failed Scala style test, remove spaces on empty line DateTimeUtils.scala:61
9d8021d [Christian Kadner] [SPARK-6785][SQL] merge recent changes in DateTimeUtils & MiscFunctionsSuite
b97c3fb [Christian Kadner] [SPARK-6785][SQL] move test case for DateTimeUtils to DateTimeUtilsSuite
a451184 [Christian Kadner] [SPARK-6785][SQL] fix DateTimeUtils.fromJavaDate(java.util.Date) for Dates before 1970
Codegen takes three steps:
1. Take a list of expressions, convert them into Java source code and a list of expressions that don't not support codegen (fallback to interpret mode).
2. Compile the Java source into Java class (bytecode)
3. Using the Java class and the list of expression to build a Projection.
Currently, we cache the whole three steps, the key is a list of expression, result is projection. Because some of expressions (which may not thread-safe, for example, Random) will be hold by the Projection, the projection maybe not thread safe.
This PR change to only cache the second step, then we can build projection using codegen even some expressions are not thread-safe, because the cache will not hold any expression anymore.
cc marmbrus rxin JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#7101 from davies/codegen_safe and squashes the following commits:
7dd41f1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into codegen_safe
847bd08 [Davies Liu] don't use scala.refect
4ddaaed [Davies Liu] Merge branch 'master' of github.com:apache/spark into codegen_safe
1793cf1 [Davies Liu] make codegen thread safe
https://issues.apache.org/jira/browse/SPARK-8236
Author: Shilei <shilei.qian@intel.com>
Closes#7108 from qiansl127/Crc32 and squashes the following commits:
5477352 [Shilei] Change to AutoCastInputTypes
5f16e5d [Shilei] Add misc function crc32
Sometimes the user may want to show the complete content of cells. Now `sql("set -v").show()` displays:
The user needs to use something like `sql("set -v").collect().foreach(r => r.toSeq.mkString("\t"))` to show the complete content.
This PR adds a `pretty` parameter to show. If `pretty` is false, `show` won't truncate strings or align cells right.
Author: zsxwing <zsxwing@gmail.com>
Closes#6877 from zsxwing/show and squashes the following commits:
22e28e9 [zsxwing] pretty -> truncate
e582628 [zsxwing] Add pretty parameter to the show method in R
a3cd55b [zsxwing] Fix calling showString in R
923cee4 [zsxwing] Add a "pretty" parameter to show to display long strings
Patch to fix crash with BINARY fields with ENUM original types.
Author: Steven She <steven@canopylabs.com>
Closes#7048 from stevencanopy/SPARK-8669 and squashes the following commits:
2e72979 [Steven She] [SPARK-8669] [SQL] Fix crash with BINARY (ENUM) fields with Parquet 1.7
cc yhuai
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#7100 from brkyvz/ct-flakiness-fix and squashes the following commits:
abc299a [Burak Yavuz] change 'to' to until
7e96d7c [Burak Yavuz] ArrayOutOfBoundsException fixed for DataFrameStatSuite.crosstab
This PR brings arbitrary object support in UnsafeRow (both in grouping key and aggregation buffer).
Two object pools will be created to hold those non-primitive objects, and put the index of them into UnsafeRow. In order to compare the grouping key as bytes, the objects in key will be stored in a unique object pool, to make sure same objects will have same index (used as hashCode).
For StringType and BinaryType, we still put them as var-length in UnsafeRow when initializing for better performance. But for update, they will be an object inside object pools (there will be some garbages left in the buffer).
BTW: Will create a JIRA once issue.apache.org is available.
cc JoshRosen rxin
Author: Davies Liu <davies@databricks.com>
Closes#6959 from davies/unsafe_obj and squashes the following commits:
5ce39da [Davies Liu] fix comment
5e797bf [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_obj
5803d64 [Davies Liu] fix conflict
461d304 [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_obj
2f41c90 [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_obj
b04d69c [Davies Liu] address comments
4859b80 [Davies Liu] fix comments
f38011c [Davies Liu] add a test for grouping by decimal
d2cf7ab [Davies Liu] add more tests for null checking
71983c5 [Davies Liu] add test for timestamp
e8a1649 [Davies Liu] reuse buffer for string
39f09ca [Davies Liu] Merge branch 'master' of github.com:apache/spark into unsafe_obj
035501e [Davies Liu] fix style
236d6de [Davies Liu] support arbitrary object in UnsafeRow
Follow-up of #6902 for being coherent between ```Udf``` and ```UDF```
Author: BenFradet <benjamin.fradet@gmail.com>
Closes#6920 from BenFradet/SPARK-8478 and squashes the following commits:
c500f29 [BenFradet] renamed a few variables in functions to use UDF
8ab0f2d [BenFradet] renamed idUdf to idUDF in SQLQuerySuite
98696c2 [BenFradet] renamed originalUdfs in TestHive to originalUDFs
7738f74 [BenFradet] modified HiveUDFSuite to use only UDF
c52608d [BenFradet] renamed HiveUdfSuite to HiveUDFSuite
e51b9ac [BenFradet] renamed ExtractPythonUdfs to ExtractPythonUDFs
8c756f1 [BenFradet] renamed Hive UDF related code
2a1ca76 [BenFradet] renamed pythonUdfs to pythonUDFs
261e6fb [BenFradet] renamed ScalaUdf to ScalaUDF
I specifically randomized the test. What crosstab does is equivalent to a countByKey, therefore if this test fails again for any reason, we will know that we hit a corner case or something.
cc rxin marmbrus
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#7060 from brkyvz/crosstab-fixes and squashes the following commits:
0a65234 [Burak Yavuz] addressed comments v1
d96da7e [Burak Yavuz] fixed wrong ordering of columns in crosstab
cc chenghao-intel adrian-wang
Author: zhichao.li <zhichao.li@intel.com>
Closes#6976 from zhichao-li/hex and squashes the following commits:
e218d1b [zhichao.li] turn off scalastyle for non-ascii
de3f5ea [zhichao.li] non-ascii char
cf9c936 [zhichao.li] give separated buffer for each hex method
967ec90 [zhichao.li] Make 'value' as a feild of Hex
3b2fa13 [zhichao.li] tiny fix
a647641 [zhichao.li] remove duplicate null check
7cab020 [zhichao.li] tiny refactoring
35ecfe5 [zhichao.li] add function hex
In DataFrame.scala, there are examples like as follows.
```
* // The following are equivalent:
* peopleDf.filter($"age" > 15)
* peopleDf.where($"age" > 15)
* peopleDf($"age" > 15)
```
But, I think the last example doesn't work.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#6977 from sarutak/fix-dataframe-example and squashes the following commits:
46efbd7 [Kousuke Saruta] Removed wrong example
Jira: https://issues.apache.org/jira/browse/SPARK-8235
I added the support for sha1. If I understood rxin correctly, sha and sha1 should execute the same algorithm, shouldn't they?
Please take a close look on the Python part. This is adopted from #6934
Author: Tarek Auel <tarek.auel@gmail.com>
Author: Tarek Auel <tarek.auel@googlemail.com>
Closes#6963 from tarekauel/SPARK-8235 and squashes the following commits:
f064563 [Tarek Auel] change to shaHex
7ce3cdc [Tarek Auel] rely on automatic cast
a1251d6 [Tarek Auel] Merge remote-tracking branch 'upstream/master' into SPARK-8235
68eb043 [Tarek Auel] added docstring
be5aff1 [Tarek Auel] improved error message
7336c96 [Tarek Auel] added type check
cf23a80 [Tarek Auel] simplified example
ebf75ef [Tarek Auel] [SPARK-8301] updated the python documentation. Removed sha in python and scala
6d6ff0d [Tarek Auel] [SPARK-8233] added docstring
ea191a9 [Tarek Auel] [SPARK-8233] fixed signatureof python function. Added expected type to misc
e3fd7c3 [Tarek Auel] SPARK[8235] added sha to the list of __all__
e5dad4e [Tarek Auel] SPARK[8235] sha / sha1
use same order: boolean, byte, short, int, date, long, timestamp, float, double, string, binary, decimal.
Then we can easily check whether some data types are missing by just one glance, and make sure we handle data/timestamp just as int/long.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7073 from cloud-fan/fix-date and squashes the following commits:
463044d [Wenchen Fan] fix style
51cd347 [Wenchen Fan] refactor handling of date and timestmap
Follow up of [SPARK-8356](https://issues.apache.org/jira/browse/SPARK-8356) and #6902.
Removes the unit test for the now deprecated ```callUdf```
Unit test in SQLQuerySuite now uses ```udf``` instead of ```callUDF```
Replaced ```callUDF``` by ```udf``` where possible in mllib
Author: BenFradet <benjamin.fradet@gmail.com>
Closes#6993 from BenFradet/SPARK-8575 and squashes the following commits:
26f5a7a [BenFradet] 2 spaces instead of 1
1ddb452 [BenFradet] renamed initUDF in order to be consistent in OneVsRest
48ca15e [BenFradet] used vector type tag for udf call in VectorIndexer
0ebd0da [BenFradet] replace the now deprecated callUDF by udf in VectorIndexer
8013409 [BenFradet] replaced the now deprecated callUDF by udf in Predictor
94345b5 [BenFradet] unifomized udf calls in ProbabilisticClassifier
1305492 [BenFradet] uniformized udf calls in Classifier
a672228 [BenFradet] uniformized udf calls in OneVsRest
49e4904 [BenFradet] Revert "removal of the unit test for the now deprecated callUdf"
bbdeaf3 [BenFradet] fixed syntax for init udf in OneVsRest
fe2a10b [BenFradet] callUDF => udf in ProbabilisticClassifier
0ea30b3 [BenFradet] callUDF => udf in Classifier where possible
197ec82 [BenFradet] callUDF => udf in OneVsRest
84d6780 [BenFradet] modified unit test in SQLQuerySuite to use udf instead of callUDF
477709f [BenFradet] removal of the unit test for the now deprecated callUdf
DataFrame supports `filter` function with two types of argument, `Column` and `String`. But `where` doesn't.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#7063 from sarutak/SPARK-8686 and squashes the following commits:
180f9a4 [Kousuke Saruta] Added test
d61aec4 [Kousuke Saruta] Add "where" method with String argument to DataFrame
Currently, we use GenericRow both for Row and InternalRow, which is confusing because it could contain Scala type also Catalyst types.
This PR changes to use GenericInternalRow for InternalRow (contains catalyst types), GenericRow for Row (contains Scala types).
Also fixes some incorrect use of InternalRow or Row.
Author: Davies Liu <davies@databricks.com>
Closes#7003 from davies/internalrow and squashes the following commits:
d05866c [Davies Liu] fix test: rollback changes for pyspark
72878dd [Davies Liu] Merge branch 'master' of github.com:apache/spark into internalrow
efd0b25 [Davies Liu] fix copy of MutableRow
87b13cf [Davies Liu] fix test
d2ebd72 [Davies Liu] fix style
eb4b473 [Davies Liu] mark expensive API as final
bd4e99c [Davies Liu] Merge branch 'master' of github.com:apache/spark into internalrow
bdfb78f [Davies Liu] remove BaseMutableRow
6f99a97 [Davies Liu] fix catalyst test
defe931 [Davies Liu] remove BaseRow
288b31f [Davies Liu] Merge branch 'master' of github.com:apache/spark into internalrow
9d24350 [Davies Liu] separate Row and InternalRow (part 2)
In `CatalystTypeConverters.createToCatalystConverter`, we add special handling for primitive types. We can apply this strategy to more places to improve performance.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#7018 from cloud-fan/converter and squashes the following commits:
8b16630 [Wenchen Fan] another fix
326c82c [Wenchen Fan] optimize type converter
`HadoopFsRelation` subclasses, especially `ParquetRelation2` should set its own output format class, so that the default output committer can be setup correctly when doing appending (where we ignore user defined output committers).
Author: Cheng Lian <lian@databricks.com>
Closes#6998 from liancheng/spark-8604 and squashes the following commits:
9be51d1 [Cheng Lian] Adds more comments
6db1368 [Cheng Lian] HadoopFsRelation subclasses should set their output format class
a follow up of https://github.com/apache/spark/pull/6405.
Note: It's not a big change, a lot of changing is due to I swap some code in `aggregates.scala` to make aggregate functions right below its corresponding aggregate expressions.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6723 from cloud-fan/type-check and squashes the following commits:
2124301 [Wenchen Fan] fix tests
5a658bb [Wenchen Fan] add tests
287d3bb [Wenchen Fan] apply type check interface to more expressions
This PR introduces `CatalystSchemaConverter` for converting Parquet schema to Spark SQL schema and vice versa. Original conversion code in `ParquetTypesConverter` is removed. Benefits of the new version are:
1. When converting Spark SQL schemas, it generates standard Parquet schemas conforming to [the most updated Parquet format spec] [1]. Converting to old style Parquet schemas is also supported via feature flag `spark.sql.parquet.followParquetFormatSpec` (which is set to `false` for now, and should be set to `true` after both read and write paths are fixed).
Note that although this version of Parquet format spec hasn't been officially release yet, Parquet MR 1.7.0 already sticks to it. So it should be safe to follow.
1. It implements backwards-compatibility rules described in the most updated Parquet format spec. Thus can recognize more schema patterns generated by other/legacy systems/tools.
1. Code organization follows convention used in [parquet-mr] [2], which is easier to follow. (Structure of `CatalystSchemaConverter` is similar to `AvroSchemaConverter`).
To fully implement backwards-compatibility rules in both read and write path, we also need to update `CatalystRowConverter` (which is responsible for converting Parquet records to `Row`s), `RowReadSupport`, and `RowWriteSupport`. These would be done in follow-up PRs.
TODO
- [x] More schema conversion test cases for legacy schema patterns.
[1]: ea09522659/LogicalTypes.md
[2]: https://github.com/apache/parquet-mr/
Author: Cheng Lian <lian@databricks.com>
Closes#6617 from liancheng/spark-6777 and squashes the following commits:
2a2062d [Cheng Lian] Don't convert decimals without precision information
b60979b [Cheng Lian] Adds a constructor which accepts a Configuration, and fixes default value of assumeBinaryIsString
743730f [Cheng Lian] Decimal scale shouldn't be larger than precision
a104a9e [Cheng Lian] Fixes Scala style issue
1f71d8d [Cheng Lian] Adds feature flag to allow falling back to old style Parquet schema conversion
ba84f4b [Cheng Lian] Fixes MapType schema conversion bug
13cb8d5 [Cheng Lian] Fixes MiMa failure
81de5b0 [Cheng Lian] Fixes UDT, workaround read path, and add tests
28ef95b [Cheng Lian] More AnalysisExceptions
b10c322 [Cheng Lian] Replaces require() with analysisRequire() which throws AnalysisException
cceaf3f [Cheng Lian] Implements backwards compatibility rules in CatalystSchemaConverter
make the `TakeOrdered` strategy and operator more general, such that it can optionally handle a projection when necessary
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6780 from cloud-fan/limit and squashes the following commits:
34aa07b [Wenchen Fan] revert
07d5456 [Wenchen Fan] clean closure
20821ec [Wenchen Fan] fix
3676a82 [Wenchen Fan] address comments
b558549 [Wenchen Fan] address comments
214842b [Wenchen Fan] fix style
2d8be83 [Wenchen Fan] add LimitPushDown
948f740 [Wenchen Fan] fix existing
https://issues.apache.org/jira/browse/SPARK-8578
It is not very safe to use a custom output committer when append data to an existing dir. This changes adds the logic to check if we are appending data, and if so, we use the output committer associated with the file output format.
Author: Yin Huai <yhuai@databricks.com>
Closes#6964 from yhuai/SPARK-8578 and squashes the following commits:
43544c4 [Yin Huai] Do not use a custom output commiter when appendiing data.
This PR improves the error message shown when conflicting partition column names are detected. This can be particularly annoying and confusing when there are a large number of partitions while a handful of them happened to contain unexpected temporary file(s). Now all suspicious directories are listed as below:
```
java.lang.AssertionError: assertion failed: Conflicting partition column names detected:
Partition column name list #0: b, c, d
Partition column name list #1: b, c
Partition column name list #2: b
For partitioned table directories, data files should only live in leaf directories. Please check the following directories for unexpected files:
file:/tmp/foo/b=0
file:/tmp/foo/b=1
file:/tmp/foo/b=1/c=1
file:/tmp/foo/b=0/c=0
```
Author: Cheng Lian <lian@databricks.com>
Closes#6610 from liancheng/part-errmsg and squashes the following commits:
7d05f2c [Cheng Lian] Fixes Scala style issue
a149250 [Cheng Lian] Adds test case for the error message
6b74dd8 [Cheng Lian] Also lists suspicious non-leaf partition directories
a935eb8 [Cheng Lian] Improves error message when conflicting partition columns are found
Add `sampleBy` to DataFrame. rxin
Author: Xiangrui Meng <meng@databricks.com>
Closes#6769 from mengxr/SPARK-7157 and squashes the following commits:
991f26f [Xiangrui Meng] fix seed
4a14834 [Xiangrui Meng] move sampleBy to stat
832f7cc [Xiangrui Meng] add sampleBy to DataFrame
This PR only applies to master branch (1.5.0-SNAPSHOT) since it references `org.apache.parquet` classes which only appear in Parquet 1.7.0.
Author: Cheng Lian <lian@databricks.com>
Closes#6683 from liancheng/output-committer-docs and squashes the following commits:
b4648b8 [Cheng Lian] Removes spark.sql.sources.outputCommitterClass as it's not a public option
ee63923 [Cheng Lian] Updates docs and comments of data sources and Parquet output committer options
The logical plan `Expand` takes the `output` as constructor argument, which break the references chain. We need to refactor the code, as well as the column pruning.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#5780 from chenghao-intel/expand and squashes the following commits:
76e4aa4 [Cheng Hao] revert the change for case insenstive
7c10a83 [Cheng Hao] refactor the grouping sets
the syntax was incorrect in the example in explode
Author: lockwobr <lockwobr@gmail.com>
Closes#6943 from lockwobr/master and squashes the following commits:
3d864d1 [lockwobr] updated the documentation for explode
Users can now do
```scala
left.join(broadcast(right), "joinKey")
```
to give the query planner a hint that "right" DataFrame is small and should be broadcasted.
Author: Reynold Xin <rxin@databricks.com>
Closes#6751 from rxin/broadcastjoin-hint and squashes the following commits:
953eec2 [Reynold Xin] Code review feedback.
88752d8 [Reynold Xin] Fixed import.
8187b88 [Reynold Xin] [SPARK-8300] DataFrame hint for broadcast join.
Deprecates ```callUdf``` in favor of ```callUDF```.
Author: BenFradet <benjamin.fradet@gmail.com>
Closes#6902 from BenFradet/SPARK-8356 and squashes the following commits:
ef4e9d8 [BenFradet] deprecated callUDF, use udf instead
9b1de4d [BenFradet] reinstated unit test for the deprecated callUdf
cbd80a5 [BenFradet] deprecated callUdf in favor of callUDF
Currently we auto alias expression in parser. However, during parser phase we don't have enough information to do the right alias. For example, Generator that has more than 1 kind of element need MultiAlias, ExtractValue don't need Alias if it's in middle of a ExtractValue chain.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6647 from cloud-fan/alias and squashes the following commits:
552eba4 [Wenchen Fan] fix python
5b5786d [Wenchen Fan] fix agg
73a90cb [Wenchen Fan] fix case-preserve of ExtractValue
4cfd23c [Wenchen Fan] fix order by
d18f401 [Wenchen Fan] refine
9f07359 [Wenchen Fan] address comments
39c1aef [Wenchen Fan] small fix
33640ec [Wenchen Fan] auto alias expressions in analyzer
This PR fixes a Parquet output file name collision bug which may cause data loss. Changes made:
1. Identify each write job issued by `InsertIntoHadoopFsRelation` with a UUID
All concrete data sources which extend `HadoopFsRelation` (Parquet and ORC for now) must use this UUID to generate task output file path to avoid name collision.
2. Make `TestHive` use a local mode `SparkContext` with 32 threads to increase parallelism
The major reason for this is that, the original parallelism of 2 is too low to reproduce the data loss issue. Also, higher concurrency may potentially caught more concurrency bugs during testing phase. (It did help us spotted SPARK-8501.)
3. `OrcSourceSuite` was updated to workaround SPARK-8501, which we detected along the way.
NOTE: This PR is made a little bit more complicated than expected because we hit two other bugs on the way and have to work them around. See [SPARK-8501] [1] and [SPARK-8513] [2].
[1]: https://github.com/liancheng/spark/tree/spark-8501
[2]: https://github.com/liancheng/spark/tree/spark-8513
----
Some background and a summary of offline discussion with yhuai about this issue for better understanding:
In 1.4.0, we added `HadoopFsRelation` to abstract partition support of all data sources that are based on Hadoop `FileSystem` interface. Specifically, this makes partition discovery, partition pruning, and writing dynamic partitions for data sources much easier.
To support appending, the Parquet data source tries to find out the max part number of part-files in the destination directory (i.e., `<id>` in output file name `part-r-<id>.gz.parquet`) at the beginning of the write job. In 1.3.0, this step happens on driver side before any files are written. However, in 1.4.0, this is moved to task side. Unfortunately, for tasks scheduled later, they may see wrong max part number generated of files newly written by other finished tasks within the same job. This actually causes a race condition. In most cases, this only causes nonconsecutive part numbers in output file names. But when the DataFrame contains thousands of RDD partitions, it's likely that two tasks may choose the same part number, then one of them gets overwritten by the other.
Before `HadoopFsRelation`, Spark SQL already supports appending data to Hive tables. From a user's perspective, these two look similar. However, they differ a lot internally. When data are inserted into Hive tables via Spark SQL, `InsertIntoHiveTable` simulates Hive's behaviors:
1. Write data to a temporary location
2. Move data in the temporary location to the final destination location using
- `Hive.loadTable()` for non-partitioned table
- `Hive.loadPartition()` for static partitions
- `Hive.loadDynamicPartitions()` for dynamic partitions
The important part is that, `Hive.copyFiles()` is invoked in step 2 to move the data to the destination directory (I found the name is kinda confusing since no "copying" occurs here, we are just moving and renaming stuff). If a file in the source directory and another file in the destination directory happen to have the same name, say `part-r-00001.parquet`, the former is moved to the destination directory and renamed with a `_copy_N` postfix (`part-r-00001_copy_1.parquet`). That's how Hive handles appending and avoids name collision between different write jobs.
Some alternatives fixes considered for this issue:
1. Use a similar approach as Hive
This approach is not preferred in Spark 1.4.0 mainly because file metadata operations in S3 tend to be slow, especially for tables with lots of file and/or partitions. That's why `InsertIntoHadoopFsRelation` just inserts to destination directory directly, and is often used together with `DirectParquetOutputCommitter` to reduce latency when working with S3. This means, we don't have the chance to do renaming, and must avoid name collision from the very beginning.
2. Same as 1.3, just move max part number detection back to driver side
This isn't doable because unlike 1.3, 1.4 also takes dynamic partitioning into account. When inserting into dynamic partitions, we don't know which partition directories will be touched on driver side before issuing the write job. Checking all partition directories is simply too expensive for tables with thousands of partitions.
3. Add extra component to output file names to avoid name collision
This seems to be the only reasonable solution for now. To be more specific, we need a JOB level unique identifier to identify all write jobs issued by `InsertIntoHadoopFile`. Notice that TASK level unique identifiers can NOT be used. Because in this way a speculative task will write to a different output file from the original task. If both tasks succeed, duplicate output will be left behind. Currently, the ORC data source adds `System.currentTimeMillis` to the output file name for uniqueness. This doesn't work because of exactly the same reason.
That's why this PR adds a job level random UUID in `BaseWriterContainer` (which is used by `InsertIntoHadoopFsRelation` to issue write jobs). The drawback is that record order is not preserved any more (output files of a later job may be listed before those of a earlier job). However, we never promise to preserve record order when writing data, and Hive doesn't promise this either because the `_copy_N` trick breaks the order.
Author: Cheng Lian <lian@databricks.com>
Closes#6864 from liancheng/spark-8406 and squashes the following commits:
db7a46a [Cheng Lian] More comments
f5c1133 [Cheng Lian] Addresses comments
85c478e [Cheng Lian] Workarounds SPARK-8513
088c76c [Cheng Lian] Adds comment about SPARK-8501
99a5e7e [Cheng Lian] Uses job level UUID in SimpleTextRelation and avoids double task abortion
4088226 [Cheng Lian] Works around SPARK-8501
1d7d206 [Cheng Lian] Adds more logs
8966bbb [Cheng Lian] Fixes Scala style issue
18b7003 [Cheng Lian] Uses job level UUID to take speculative tasks into account
3806190 [Cheng Lian] Lets TestHive use all cores by default
748dbd7 [Cheng Lian] Adding UUID to output file name to avoid accidental overwriting
In earlier versions of Spark SQL we casted `TimestampType` and `DataType` to `StringType` when it was involved in a binary comparison with a `StringType`. This allowed comparing a timestamp with a partial date as a user would expect.
- `time > "2014-06-10"`
- `time > "2014"`
In 1.4.0 we tried to cast the String instead into a Timestamp. However, since partial dates are not a valid complete timestamp this results in `null` which results in the tuple being filtered.
This PR restores the earlier behavior. Note that we still special case equality so that these comparisons are not affected by not printing zeros for subsecond precision.
Author: Michael Armbrust <michael@databricks.com>
Closes#6888 from marmbrus/timeCompareString and squashes the following commits:
bdef29c [Michael Armbrust] test partial date
1f09adf [Michael Armbrust] special handling of equality
1172c60 [Michael Armbrust] more test fixing
4dfc412 [Michael Armbrust] fix tests
aaa9508 [Michael Armbrust] newline
04d908f [Michael Armbrust] [SPARK-8420][SQL] Fix comparision of timestamps/dates with strings
Author: Nathan Howell <nhowell@godaddy.com>
Closes#6799 from NathanHowell/spark-8093 and squashes the following commits:
76ac3e8 [Nathan Howell] [SPARK-8093] [SQL] Remove empty structs inferred from JSON documents
Author: Shilei <shilei.qian@intel.com>
Closes#6779 from qiansl127/MD5 and squashes the following commits:
11fcdb2 [Shilei] Fix the indent
04bd27b [Shilei] Add codegen
da60eb3 [Shilei] Remove checkInputDataTypes function
9509ad0 [Shilei] Format code
12c61f4 [Shilei] Accept only BinaryType for Md5
1df0b5b [Shilei] format to scala type
60ccde1 [Shilei] Add more test case
b8c73b4 [Shilei] Rewrite the type check for Md5
c166167 [Shilei] Add md5 function
I have added it for only Scala.
TODO: we should also support `in` operator in Python.
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#6824 from yu-iskw/SPARK-8348 and squashes the following commits:
e76d02f [Yu ISHIKAWA] Not use infix notation
6f744ac [Yu ISHIKAWA] Fit the test cases because these used the old test data set.
00077d3 [Yu ISHIKAWA] [SPARK-8348][SQL] Add in operator to DataFrame Column
Author: Sandy Ryza <sandy@cloudera.com>
Closes#6679 from sryza/sandy-spark-8135 and squashes the following commits:
c5554ff [Sandy Ryza] SPARK-8135. In SerializableWritable, don't load defaults when instantiating Configuration
This patch introduces `SparkPlanTest`, a base class for unit tests of SparkPlan physical operators. This is analogous to Spark SQL's existing `QueryTest`, which does something similar for end-to-end tests with actual queries.
These helper methods provide nicer error output when tests fail and help developers to avoid writing lots of boilerplate in order to execute manually constructed physical plans.
Author: Josh Rosen <joshrosen@databricks.com>
Author: Josh Rosen <rosenville@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#6885 from JoshRosen/spark-plan-test and squashes the following commits:
f8ce275 [Josh Rosen] Fix some IntelliJ inspections and delete some dead code
84214be [Josh Rosen] Add an extra column which isn't part of the sort
ae1896b [Josh Rosen] Provide implicits automatically
a80f9b0 [Josh Rosen] Merge pull request #4 from marmbrus/pr/6885
d9ab1e4 [Michael Armbrust] Add simple resolver
c60a44d [Josh Rosen] Manually bind references
996332a [Josh Rosen] Add types so that tests compile
a46144a [Josh Rosen] WIP
JIRA: https://issues.apache.org/jira/browse/SPARK-8363
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6823 from viirya/move_sqrt and squashes the following commits:
8977e11 [Liang-Chi Hsieh] Remove unnecessary old tests.
d23e79e [Liang-Chi Hsieh] Explicitly indicate sqrt value sequence.
699f48b [Liang-Chi Hsieh] Use correct @since tag.
8dff6d1 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into move_sqrt
bc2ed77 [Liang-Chi Hsieh] Remove/move arithmetic expression test and expression type checking test. Remove unnecessary Sqrt type rule.
d38492f [Liang-Chi Hsieh] Now sqrt accepts boolean because type casting is handled by HiveTypeCoercion.
297cc90 [Liang-Chi Hsieh] Sqrt only accepts double input.
ef4a21a [Liang-Chi Hsieh] Move sqrt to math.
1. Add `SQLConfEntry` to store the information about a configuration. For those configurations that cannot be found in `sql-programming-guide.md`, I left the doc as `<TODO>`.
2. Verify the value when setting a configuration if this is in SQLConf.
3. Use `SET -v` to display all public configurations.
Author: zsxwing <zsxwing@gmail.com>
Closes#6747 from zsxwing/sqlconf and squashes the following commits:
7d09bad [zsxwing] Use SQLConfEntry in HiveContext
49f6213 [zsxwing] Add getConf, setConf to SQLContext and HiveContext
e014f53 [zsxwing] Merge branch 'master' into sqlconf
93dad8e [zsxwing] Fix the unit tests
cf950c1 [zsxwing] Fix the code style and tests
3c5f03e [zsxwing] Add unsetConf(SQLConfEntry) and fix the code style
a2f4add [zsxwing] getConf will return the default value if a config is not set
037b1db [zsxwing] Add schema to SetCommand
0520c3c [zsxwing] Merge branch 'master' into sqlconf
7afb0ec [zsxwing] Fix the configurations about HiveThriftServer
7e728e3 [zsxwing] Add doc for SQLConfEntry and fix 'toString'
5e95b10 [zsxwing] Add enumConf
c6ba76d [zsxwing] setRawString => setConfString, getRawString => getConfString
4abd807 [zsxwing] Fix the test for 'set -v'
6e47e56 [zsxwing] Fix the compilation error
8973ced [zsxwing] Remove floatConf
1fc3a8b [zsxwing] Remove the 'conf' command and use 'set -v' instead
99c9c16 [zsxwing] Fix tests that use SQLConfEntry as a string
88a03cc [zsxwing] Add new lines between confs and return types
ce7c6c8 [zsxwing] Remove seqConf
f3c1b33 [zsxwing] Refactor SQLConf to display better error message
This PR is a improvement for https://github.com/apache/spark/pull/5189.
The resolution rule for ORDER BY is: first resolve based on what comes from the select clause and then fall back on its child only when this fails.
There are 2 steps. First, try to resolve `Sort` in `ResolveReferences` based on select clause, and ignore exceptions. Second, try to resolve `Sort` in `ResolveSortReferences` and add missing projection.
However, the way we resolve `SortOrder` is wrong. We just resolve `UnresolvedAttribute` and use the result to indicate if we can resolve `SortOrder`. But `UnresolvedAttribute` is only part of `GetField` chain(broken by `GetItem`), so we need to go through the whole chain to indicate if we can resolve `SortOrder`.
With this change, we can also avoid re-throw GetField exception in `CheckAnalysis` which is little ugly.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#5659 from cloud-fan/order-by and squashes the following commits:
cfa79f8 [Wenchen Fan] update test
3245d28 [Wenchen Fan] minor improve
465ee07 [Wenchen Fan] address comment
1fc41a2 [Wenchen Fan] fix SPARK-7067
1. Given a query
`select coalesce(null, 1, '1') from dual` will cause exception:
java.lang.RuntimeException: Could not determine return type of Coalesce for IntegerType,StringType
2. Given a query:
`select case when true then 1 else '1' end from dual` will cause exception:
java.lang.RuntimeException: Types in CASE WHEN must be the same or coercible to a common type: StringType != IntegerType
I checked the code, the main cause is the HiveTypeCoercion doesn't do implicit convert when there is a IntegerType and StringType.
Numeric types can be promoted to string type
Hive will always do this implicit conversion.
Author: OopsOutOfMemory <victorshengli@126.com>
Closes#6551 from OopsOutOfMemory/pnts and squashes the following commits:
7a209d7 [OopsOutOfMemory] rebase master
6018613 [OopsOutOfMemory] convert function to method
4cd5618 [OopsOutOfMemory] limit the data type to primitive type
df365d2 [OopsOutOfMemory] refine
95cbd58 [OopsOutOfMemory] fix style
403809c [OopsOutOfMemory] promote non-string to string when can not found tighestCommonTypeOfTwo
chenghao-intel adrian-wang
Author: dragonli <lisurprise@gmail.com>
Author: zhichao.li <zhichao.li@intel.com>
Closes#6838 from zhichao-li/positive and squashes the following commits:
e1032a0 [dragonli] remove useless import and refactor code
624d438 [zhichao.li] add positive identify function
[SQL][DOC] I found it a bit confusing when I came across it for the first time in the docs
Author: Radek Ostrowski <dest.hawaii@gmail.com>
Author: radek <radek@radeks-MacBook-Pro-2.local>
Closes#6332 from radek1st/master and squashes the following commits:
dae3347 [Radek Ostrowski] fixed typo
c76bb3a [radek] improved a comment
In order to have better performance out of box, this PR turn on codegen by default, then codegen can be tested by sql/test and hive/test.
This PR also fix some corner cases for codegen.
Before 1.5 release, we should re-visit this, turn it off if it's not stable or causing regressions.
cc rxin JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#6726 from davies/enable_codegen and squashes the following commits:
f3b25a5 [Davies Liu] fix warning
73750ea [Davies Liu] fix long overflow when compare
3017a47 [Davies Liu] Merge branch 'master' of github.com:apache/spark into enable_codegen
a7d75da [Davies Liu] Merge branch 'master' of github.com:apache/spark into enable_codegen
ff5b75a [Davies Liu] Merge branch 'master' of github.com:apache/spark into enable_codegen
f4cf2c2 [Davies Liu] fix style
99fc139 [Davies Liu] Merge branch 'enable_codegen' of github.com:davies/spark into enable_codegen
91fc7a2 [Davies Liu] disable codegen for ScalaUDF
207e339 [Davies Liu] Update CodeGenerator.scala
44573a3 [Davies Liu] check thread safety of expression
f3886fa [Davies Liu] don't inline primitiveTerm for null literal
c8e7cd2 [Davies Liu] address comment
a8618c9 [Davies Liu] enable codegen by default
Add aggregates in ORDER BY clauses to the `Aggregate` operator beneath. Project these results away after the Sort.
Based on work by watermen. Also Closes#5290.
Author: Yadong Qi <qiyadong2010@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#6816 from marmbrus/pr/5290 and squashes the following commits:
3226a97 [Michael Armbrust] consistent ordering
eb8938d [Michael Armbrust] no vars
c8b25c1 [Yadong Qi] move the test data.
7f9b736 [Yadong Qi] delete Substring case
a1e87c1 [Yadong Qi] fix conflict
f119849 [Yadong Qi] order by aggregated function
Author: Michael Armbrust <michael@databricks.com>
Closes#6811 from marmbrus/aliasExplodeStar and squashes the following commits:
fbd2065 [Michael Armbrust] more style
806a373 [Michael Armbrust] fix style
7cbb530 [Michael Armbrust] [SPARK-8358][SQL] Wait for child resolution when resolving generatorsa
Also addressed code review feedback from #6754
Author: Reynold Xin <rxin@databricks.com>
Closes#6803 from rxin/abs and squashes the following commits:
d07beba [Reynold Xin] [SPARK-8347] Add unit tests for abs.
This patch updates two pieces of logic that are related to handling of keyOrderings in ShuffleDependencies:
- The Tungsten ShuffleManager falls back to regular SortShuffleManager whenever the shuffle dependency specifies a key ordering, but technically we only need to fall back when an aggregator is also specified. This patch updates the fallback logic to reflect this so that the Tungsten optimizations can apply to more workloads.
- The SQL Exchange operator performs defensive copying of shuffle inputs when a key ordering is specified, but this is unnecessary. The copying was added to guard against cases where ExternalSorter would buffer non-serialized records in memory. When ExternalSorter is configured without an aggregator, it uses the following logic to determine whether to buffer records in a serialized or deserialized format:
```scala
private val useSerializedPairBuffer =
ordering.isEmpty &&
conf.getBoolean("spark.shuffle.sort.serializeMapOutputs", true) &&
ser.supportsRelocationOfSerializedObjects
```
The `newOrdering.isDefined` branch in `ExternalSorter.needToCopyObjectsBeforeShuffle`, removed by this patch, is not necessary:
- It was checked even if we weren't using sort-based shuffle, but this was unnecessary because only SortShuffleManager performs map-side sorting.
- Map-side sorting during shuffle writing is only performed for shuffles that perform map-side aggregation as part of the shuffle (to see this, look at how SortShuffleWriter constructs ExternalSorter). Since SQL never pushes aggregation into Spark's shuffle, we can guarantee that both the aggregator and ordering will be empty and Spark SQL always uses serializers that support relocation, so sort-shuffle will use the serialized pair buffer unless the user has explicitly disabled it via the SparkConf feature-flag. Therefore, I think my optimization in Exchange should be safe.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6773 from JoshRosen/SPARK-8319 and squashes the following commits:
7a14129 [Josh Rosen] Revise comments; add handler to guard against future ShuffleManager implementations
07bb2c9 [Josh Rosen] Update comment to clarify circumstances under which shuffle operates on serialized records
269089a [Josh Rosen] Avoid unnecessary copy in SQL Exchange
34e526e [Josh Rosen] Enable Tungsten shuffle for non-agg shuffles w/ key orderings
cc rxin marmbrus
Author: Davies Liu <davies@databricks.com>
Closes#6802 from davies/cleanup_internalrow and squashes the following commits:
769d2aa [Davies Liu] remove not needed cast
4acbbe4 [Davies Liu] catalyst.Internal -> InternalRow
The original fix uses DecimalType.Unlimited, which is harder to
handle afterwards. There is no scale and most data should fit into
a long, thus DecimalType(20,0) should be better.
Author: Rene Treffer <treffer@measite.de>
Closes#6789 from rtreffer/spark-7897-unsigned-bigint-as-decimal and squashes the following commits:
2006613 [Rene Treffer] Fix type for "unsigned bigint" jdbc loading.
Author: Michael Armbrust <michael@databricks.com>
Closes#6786 from marmbrus/optionsParser and squashes the following commits:
e7d18ef [Michael Armbrust] add dots
99a3452 [Michael Armbrust] [SPARK-8329][SQL] Allow _ in DataSource options
Currently, we use o.a.s.sql.Row both internally and externally. The external interface is wider than what the internal needs because it is designed to facilitate end-user programming. This design has proven to be very error prone and cumbersome for internal Row implementations.
As a first step, we create an InternalRow interface in the catalyst module, which is identical to the current Row interface. And we switch all internal operators/expressions to use this InternalRow instead. When we need to expose Row, we convert the InternalRow implementation into Row for users.
For all public API, we use Row (for example, data source APIs), which will be converted into/from InternalRow by CatalystTypeConverters.
For all internal data sources (Json, Parquet, JDBC, Hive), we use InternalRow for better performance, casted into Row in buildScan() (without change the public API). When create a PhysicalRDD, we cast them back to InternalRow.
cc rxin marmbrus JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#6792 from davies/internal_row and squashes the following commits:
f2abd13 [Davies Liu] fix scalastyle
a7e025c [Davies Liu] move InternalRow into catalyst
30db8ba [Davies Liu] Merge branch 'master' of github.com:apache/spark into internal_row
7cbced8 [Davies Liu] separate Row and InternalRow
It's a follow up of https://github.com/apache/spark/pull/6173, for expressions like `Coalesce` that have a `Seq[Expression]`, when we do semantic equal check for it, we need to do semantic equal check for all of its children.
Also we can just use `Seq[(Expression, NamedExpression)]` instead of `Map[Expression, NamedExpression]` as we only search it with `find`.
chenghao-intel, I agree that we probably never knows `semanticEquals` in a general way, but I think we have done that in `TreeNode`, so we can use similar logic. Then we can handle something like `Coalesce(children: Seq[Expression])` correctly.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6261 from cloud-fan/tmp and squashes the following commits:
4daef88 [Wenchen Fan] address comments
dd8fbd9 [Wenchen Fan] correct semanticEquals
This brings in major improvement in that footers are not read on the driver. This also cleans up the code in parquetTableOperations, where we had to override getSplits to eliminate multiple listStatus calls.
cc liancheng
are there any other changes we need for this ?
Author: Yash Datta <Yash.Datta@guavus.com>
Closes#5889 from saucam/parquet_1.6 and squashes the following commits:
d1bf41e [Yash Datta] SPARK-7340: Fix scalastyle and incorporate review comments
c9aa042 [Yash Datta] SPARK-7340: Use the new user defined filter predicate for pushing down inset into parquet
56bc750 [Yash Datta] SPARK-7340: Change parquet version to latest release
In some cases, Spark SQL pushes sorting operations into the shuffle layer by specifying a key ordering as part of the shuffle dependency. I think that we should not do this:
- Since we do not delegate aggregation to Spark's shuffle, specifying the keyOrdering as part of the shuffle has no effect on the shuffle map side.
- By performing the shuffle ourselves (by inserting a sort operator after the shuffle instead), we can use the Exchange planner to choose specialized sorting implementations based on the types of rows being sorted.
- We can remove some complexity from SqlSerializer2 by not requiring it to know about sort orderings, since SQL's own sort operators will already perform the necessary defensive copying.
This patch removes Exchange's `canSortWithShuffle` path and the associated code in `SqlSerializer2`. Shuffles that used to go through the `canSortWithShuffle` path would always wind up using Spark's `ExternalSorter` (inside of `HashShuffleReader`); to avoid a performance regression as a result of handling these shuffles ourselves, I've changed the SQLConf defaults so that external sorting is enabled by default.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6772 from JoshRosen/SPARK-8317 and squashes the following commits:
ebf9c0f [Josh Rosen] Do not push sort into shuffle in Exchange operator
bf3b4c8 [Josh Rosen] Enable external sort by default
When df.cache() method called, the `withCachedData` of `QueryExecution` has been created, which mean it will not look up the cached tables when action method called afterward.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#5714 from chenghao-intel/SPARK-7158 and squashes the following commits:
58ea8aa [Cheng Hao] style issue
2bf740f [Cheng Hao] create new QueryExecution instance for CacheManager
a5647d9 [Cheng Hao] hide the queryExecution of DataFrame
fbfd3c5 [Cheng Hao] make the DataFrame.queryExecution mutable for cache/persist/unpersist
Unit test is still in Scala.
Author: Reynold Xin <rxin@databricks.com>
Closes#6738 from rxin/utf8string-java and squashes the following commits:
562dc6e [Reynold Xin] Flag...
98e600b [Reynold Xin] Another try with encoding setting ..
cfa6bdf [Reynold Xin] Merge branch 'master' into utf8string-java
a3b124d [Reynold Xin] Try different UTF-8 encoded characters.
1ff7c82 [Reynold Xin] Enable UTF-8 encoding.
82d58cc [Reynold Xin] Reset run-tests.
2cb3c69 [Reynold Xin] Use utf-8 encoding in set bytes.
53f8ef4 [Reynold Xin] Hack Jenkins to run one test.
9a48e8d [Reynold Xin] Fixed runtime compilation error.
911c450 [Reynold Xin] Moved unit test also to Java.
4eff7bd [Reynold Xin] Improved unit test coverage.
8e89a3c [Reynold Xin] Fixed tests.
77c64bd [Reynold Xin] Fixed string type codegen.
ffedb62 [Reynold Xin] Code review feedback.
0967ce6 [Reynold Xin] Fixed import ordering.
45a123d [Reynold Xin] [SPARK-8286] Rewrite UTF8String in Java and move it into unsafe package.
Spark SQL does not support timezone, and Pyrolite does not support timezone well. This patch will convert datetime into POSIX timestamp (without confusing of timezone), which is used by SQL. If the datetime object does not have timezone, it's treated as local time.
The timezone in RDD will be lost after one round trip, all the datetime from SQL will be local time.
Because of Pyrolite, datetime from SQL only has precision as 1 millisecond.
This PR also drop the timezone in date, convert it to number of days since epoch (used in SQL).
Author: Davies Liu <davies@databricks.com>
Closes#6250 from davies/tzone and squashes the following commits:
44d8497 [Davies Liu] add timezone support for DateType
99d9d9c [Davies Liu] use int for timestamp
10aa7ca [Davies Liu] Merge branch 'master' of github.com:apache/spark into tzone
6a29aa4 [Davies Liu] support datetime with timezone
Author: Daoyuan Wang <daoyuan.wang@intel.com>
This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@databricks.com>
Closes#6718 from adrian-wang/udflog2 and squashes the following commits:
3909f48 [Daoyuan Wang] math function: log2
Author: Cheng Hao <hao.cheng@intel.com>
Closes#6724 from chenghao-intel/length and squashes the following commits:
aaa3c31 [Cheng Hao] revert the additional change
97148a9 [Cheng Hao] remove the codegen testing temporally
ae08003 [Cheng Hao] update the comments
1eb1fd1 [Cheng Hao] simplify the code as commented
3e92d32 [Cheng Hao] use the selectExpr in unit test intead of SQLQuery
3c729aa [Cheng Hao] fix bug for constant null value in codegen
3641f06 [Cheng Hao] keep the length() method for registered function
8e30171 [Cheng Hao] update the code as comment
db604ae [Cheng Hao] Add code gen support
548d2ef [Cheng Hao] register the length()
09a0738 [Cheng Hao] add length support
Currently we only support `Seq[Expression]`, we should handle cases like `Seq[Seq[Expression]]` so that we can remove the unnecessary `GroupExpression`.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6706 from cloud-fan/clean and squashes the following commits:
60a1193 [Wenchen Fan] support nested expression sequence and remove GroupExpression
case cs CombineSum(expr) =>
val calcType = expr.dataType
expr.dataType match {
case DecimalType.Fixed(_, _) =>
DecimalType.Unlimited
case _ =>
expr.dataType
}
calcType is always expr.dataType. credits are all belong to IntelliJ
Author: navis.ryu <navis@apache.org>
Closes#6736 from navis/SPARK-8285 and squashes the following commits:
20382c1 [navis.ryu] [SPARK-8285] [SQL] CombineSum should be calculated as unlimited decimal first
This PR change to use Long as internal type for TimestampType for efficiency, which means it will the precision below 100ns.
Author: Davies Liu <davies@databricks.com>
Closes#6733 from davies/timestamp and squashes the following commits:
d9565fa [Davies Liu] remove print
65cf2f1 [Davies Liu] fix Timestamp in SparkR
86fecfb [Davies Liu] disable two timestamp tests
8f77ee0 [Davies Liu] fix scala style
246ee74 [Davies Liu] address comments
309d2e1 [Davies Liu] use Long for TimestampType in SQL
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#6716 from adrian-wang/epi and squashes the following commits:
e2e8dbd [Daoyuan Wang] move tests
11b351c [Daoyuan Wang] add tests and remove pu
db331c9 [Daoyuan Wang] py style
599ddd8 [Daoyuan Wang] add py
e6783ef [Daoyuan Wang] register function
82d426e [Daoyuan Wang] add function entry
dbf3ab5 [Daoyuan Wang] add PI and E
This is a followup to #6712.
Author: Reynold Xin <rxin@databricks.com>
Closes#6739 from rxin/6712-followup and squashes the following commits:
fd9acfb [Reynold Xin] [SPARK-7886] Added unit test for HAVING aggregate pushdown.
This builds on #6710 and also uses FunctionRegistry for function lookup in HiveContext.
Author: Reynold Xin <rxin@databricks.com>
Closes#6712 from rxin/udf-registry-hive and squashes the following commits:
f4c2df0 [Reynold Xin] Fixed style violation.
0bd4127 [Reynold Xin] Fixed Python UDFs.
f9a0378 [Reynold Xin] Disable one more test.
5609494 [Reynold Xin] Disable some failing tests.
4efea20 [Reynold Xin] Don't check children resolved for UDF resolution.
2ebe549 [Reynold Xin] Removed more hardcoded functions.
aadce78 [Reynold Xin] [SPARK-7886] Use FunctionRegistry for built-in expressions in HiveContext.
This patch switches to using FunctionRegistry for built-in expressions. It is based on #6463, but with some work to simplify it along with unit tests.
TODOs for future pull requests:
- Use static registration so we don't need to register all functions every time we start a new SQLContext
- Switch to using this in HiveContext
Author: Reynold Xin <rxin@databricks.com>
Author: Santiago M. Mola <santi@mola.io>
Closes#6710 from rxin/udf-registry and squashes the following commits:
6930822 [Reynold Xin] Fixed Python test.
b802c9a [Reynold Xin] Made UDF case insensitive.
e60d815 [Reynold Xin] Made UDF case insensitive.
852f9c0 [Reynold Xin] Fixed style violation.
e76a3c1 [Reynold Xin] Fixed parser.
52ddaba [Reynold Xin] Fixed compilation.
ee7854f [Reynold Xin] Improved error reporting.
ff906f2 [Reynold Xin] More robust constructor calling.
77b46f1 [Reynold Xin] Simplified the code.
2a2a149 [Reynold Xin] Merge pull request #6463 from smola/SPARK-7886
8616924 [Santiago M. Mola] [SPARK-7886] Add built-in expressions to FunctionRegistry.
Use DoubleType instead to be more stable and robust.
Author: Reynold Xin <rxin@databricks.com>
Closes#6692 from rxin/SPARK-8148 and squashes the following commits:
6742ecc [Reynold Xin] [SPARK-8148] Do not use FloatType in partition column inference.
For Hadoop 1.x, `TaskAttemptContext` constructor clones the `Configuration` argument, thus configurations done in `HadoopFsRelation.prepareForWriteJob()` are not populated to *driver* side `TaskAttemptContext` (executor side configurations are properly populated). Currently this should only affect Parquet output committer class configuration.
Author: Cheng Lian <lian@databricks.com>
Closes#6669 from liancheng/spark-8121 and squashes the following commits:
73819e8 [Cheng Lian] Minor logging fix
fce089c [Cheng Lian] Adds more logging
b6f78a6 [Cheng Lian] Fixes compilation error introduced while rebasing
963a1aa [Cheng Lian] Addresses @yhuai's comment
c3a0b1a [Cheng Lian] Fixes InsertIntoHadoopFsRelation job initialization
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#6434 from adrian-wang/joinerr and squashes the following commits:
ee1b64f [Daoyuan Wang] break line
f7c53e9 [Daoyuan Wang] to IllegalArgumentException
f8dea2d [Daoyuan Wang] sys.err to IllegalStateException
be82259 [Daoyuan Wang] change new exception to sys.err
JIRA: https://issues.apache.org/jira/browse/SPARK-7939
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6503 from viirya/disable_partition_type_inference and squashes the following commits:
3e90470 [Liang-Chi Hsieh] Default to enable type inference and update docs.
455edb1 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into disable_partition_type_inference
9a57933 [Liang-Chi Hsieh] Add conf to enable/disable partition column type inference.
Also moved a few files in expressions package around to match test suites.
Author: Reynold Xin <rxin@databricks.com>
Closes#6693 from rxin/expr-refactoring and squashes the following commits:
857599f [Reynold Xin] Fixed style violation.
c0eb74b [Reynold Xin] Fixed compilation.
b3a40f8 [Reynold Xin] Refactored expression test suites.
This PR move codegen implementation of expressions into Expression class itself, make it easy to manage.
It introduces two APIs in Expression:
```
def gen(ctx: CodeGenContext): GeneratedExpressionCode
def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): Code
```
gen(ctx) will call genSource(ctx, ev) to generate Java source code for the current expression. A expression needs to override genSource().
Here are the types:
```
type Term String
type Code String
/**
* Java source for evaluating an [[Expression]] given a [[Row]] of input.
*/
case class GeneratedExpressionCode(var code: Code,
nullTerm: Term,
primitiveTerm: Term,
objectTerm: Term)
/**
* A context for codegen, which is used to bookkeeping the expressions those are not supported
* by codegen, then they are evaluated directly. The unsupported expression is appended at the
* end of `references`, the position of it is kept in the code, used to access and evaluate it.
*/
class CodeGenContext {
/**
* Holding all the expressions those do not support codegen, will be evaluated directly.
*/
val references: Seq[Expression] = new mutable.ArrayBuffer[Expression]()
}
```
This is basically #6660, but fixed style violation and compilation failure.
Author: Davies Liu <davies@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#6690 from rxin/codegen and squashes the following commits:
e1368c2 [Reynold Xin] Fixed tests.
73db80e [Reynold Xin] Fixed compilation failure.
19d6435 [Reynold Xin] Fixed style violation.
9adaeaf [Davies Liu] address comments
f42c732 [Davies Liu] improve coverage and tests
bad6828 [Davies Liu] address comments
e03edaa [Davies Liu] consts fold
86fac2c [Davies Liu] fix style
02262c9 [Davies Liu] address comments
b5d3617 [Davies Liu] Merge pull request #5 from rxin/codegen
48c454f [Reynold Xin] Some code gen update.
2344bc0 [Davies Liu] fix test
12ff88a [Davies Liu] fix build
c5fb514 [Davies Liu] rename
8c6d82d [Davies Liu] update docs
b145047 [Davies Liu] fix style
e57959d [Davies Liu] add type alias
3ff25f8 [Davies Liu] refactor
593d617 [Davies Liu] pushing codegen into Expression
This is a follow-up patch to #6577 to replace columnEnclosing to quoteIdentifier.
I also did some minor cleanup to the JdbcDialect file.
Author: Reynold Xin <rxin@databricks.com>
Closes#6689 from rxin/jdbc-quote and squashes the following commits:
bad365f [Reynold Xin] Fixed test compilation...
e39e14e [Reynold Xin] Fixed compilation.
db9a8e0 [Reynold Xin] [SPARK-8004][SQL] Quote identifier in JDBC data source.
Author: Cheng Lian <lian@databricks.com>
Closes#6670 from liancheng/spark-8118 and squashes the following commits:
b6e85a6 [Cheng Lian] Suppresses unnecesary ParquetRecordReader log message (PARQUET-220)
385603c [Cheng Lian] Mutes noisy Parquet log output reappeared after upgrading Parquet to 1.7.0
JIRA: https://issues.apache.org/jira/browse/SPARK-8141
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6687 from viirya/reuse_partition_column_types and squashes the following commits:
dab0688 [Liang-Chi Hsieh] Reuse partitionColumnTypes.
JIRA: https://issues.apache.org/jira/browse/SPARK-8004
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6577 from viirya/enclose_jdbc_columns and squashes the following commits:
614606a [Liang-Chi Hsieh] For comment.
bc50182 [Liang-Chi Hsieh] Enclose column names by JDBC Dialect.
As described in SPARK-8079, when writing a DataFrame to a `HadoopFsRelation`, if `HadoopFsRelation.prepareForWriteJob` throws exception, an unexpected NPE will be thrown during job abortion. (This issue doesn't bring much damage since the job is failing anyway.)
This PR makes the job/task abortion logic in `InsertIntoHadoopFsRelation` more robust to avoid such confusing exceptions.
Author: Cheng Lian <lian@databricks.com>
Closes#6612 from liancheng/spark-8079 and squashes the following commits:
87cd81e [Cheng Lian] Addresses @rxin's comment
1864c75 [Cheng Lian] Addresses review comments
9e6dbb3 [Cheng Lian] Makes InsertIntoHadoopFsRelation job/task abortion more robust
Author: Reynold Xin <rxin@databricks.com>
Closes#6677 from rxin/test-wildcard and squashes the following commits:
8a17b33 [Reynold Xin] Fixed line length.
6663813 [Reynold Xin] [SPARK-8114][SQL] Remove some wildcard import on TestSQLContext._ round 3.
Support runInBackground in SparkExecuteStatementOperation, and add cancellation
Author: Dong Wang <dong@databricks.com>
Closes#6207 from dongwang218/SPARK-6964-jdbc-cancel and squashes the following commits:
687c113 [Dong Wang] fix 100 characters
7bfa2a7 [Dong Wang] fix merge
380480f [Dong Wang] fix for liancheng's comments
eb3e385 [Dong Wang] small nit
341885b [Dong Wang] small fix
3d8ebf8 [Dong Wang] add spark.sql.hive.thriftServer.async flag
04142c3 [Dong Wang] set SQLSession for async execution
184ec35 [Dong Wang] keep hive conf
819ae03 [Dong Wang] [SPARK-6964][SQL][WIP] Support Cancellation in the Thrift Server
Fixed the following packages:
sql.columnar
sql.jdbc
sql.json
sql.parquet
Author: Reynold Xin <rxin@databricks.com>
Closes#6667 from rxin/testsqlcontext_wildcard and squashes the following commits:
134a776 [Reynold Xin] Fixed compilation break.
6da7b69 [Reynold Xin] [SPARK-8114][SQL] Remove some wildcard import on TestSQLContext._ cont'd.
cc davies sun-rui
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#6620 from shivaram/sparkr-read-schema and squashes the following commits:
16a6726 [Shivaram Venkataraman] Fix loadDF to pass schema Also add a unit test
a229877 [Shivaram Venkataraman] Use wrapper function to DataFrameReader
ee70ba8 [Shivaram Venkataraman] Support user-specified schema in read.df
I kept some of the sql import there to avoid changing too many lines.
Author: Reynold Xin <rxin@databricks.com>
Closes#6661 from rxin/remove-wildcard-import-sqlcontext and squashes the following commits:
c265347 [Reynold Xin] Fixed ListTablesSuite failure.
de9d491 [Reynold Xin] Fixed tests.
73b5365 [Reynold Xin] Mima.
8f6b642 [Reynold Xin] Fixed style violation.
443f6e8 [Reynold Xin] [SPARK-8113][SQL] Remove some wildcard import on TestSQLContext._
This patch replaces Distinct with Aggregate in the optimizer, so Distinct will become
more efficient over time as we optimize Aggregate (via Tungsten).
Author: Reynold Xin <rxin@databricks.com>
Closes#6637 from rxin/replace-distinct and squashes the following commits:
b3cc50e [Reynold Xin] Mima excludes.
93d6117 [Reynold Xin] Code review feedback.
87e4741 [Reynold Xin] [SPARK-7440][SQL] Remove physical Distinct operator in favor of Aggregate.
Resolves [SPARK-7743](https://issues.apache.org/jira/browse/SPARK-7743).
Trivial changes of versions, package names, as well as a small issue in `ParquetTableOperations.scala`
```diff
- val readContext = getReadSupport(configuration).init(
+ val readContext = ParquetInputFormat.getReadSupportInstance(configuration).init(
```
Since ParquetInputFormat.getReadSupport was made package private in the latest release.
Thanks
-- Thomas Omans
Author: Thomas Omans <tomans@cj.com>
Closes#6597 from eggsby/SPARK-7743 and squashes the following commits:
2df0d1b [Thomas Omans] [SPARK-7743] [SQL] Upgrading parquet version to 1.7.0
Added a `DataFrame.drop` function that accepts a `Column` reference rather than a `String`, and added associated unit tests. Basically iterates through the `DataFrame` to find a column with an expression that is equivalent to that of the `Column` argument supplied to the function.
Author: Mike Dusenberry <dusenberrymw@gmail.com>
Closes#6585 from dusenberrymw/SPARK-7969_Drop_method_on_Dataframes_should_handle_Column and squashes the following commits:
514727a [Mike Dusenberry] Updating the @since tag of the drop(Column) function doc to reflect version 1.4.1 instead of 1.4.0.
2f1bb4e [Mike Dusenberry] Adding an additional assert statement to the 'drop column after join' unit test in order to make sure the correct column was indeed left over.
6bf7c0e [Mike Dusenberry] Minor code formatting change.
e583888 [Mike Dusenberry] Adding more Python doctests for the df.drop with column reference function to test joined datasets that have columns with the same name.
5f74401 [Mike Dusenberry] Updating DataFrame.drop with column reference function to use logicalPlan.output to prevent ambiguities resulting from columns with the same name. Also added associated unit tests for joined datasets with duplicate column names.
4b8bbe8 [Mike Dusenberry] Adding Python support for Dataframe.drop with a Column reference.
986129c [Mike Dusenberry] Added a DataFrame.drop function that accepts a Column reference rather than a String, and added associated unit tests. Basically iterates through the DataFrame to find a column with an expression that is equivalent to one supplied to the function.
In order to reduce the overhead of codegen, this PR switch to use Janino to compile SQL expressions into bytecode.
After this, the time used to compile a SQL expression is decreased from 100ms to 5ms, which is necessary to turn on codegen for general workload, also tests.
cc rxin
Author: Davies Liu <davies@databricks.com>
Closes#6479 from davies/janino and squashes the following commits:
cc689f5 [Davies Liu] remove globalLock
262d848 [Davies Liu] Merge branch 'master' of github.com:apache/spark into janino
eec3a33 [Davies Liu] address comments from Josh
f37c8c3 [Davies Liu] fix DecimalType and cast to String
202298b [Davies Liu] Merge branch 'master' of github.com:apache/spark into janino
a21e968 [Davies Liu] fix style
0ed3dc6 [Davies Liu] Merge branch 'master' of github.com:apache/spark into janino
551a851 [Davies Liu] fix tests
c3bdffa [Davies Liu] remove print
6089ce5 [Davies Liu] change logging level
7e46ac3 [Davies Liu] fix style
d8f0f6c [Davies Liu] Merge branch 'master' of github.com:apache/spark into janino
da4926a [Davies Liu] fix tests
03660f3 [Davies Liu] WIP: use Janino to compile Java source
f2629cd [Davies Liu] Merge branch 'master' of github.com:apache/spark into janino
f7d66cf [Davies Liu] use template based string for codegen
Author: Reynold Xin <rxin@databricks.com>
Closes#6608 from rxin/parquet-analysis and squashes the following commits:
b5dc8e2 [Reynold Xin] Code review feedback.
5617cf6 [Reynold Xin] [SPARK-8074] Parquet should throw AnalysisException during setup for data type/name related failures.
1. range() overloaded in SQLContext.scala
2. range() modified in python sql context.py
3. Tests added accordingly in DataFrameSuite.scala and python sql tests.py
Author: animesh <animesh@apache.spark>
Closes#6609 from animeshbaranawal/SPARK-7980 and squashes the following commits:
935899c [animesh] SPARK-7980:python+scala changes
Author: Patrick Wendell <patrick@databricks.com>
Closes#6328 from pwendell/spark-1.5-update and squashes the following commits:
2f42d02 [Patrick Wendell] A few more excludes
4bebcf0 [Patrick Wendell] Update to RC4
61aaf46 [Patrick Wendell] Using new release candidate
55f1610 [Patrick Wendell] Another exclude
04b4f04 [Patrick Wendell] More issues with transient 1.4 changes
36f549b [Patrick Wendell] [SPARK-7801] [BUILD] Updating versions to SPARK 1.5.0
It seems hard to find a common pattern of checking types in `Expression`. Sometimes we know what input types we need(like `And`, we know we need two booleans), sometimes we just have some rules(like `Add`, we need 2 numeric types which are equal). So I defined a general interface `checkInputDataTypes` in `Expression` which returns a `TypeCheckResult`. `TypeCheckResult` can tell whether this expression passes the type checking or what the type mismatch is.
This PR mainly works on apply input types checking for arithmetic and predicate expressions.
TODO: apply type checking interface to more expressions.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6405 from cloud-fan/6444 and squashes the following commits:
b5ff31b [Wenchen Fan] address comments
b917275 [Wenchen Fan] rebase
39929d9 [Wenchen Fan] add todo
0808fd2 [Wenchen Fan] make constrcutor of TypeCheckResult private
3bee157 [Wenchen Fan] and decimal type coercion rule for binary comparison
8883025 [Wenchen Fan] apply type check interface to CaseWhen
cffb67c [Wenchen Fan] to have resolved call the data type check function
6eaadff [Wenchen Fan] add equal type constraint to EqualTo
3affbd8 [Wenchen Fan] more fixes
654d46a [Wenchen Fan] improve tests
e0a3628 [Wenchen Fan] improve error message
1524ff6 [Wenchen Fan] fix style
69ca3fe [Wenchen Fan] add error message and tests
c71d02c [Wenchen Fan] fix hive tests
6491721 [Wenchen Fan] use value class TypeCheckResult
7ae76b9 [Wenchen Fan] address comments
cb77e4f [Wenchen Fan] Improve error reporting for expression data type mismatch
This patch significantly refactors CatalystTypeConverters to both clean up the code and enable these conversions to work with future Project Tungsten features.
At a high level, I've reorganized the code so that all functions dealing with the same type are grouped together into type-specific subclasses of `CatalystTypeConveter`. In addition, I've added new methods that allow the Catalyst Row -> Scala Row conversions to access the Catalyst row's fields through type-specific `getTYPE()` methods rather than the generic `get()` / `Row.apply` methods. This refactoring is a blocker to being able to unit test new operators that I'm developing as part of Project Tungsten, since those operators may output `UnsafeRow` instances which don't support the generic `get()`.
The stricter type usage of types here has uncovered some bugs in other parts of Spark SQL:
- #6217: DescribeCommand is assigned wrong output attributes in SparkStrategies
- #6218: DataFrame.describe() should cast all aggregates to String
- #6400: Use output schema, not relation schema, for data source input conversion
Spark SQL current has undefined behavior for what happens when you try to create a DataFrame from user-specified rows whose values don't match the declared schema. According to the `createDataFrame()` Scaladoc:
> It is important to make sure that the structure of every [[Row]] of the provided RDD matches the provided schema. Otherwise, there will be runtime exception.
Given this, it sounds like it's technically not a break of our API contract to fail-fast when the data types don't match. However, there appear to be many cases where we don't fail even though the types don't match. For example, `JavaHashingTFSuite.hasingTF` passes a column of integers values for a "label" column which is supposed to contain floats. This column isn't actually read or modified as part of query processing, so its actual concrete type doesn't seem to matter. In other cases, there could be situations where we have generic numeric aggregates that tolerate being called with different numeric types than the schema specified, but this can be okay due to numeric conversions.
In the long run, we will probably want to come up with precise semantics for implicit type conversions / widening when converting Java / Scala rows to Catalyst rows. Until then, though, I think that failing fast with a ClassCastException is a reasonable behavior; this is the approach taken in this patch. Note that certain optimizations in the inbound conversion functions for primitive types mean that we'll probably preserve the old undefined behavior in a majority of cases.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6222 from JoshRosen/catalyst-converters-refactoring and squashes the following commits:
740341b [Josh Rosen] Optimize method dispatch for primitive type conversions
befc613 [Josh Rosen] Add tests to document Option-handling behavior.
5989593 [Josh Rosen] Use new SparkFunSuite base in CatalystTypeConvertersSuite
6edf7f8 [Josh Rosen] Re-add convertToScala(), since a Hive test still needs it
3f7b2d8 [Josh Rosen] Initialize converters lazily so that the attributes are resolved first
6ad0ebb [Josh Rosen] Fix JavaHashingTFSuite ClassCastException
677ff27 [Josh Rosen] Fix null handling bug; add tests.
8033d4c [Josh Rosen] Fix serialization error in UserDefinedGenerator.
85bba9d [Josh Rosen] Fix wrong input data in InMemoryColumnarQuerySuite
9c0e4e1 [Josh Rosen] Remove last use of convertToScala().
ae3278d [Josh Rosen] Throw ClassCastException errors during inbound conversions.
7ca7fcb [Josh Rosen] Comments and cleanup
1e87a45 [Josh Rosen] WIP refactoring of CatalystTypeConverters
The current code references the schema of the DataFrame to be written before checking save mode. This triggers expensive metadata discovery prematurely. For save mode other than `Append`, this metadata discovery is useless since we either ignore the result (for `Ignore` and `ErrorIfExists`) or delete existing files (for `Overwrite`) later.
This PR fixes this issue by deferring metadata discovery after save mode checking.
Author: Cheng Lian <lian@databricks.com>
Closes#6583 from liancheng/spark-8014 and squashes the following commits:
1aafabd [Cheng Lian] Updates comments
088abaa [Cheng Lian] Avoids schema merging and partition discovery when data schema and partition schema are defined
8fbd93f [Cheng Lian] Fixes SPARK-8014
Author: Cheng Lian <lian@databricks.com>
Closes#6581 from liancheng/spark-8037 and squashes the following commits:
d08e97b [Cheng Lian] Ignores files whose name starts with dot in HadoopFsRelation
This closes#6570.
Author: Yin Huai <yhuai@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#6573 from rxin/deterministic and squashes the following commits:
356cd22 [Reynold Xin] Added unit test for the optimizer.
da3fde1 [Reynold Xin] Merge pull request #6570 from yhuai/SPARK-8023
da56200 [Yin Huai] Comments.
e38f264 [Yin Huai] Comment.
f9d6a73 [Yin Huai] Add a deterministic method to Expression.
https://issues.apache.org/jira/browse/SPARK-8020
Author: Yin Huai <yhuai@databricks.com>
Closes#6571 from yhuai/SPARK-8020-1 and squashes the following commits:
0398f5b [Yin Huai] First populate the SQLConf and then construct executionHive and metadataHive.
cc yhuai
Author: Davies Liu <davies@databricks.com>
Closes#6558 from davies/decimalType and squashes the following commits:
c877ca8 [Davies Liu] Update ParquetConverter.scala
48cc57c [Davies Liu] Update ParquetConverter.scala
b43845c [Davies Liu] add test
3b4a94f [Davies Liu] DecimalType is not read back when non-native type exists
https://issues.apache.org/jira/browse/SPARK-8020
Author: Yin Huai <yhuai@databricks.com>
Closes#6563 from yhuai/SPARK-8020 and squashes the following commits:
4e5addc [Yin Huai] style
bf766c6 [Yin Huai] Failed test.
0398f5b [Yin Huai] First populate the SQLConf and then construct executionHive and metadataHive.
Author: Reynold Xin <rxin@databricks.com>
Closes#6569 from rxin/freqItemsWarning and squashes the following commits:
7eec145 [Reynold Xin] [minor doc] Add exploratory data analysis warning for DataFrame.stat.freqItem API.
Author: Reynold Xin <rxin@databricks.com>
Closes#6565 from rxin/alias and squashes the following commits:
286d880 [Reynold Xin] [SPARK-8026][SQL] Add Column.alias to Scala/Java DataFrame API
Author: Reynold Xin <rxin@databricks.com>
Closes#6566 from rxin/crosstab and squashes the following commits:
e0ace1c [Reynold Xin] [SPARK-7982][SQL] DataFrame.stat.crosstab should use 0 instead of null for pairs that don't appear
The origin code has several problems:
* `true <=> 1` will return false as we didn't set a rule to handle it.
* `true = a` where `a` is not `Literal` and its value is 1, will return false as we only handle literal values.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6505 from cloud-fan/tmp1 and squashes the following commits:
77f0f39 [Wenchen Fan] minor fix
b6401ba [Wenchen Fan] add type coercion for CaseKeyWhen and address comments
ebc8c61 [Wenchen Fan] use SQLTestUtils and If
625973c [Wenchen Fan] improve
9ba2130 [Wenchen Fan] address comments
fc0d741 [Wenchen Fan] fix style
2846a04 [Wenchen Fan] fix 7952
Author: Reynold Xin <rxin@databricks.com>
Closes#6541 from rxin/trailing-whitespace-on and squashes the following commits:
f72ebe4 [Reynold Xin] [SPARK-3850] Turn style checker on for trailing whitespaces.
Author: Reynold Xin <rxin@databricks.com>
Closes#6535 from rxin/whitespace-sql and squashes the following commits:
de50316 [Reynold Xin] [SPARK-3850] Trim trailing spaces for SQL.
Author: Reynold Xin <rxin@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@databricks.com>
Closes#6527 from rxin/covariant-equals and squashes the following commits:
e7d7784 [Reynold Xin] [SPARK-7975] Enforce CovariantEqualsChecker
Author: Cheng Lian <lian@databricks.com>
Closes#6529 from liancheng/schemardd-deprecation-fix and squashes the following commits:
49765c2 [Cheng Lian] Adds @deprecated Scaladoc entry for SchemaRDD
Scala deprecated annotation actually doesn't show up in JavaDoc.
Author: Reynold Xin <rxin@databricks.com>
Closes#6523 from rxin/df-deprecated-javadoc and squashes the following commits:
26da2b2 [Reynold Xin] [SPARK-7971] Add JavaDoc style deprecation for deprecated DataFrame methods.
I went through all the JavaDocs and tightened up visibility.
Author: Reynold Xin <rxin@databricks.com>
Closes#6526 from rxin/sql-1.4-visibility-for-docs and squashes the following commits:
bc37d1e [Reynold Xin] Tighten up visibility for JavaDoc.
Right now `unit-tests.log` are not of much value because we can't tell where the test boundaries are easily. This patch adds log statements before and after each test to outline the test boundaries, e.g.:
```
===== TEST OUTPUT FOR o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' =====
15/05/27 12:36:39.596 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO SparkContext: Starting job: count at KryoSerializerSuite.scala:230
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Got job 3 (count at KryoSerializerSuite.scala:230) with 4 output partitions (allowLocal=false)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Final stage: ResultStage 3(count at KryoSerializerSuite.scala:230)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Parents of final stage: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Missing parents: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Submitting ResultStage 3 (ParallelCollectionRDD[5] at parallelize at KryoSerializerSuite.scala:230), which has no missing parents
...
15/05/27 12:36:39.624 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO DAGScheduler: Job 3 finished: count at KryoSerializerSuite.scala:230, took 0.028563 s
15/05/27 12:36:39.625 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO KryoSerializerSuite:
***** FINISHED o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' *****
...
```
Author: Andrew Or <andrew@databricks.com>
Closes#6441 from andrewor14/demarcate-tests and squashes the following commits:
879b060 [Andrew Or] Fix compile after rebase
d622af7 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
017c8ba [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
7790b6c [Andrew Or] Fix tests after logical merge conflict
c7460c0 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
c43ffc4 [Andrew Or] Fix tests?
8882581 [Andrew Or] Fix tests
ee22cda [Andrew Or] Fix log message
fa9450e [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
12d1e1b [Andrew Or] Various whitespace changes (minor)
69cbb24 [Andrew Or] Make all test suites extend SparkFunSuite instead of FunSuite
bbce12e [Andrew Or] Fix manual things that cannot be covered through automation
da0b12f [Andrew Or] Add core tests as dependencies in all modules
f7d29ce [Andrew Or] Introduce base abstract class for all test suites
So we can enable a whitespace enforcement rule in the style checker to save code review time.
Author: Reynold Xin <rxin@databricks.com>
Closes#6477 from rxin/whitespace-sql-core and squashes the following commits:
ce6e369 [Reynold Xin] Fixed tests.
6095fed [Reynold Xin] [SPARK-7927] whitespace fixes for SQL core.
JIRA: https://issues.apache.org/jira/browse/SPARK-7897
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6438 from viirya/jdbc_unsigned_bigint and squashes the following commits:
ccb3c3f [Liang-Chi Hsieh] Use DecimalType to represent unsigned bigint.
As stated in SPARK-7684, currently `TestHive.reset` has some execution order specific bug, which makes running specific test suites locally pretty frustrating. This PR refactors `MetastoreDataSourcesSuite` (which relies on `TestHive.reset` heavily) using various `withXxx` utility methods in `SQLTestUtils` to ask each test case to cleanup their own mess so that we can avoid calling `TestHive.reset`.
Author: Cheng Lian <lian@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Closes#6353 from liancheng/workaround-spark-7684 and squashes the following commits:
26939aa [Yin Huai] Move the initialization of jsonFilePath to beforeAll.
a423d48 [Cheng Lian] Fixes Scala style issue
dfe45d0 [Cheng Lian] Refactors MetastoreDataSourcesSuite to workaround SPARK-7684
92a116d [Cheng Lian] Fixes minor styling issues
This should also close#6243.
Author: Reynold Xin <rxin@databricks.com>
Closes#6431 from rxin/JavaTypeInference-guava and squashes the following commits:
e58df3c [Reynold Xin] Removed Gauva dependency from JavaTypeInference's type signature.
Please refer to [SPARK-7847] [1] for details.
[1]: https://issues.apache.org/jira/browse/SPARK-7847
Author: Cheng Lian <lian@databricks.com>
Closes#6389 from liancheng/spark-7847 and squashes the following commits:
935c652 [Cheng Lian] Adds test case for writing various data types as dynamic partition value
f4fc398 [Cheng Lian] Converts partition columns to Scala type when writing dynamic partitions
d0aeca0 [Cheng Lian] Fixes dynamic partition directory escaping
This type is not really used. Might as well remove it.
Author: Reynold Xin <rxin@databricks.com>
Closes#6427 from rxin/evalutedType and squashes the following commits:
51a319a [Reynold Xin] [SPARK-7887][SQL] Remove EvaluatedType from SQL Expression.
JIRA: https://issues.apache.org/jira/browse/SPARK-7697
The reported problem case is mysql. But for h2 db, there is no unsigned int. So it is not able to add corresponding test.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6229 from viirya/unsignedint_as_long and squashes the following commits:
dc4b5d8 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into unsignedint_as_long
608695b [Liang-Chi Hsieh] Use LongType for unsigned int in JDBCRDD.
So that potential partial/corrupted data files left by failed tasks/jobs won't affect normal data scan.
Author: Cheng Lian <lian@databricks.com>
Closes#6411 from liancheng/spark-7868 and squashes the following commits:
273ea36 [Cheng Lian] Ignores _temporary directories
In `DataSourceStrategy.createPhysicalRDD`, we use the relation schema as the target schema for converting incoming rows into Catalyst rows. However, we should be using the output schema instead, since our scan might return a subset of the relation's columns.
This patch incorporates #6414 by liancheng, which fixes an issue in `SimpleTestRelation` that prevented this bug from being caught by our old tests:
> In `SimpleTextRelation`, we specified `needsConversion` to `true`, indicating that values produced by this testing relation should be of Scala types, and need to be converted to Catalyst types when necessary. However, we also used `Cast` to convert strings to expected data types. And `Cast` always produces values of Catalyst types, thus no conversion is done at all. This PR makes `SimpleTextRelation` produce Scala values so that data conversion code paths can be properly tested.
Closes#5986.
Author: Josh Rosen <joshrosen@databricks.com>
Author: Cheng Lian <lian@databricks.com>
Author: Cheng Lian <liancheng@users.noreply.github.com>
Closes#6400 from JoshRosen/SPARK-7858 and squashes the following commits:
e71c866 [Josh Rosen] Re-fix bug so that the tests pass again
56b13e5 [Josh Rosen] Add regression test to hadoopFsRelationSuites
2169a0f [Josh Rosen] Remove use of SpecificMutableRow and BufferedIterator
6cd7366 [Josh Rosen] Fix SPARK-7858 by using output types for conversion.
5a00e66 [Josh Rosen] Add assertions in order to reproduce SPARK-7858
8ba195c [Cheng Lian] Merge 9968fba9979287aaa1f141ba18bfb9d4c116a3b3 into 61664732b2
9968fba [Cheng Lian] Tests the data type conversion code paths
When committing/aborting a write task issued in `InsertIntoHadoopFsRelation`, if an exception is thrown from `OutputWriter.close()`, the committing/aborting process will be interrupted, and leaves messy stuff behind (e.g., the `_temporary` directory created by `FileOutputCommitter`).
This PR makes these two process more robust by catching potential exceptions and falling back to normal task committment/abort.
Author: Cheng Lian <lian@databricks.com>
Closes#6378 from liancheng/spark-7838 and squashes the following commits:
f18253a [Cheng Lian] Makes task committing/aborting in InsertIntoHadoopFsRelation more robust
https://issues.apache.org/jira/browse/SPARK-7805
Because `sql/hive`'s tests depend on the test jar of `sql/core`, we do not need to store `SQLTestUtils` and `ParquetTest` in `src/main`. We should only add stuff that will be needed by `sql/console` or Python tests (for Python, we need it in `src/main`, right? davies).
Author: Yin Huai <yhuai@databricks.com>
Closes#6334 from yhuai/SPARK-7805 and squashes the following commits:
af6d0c9 [Yin Huai] mima
b86746a [Yin Huai] Move SQLTestUtils.scala and ParquetTest.scala to src/test.
This one continues the work of https://github.com/apache/spark/pull/6216.
Author: Yin Huai <yhuai@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#6366 from yhuai/insert and squashes the following commits:
3d717fb [Yin Huai] Use insertInto to handle the casue when table exists and Append is used for saveAsTable.
56d2540 [Yin Huai] Add PreWriteCheck to HiveContext's analyzer.
c636e35 [Yin Huai] Remove unnecessary empty lines.
cf83837 [Yin Huai] Move insertInto to write. Also, remove the partition columns from InsertIntoHadoopFsRelation.
0841a54 [Reynold Xin] Removed experimental tag for deprecated methods.
33ed8ef [Reynold Xin] [SPARK-7654][SQL] Move insertInto into reader/writer interface.
Author: Michael Armbrust <michael@databricks.com>
Closes#6165 from marmbrus/wrongColumn and squashes the following commits:
4fad158 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into wrongColumn
aad7eab [Michael Armbrust] rxins comments
f1e8df1 [Michael Armbrust] [SPARK-6743][SQL] Fix empty projections of cached data
This closes#6104.
Author: Cheng Hao <hao.cheng@intel.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#6343 from rxin/window-df and squashes the following commits:
026d587 [Reynold Xin] Address code review feedback.
dc448fe [Reynold Xin] Fixed Hive tests.
9794d9d [Reynold Xin] Moved Java test package.
9331605 [Reynold Xin] Refactored API.
3313e2a [Reynold Xin] Merge pull request #6104 from chenghao-intel/df_window
d625a64 [Cheng Hao] Update the dataframe window API as suggsted
c141fb1 [Cheng Hao] hide all of properties of the WindowFunctionDefinition
3b1865f [Cheng Hao] scaladoc typos
f3fd2d0 [Cheng Hao] polish the unit test
6847825 [Cheng Hao] Add additional analystcs functions
57e3bc0 [Cheng Hao] typos
24a08ec [Cheng Hao] scaladoc
28222ed [Cheng Hao] fix bug of range/row Frame
1d91865 [Cheng Hao] style issue
53f89f2 [Cheng Hao] remove the over from the functions.scala
964c013 [Cheng Hao] add more unit tests and window functions
64e18a7 [Cheng Hao] Add Window Function support for DataFrame
https://issues.apache.org/jira/browse/SPARK-7737
cc liancheng
Author: Yin Huai <yhuai@databricks.com>
Closes#6329 from yhuai/spark-7737 and squashes the following commits:
7e0dfc7 [Yin Huai] Use leaf dirs having data files to discover partitions.
According to yhuai we spent 6-7 seconds cleaning closures in a partitioning job that takes 12 seconds. Since we provide these closures in Spark we know for sure they are serializable, so we can bypass the cleaning.
Author: Andrew Or <andrew@databricks.com>
Closes#6256 from andrewor14/sql-partition-speed-up and squashes the following commits:
a82b451 [Andrew Or] Fix style
10f7e3e [Andrew Or] Avoid getting call sites and cleaning closures
17e2943 [Andrew Or] Merge branch 'master' of github.com:apache/spark into sql-partition-speed-up
523f042 [Andrew Or] Skip unnecessary Utils.getCallSites too
f7fe143 [Andrew Or] Avoid unnecessary closure cleaning
Having a SQLContext singleton would make it easier for applications to use a lazily instantiated single shared instance of SQLContext when needed. It would avoid problems like
1. In REPL/notebook environment, rerunning the line {{val sqlContext = new SQLContext}} multiple times created different contexts while overriding the reference to previous context, leading to issues like registered temp tables going missing.
2. In Streaming, creating SQLContext directly leads to serialization/deserialization issues when attempting to recover from DStream checkpoints. See [SPARK-6770]. Also to get around this problem I had to suggest creating a singleton instance - https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
This can be solved by {{SQLContext.getOrCreate}} which get or creates a new singleton instance of SQLContext using either a given SparkContext or a given SparkConf.
rxin marmbrus
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#6006 from tdas/SPARK-7478 and squashes the following commits:
25f4da9 [Tathagata Das] Addressed comments.
79fe069 [Tathagata Das] Added comments.
c66ca76 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-7478
48adb14 [Tathagata Das] Removed HiveContext.getOrCreate
bf8cf50 [Tathagata Das] Fix more bug
dec5594 [Tathagata Das] Fixed bug
b4e9721 [Tathagata Das] Remove unnecessary import
4ef513b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-7478
d3ea8e4 [Tathagata Das] Added HiveContext
83bc950 [Tathagata Das] Updated tests
f82ae81 [Tathagata Das] Fixed test
bc72868 [Tathagata Das] Added SQLContext.getOrCreate
Author: Yin Huai <yhuai@databricks.com>
Author: Cheng Lian <lian@databricks.com>
Closes#6285 from liancheng/spark-7763 and squashes the following commits:
bb2829d [Yin Huai] Fix hashCode.
d677f7d [Cheng Lian] Fixes Scala style issue
44b283f [Cheng Lian] Adds test case for SPARK-7616
6733276 [Yin Huai] Fix a bug that potentially causes https://issues.apache.org/jira/browse/SPARK-7616.
6cabf3c [Yin Huai] Update unit test.
7e02910 [Yin Huai] Use metastore partition columns and do not hijack maybePartitionSpec.
e9a03ec [Cheng Lian] Persists partition columns into metastore
When no partition columns can be found, we should have an empty `PartitionSpec`, rather than a `PartitionSpec` with empty partition columns.
This PR together with #6285 should fix SPARK-7749.
Author: Cheng Lian <lian@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Closes#6287 from liancheng/spark-7749 and squashes the following commits:
a799ff3 [Cheng Lian] Adds test cases for SPARK-7749
c4949be [Cheng Lian] Minor refactoring, and tolerant _TEMPORARY directory name
5aa87ea [Yin Huai] Make parsePartitions more robust.
fc56656 [Cheng Lian] Returns empty PartitionSpec if no partition columns can be inferred
19ae41e [Cheng Lian] Don't list base directory as leaf directory
The key of Map in JsonRDD should be converted into UTF8String (also failed records), Thanks to yhuai viirya
Closes#6084
Author: Davies Liu <davies@databricks.com>
Closes#6299 from davies/string_in_json and squashes the following commits:
0dbf559 [Davies Liu] improve test, fix corrupt record
6836a80 [Davies Liu] move unit tests into Scala
b97af11 [Davies Liu] fix MapType in JsonRDD
JIRA: https://issues.apache.org/jira/browse/SPARK-7746
Looks like an easy to add parameter but can show significant performance improvement if the JDBC driver accepts it.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6283 from viirya/jdbc_fetchsize and squashes the following commits:
de47f94 [Liang-Chi Hsieh] Don't keep fetchSize as single parameter.
b7bff2f [Liang-Chi Hsieh] Add FetchSize parameter for JDBC driver.
This is a follow up for #6257, which broke the maven test.
Add cube & rollup for DataFrame
For example:
```scala
testData.rollup($"a" + $"b", $"b").agg(sum($"a" - $"b"))
testData.cube($"a" + $"b", $"b").agg(sum($"a" - $"b"))
```
Author: Cheng Hao <hao.cheng@intel.com>
Closes#6304 from chenghao-intel/rollup and squashes the following commits:
04bb1de [Cheng Hao] move the table register/unregister into beforeAll/afterAll
a6069f1 [Cheng Hao] cancel the implicit keyword
ced4b8f [Cheng Hao] remove the unnecessary code changes
9959dfa [Cheng Hao] update the code as comments
e1d88aa [Cheng Hao] update the code as suggested
03bc3d9 [Cheng Hao] Remove the CubedData & RollupedData
5fd62d0 [Cheng Hao] hiden the CubedData & RollupedData
5ffb196 [Cheng Hao] Add Cube / Rollup for dataframe
https://issues.apache.org/jira/browse/SPARK-7713
I tested the performance with the following code:
```scala
import sqlContext._
import sqlContext.implicits._
(1 to 5000).foreach { i =>
val df = (1 to 1000).map(j => (j, s"str$j")).toDF("a", "b").save(s"/tmp/partitioned/i=$i")
}
sqlContext.sql("""
CREATE TEMPORARY TABLE partitionedParquet
USING org.apache.spark.sql.parquet
OPTIONS (
path '/tmp/partitioned'
)""")
table("partitionedParquet").explain(true)
```
In our master `explain` takes 40s in my laptop. With this PR, `explain` takes 14s.
Author: Yin Huai <yhuai@databricks.com>
Closes#6252 from yhuai/broadcastHadoopConf and squashes the following commits:
6fa73df [Yin Huai] Address comments of Josh and Andrew.
807fbf9 [Yin Huai] Make the new buildScan and SqlNewHadoopRDD private sql.
e393555 [Yin Huai] Cheng's comments.
2eb53bb [Yin Huai] Use a shared broadcast Hadoop Configuration for partitioned HadoopFsRelations.
follow up for #5806
Author: scwf <wangfei1@huawei.com>
Closes#6164 from scwf/FunctionRegistry and squashes the following commits:
15e6697 [scwf] use catalogconf in FunctionRegistry
In `DataFrame.describe()`, the `count` aggregate produces an integer, the `avg` and `stdev` aggregates produce doubles, and `min` and `max` aggregates can produce varying types depending on what type of column they're applied to. As a result, we should cast all aggregate results to String so that `describe()`'s output types match its declared output schema.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6218 from JoshRosen/SPARK-7687 and squashes the following commits:
146b615 [Josh Rosen] Fix R test.
2974bd5 [Josh Rosen] Cast to string type instead
f206580 [Josh Rosen] Cast to double to fix SPARK-7687
307ecbf [Josh Rosen] Add failing regression test for SPARK-7687
This PR is based on #6081, thanks adrian-wang.
Closes#6081
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#6230 from davies/range and squashes the following commits:
d3ce5fe [Davies Liu] add tests
789eda5 [Davies Liu] add range() in Python
4590208 [Davies Liu] Merge commit 'refs/pull/6081/head' of github.com:apache/spark into range
cbf5200 [Daoyuan Wang] let's add python support in a separate PR
f45e3b2 [Daoyuan Wang] remove redundant toLong
617da76 [Daoyuan Wang] fix safe marge for corner cases
867c417 [Daoyuan Wang] fix
13dbe84 [Daoyuan Wang] update
bd998ba [Daoyuan Wang] update comments
d3a0c1b [Daoyuan Wang] add range api()
This PR revert #5404, change to pass the version of python in driver into JVM, check it in worker before deserializing closure, then it can works with different major version of Python.
Author: Davies Liu <davies@databricks.com>
Closes#6203 from davies/py_version and squashes the following commits:
b8fb76e [Davies Liu] fix test
6ce5096 [Davies Liu] use string for version
47c6278 [Davies Liu] check python version of worker with driver
This PR introduces several performance optimizations to `HadoopFsRelation` and `ParquetRelation2`:
1. Moving `FileStatus` listing from `DataSourceStrategy` into a cache within `HadoopFsRelation`.
This new cache generalizes and replaces the one used in `ParquetRelation2`.
This also introduces an interface change: to reuse cached `FileStatus` objects, `HadoopFsRelation.buildScan` methods now receive `Array[FileStatus]` instead of `Array[String]`.
1. When Parquet task side metadata reading is enabled, skip reading row group information when reading Parquet footers.
This is basically what PR #5334 does. Also, now we uses `ParquetFileReader.readAllFootersInParallel` to read footers in parallel.
Another optimization in question is, instead of asking `HadoopFsRelation.buildScan` to return an `RDD[Row]` for a single selected partition and then union them all, we ask it to return an `RDD[Row]` for all selected partitions. This optimization is based on the fact that Hadoop configuration broadcasting used in `NewHadoopRDD` takes 34% time in the following microbenchmark. However, this complicates data source user code because user code must merge partition values manually.
To check the cost of broadcasting in `NewHadoopRDD`, I also did microbenchmark after removing the `broadcast` call in `NewHadoopRDD`. All results are shown below.
### Microbenchmark
#### Preparation code
Generating a partitioned table with 50k partitions, 1k rows per partition:
```scala
import sqlContext._
import sqlContext.implicits._
for (n <- 0 until 500) {
val data = for {
p <- (n * 10) until ((n + 1) * 10)
i <- 0 until 1000
} yield (i, f"val_$i%04d", f"$p%04d")
data.
toDF("a", "b", "p").
write.
partitionBy("p").
mode("append").
parquet(path)
}
```
#### Benchmarking code
```scala
import sqlContext._
import sqlContext.implicits._
import org.apache.spark.sql.types._
import com.google.common.base.Stopwatch
val path = "hdfs://localhost:9000/user/lian/5k"
def benchmark(n: Int)(f: => Unit) {
val stopwatch = new Stopwatch()
def run() = {
stopwatch.reset()
stopwatch.start()
f
stopwatch.stop()
stopwatch.elapsedMillis()
}
val records = (0 until n).map(_ => run())
(0 until n).foreach(i => println(s"Round $i: ${records(i)} ms"))
println(s"Average: ${records.sum / n.toDouble} ms")
}
benchmark(3) { read.parquet(path).explain(extended = true) }
```
#### Results
Before:
```
Round 0: 72528 ms
Round 1: 68938 ms
Round 2: 65372 ms
Average: 68946.0 ms
```
After:
```
Round 0: 59499 ms
Round 1: 53645 ms
Round 2: 53844 ms
Round 3: 49093 ms
Round 4: 50555 ms
Average: 53327.2 ms
```
Also removing Hadoop configuration broadcasting:
(Note that I was testing on a local laptop, thus network cost is pretty low.)
```
Round 0: 15806 ms
Round 1: 14394 ms
Round 2: 14699 ms
Round 3: 15334 ms
Round 4: 14123 ms
Average: 14871.2 ms
```
Author: Cheng Lian <lian@databricks.com>
Closes#6225 from liancheng/spark-7673 and squashes the following commits:
2d58a2b [Cheng Lian] Skips reading row group information when using task side metadata reading
7aa3748 [Cheng Lian] Optimizes FileStatusCache by introducing a map from parent directories to child files
ba41250 [Cheng Lian] Reuses HadoopFsRelation FileStatusCache in ParquetRelation2
3d278f7 [Cheng Lian] Fixes a bug when reading a single Parquet data file
b84612a [Cheng Lian] Fixes Scala style issue
6a08b02 [Cheng Lian] WIP: Moves file status cache into HadoopFSRelation
cc liancheng marmbrus
Author: Yin Huai <yhuai@databricks.com>
Closes#6130 from yhuai/directOutput and squashes the following commits:
312b07d [Yin Huai] A data source can use spark.sql.sources.outputCommitterClass to override the output committer.
This PR updates PR #6135 authored by zhzhan from Hortonworks.
----
This PR implements a Spark SQL data source for accessing ORC files.
> **NOTE**
>
> Although ORC is now an Apache TLP, the codebase is still tightly coupled with Hive. That's why the new ORC data source is under `org.apache.spark.sql.hive` package, and must be used with `HiveContext`. However, it doesn't require existing Hive installation to access ORC files.
1. Saving/loading ORC files without contacting Hive metastore
1. Support for complex data types (i.e. array, map, and struct)
1. Aware of common optimizations provided by Spark SQL:
- Column pruning
- Partitioning pruning
- Filter push-down
1. Schema evolution support
1. Hive metastore table conversion
This PR also include initial work done by scwf from Huawei (PR #3753).
Author: Zhan Zhang <zhazhan@gmail.com>
Author: Cheng Lian <lian@databricks.com>
Closes#6194 from liancheng/polishing-orc and squashes the following commits:
55ecd96 [Cheng Lian] Reorganizes ORC test suites
d4afeed [Cheng Lian] Addresses comments
21ada22 [Cheng Lian] Adds @since and @Experimental annotations
128bd3b [Cheng Lian] ORC filter bug fix
d734496 [Cheng Lian] Polishes the ORC data source
2650a42 [Zhan Zhang] resolve review comments
3c9038e [Zhan Zhang] resolve review comments
7b3c7c5 [Zhan Zhang] save mode fix
f95abfd [Zhan Zhang] reuse test suite
7cc2c64 [Zhan Zhang] predicate fix
4e61c16 [Zhan Zhang] minor change
305418c [Zhan Zhang] orc data source support
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Author: Cheng Lian <lian@databricks.com>
Closes#6091 from liancheng/spark-7570 and squashes the following commits:
8ff07e8 [Cheng Lian] Ignores _temporary during partition discovery
Replace the DriverQuirks with JdbcDialect(s) (and MySQLDialect/PostgresDialect)
and allow developers to change the dialects on the fly (for new JDBCRRDs only).
Some types (like an unsigned 64bit number) can be trivially mapped to java.
The status quo is that the RRD will fail to load.
This patch makes it possible to overwrite the type mapping to read e.g.
64Bit numbers as strings and handle them afterwards in software.
JDBCSuite has an example that maps all types to String, which should always
work (at the cost of extra code afterwards).
As a side effect it should now be possible to develop simple dialects
out-of-tree and even with spark-shell.
Author: Rene Treffer <treffer@measite.de>
Closes#5555 from rtreffer/jdbc-dialects and squashes the following commits:
3cbafd7 [Rene Treffer] [SPARK-6888] ignore classes belonging to changed API in MIMA report
fe7e2e8 [Rene Treffer] [SPARK-6888] Make the jdbc driver handling user-definable
JIRA: https://issues.apache.org/jira/browse/SPARK-7299
When connecting with oracle db through jdbc, the precision and scale of `BigDecimal` object returned by `ResultSet.getBigDecimal` is not correctly matched to the table schema reported by `ResultSetMetaData.getPrecision` and `ResultSetMetaData.getScale`.
So in case you insert a value like `19999` into a column with `NUMBER(12, 2)` type, you get through a `BigDecimal` object with scale as 0. But the dataframe schema has correct type as `DecimalType(12, 2)`. Thus, after you save the dataframe into parquet file and then retrieve it, you will get wrong result `199.99`.
Because it is reported to be problematic on jdbc connection with oracle db. It might be difficult to add test case for it. But according to the user's test on JIRA, it solves this problem.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5833 from viirya/jdbc_decimal_precision and squashes the following commits:
69bc2b5 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into jdbc_decimal_precision
928f864 [Liang-Chi Hsieh] Add comments.
5f9da94 [Liang-Chi Hsieh] Set up Decimal's precision and scale according to table schema instead of returned BigDecimal.
Learnt a lesson from SPARK-7655: Spark should avoid to use `scala.concurrent.ExecutionContext.Implicits.global` because the user may submit blocking actions to `scala.concurrent.ExecutionContext.Implicits.global` and exhaust all threads in it. This could crash Spark. So Spark should always use its own thread pools for safety.
This PR removes all usages of `scala.concurrent.ExecutionContext.Implicits.global` and uses proper thread pools to replace them.
Author: zsxwing <zsxwing@gmail.com>
Closes#6223 from zsxwing/SPARK-7693 and squashes the following commits:
a33ff06 [zsxwing] Decrease the max thread number from 1024 to 128
cf4b3fc [zsxwing] Remove "import scala.concurrent.ExecutionContext.Implicits.global"
In `SparkStrategies`, `RunnableDescribeCommand` is called with the output attributes of the table being described rather than the attributes for the `describe` command's output. I discovered this issue because it caused type conversion errors in some UnsafeRow conversion code that I'm writing.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6217 from JoshRosen/SPARK-7686 and squashes the following commits:
953a344 [Josh Rosen] Fix SPARK-7686 with a simple change in SparkStrategies.
a4eec9f [Josh Rosen] Add failing regression test for SPARK-7686
JIRA: https://issues.apache.org/jira/browse/SPARK-7447
`MetadataCache` in `ParquetRelation2` is annotated as `transient`. When `ParquetRelation2` is deserialized, we ask `MetadataCache` to refresh and perform schema merging again. It is time-consuming especially for very many parquet files.
With the new `FSBasedParquetRelation`, although `MetadataCache` is not `transient` now, `MetadataCache.refresh()` still performs schema merging again when the relation is deserialized.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6012 from viirya/without_remerge_schema and squashes the following commits:
2663957 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into without_remerge_schema
6ac7d93 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into without_remerge_schema
b0fc09b [Liang-Chi Hsieh] Don't generate and merge parquetSchema multiple times.
This case clause is already covered by the one above, and generates a compilation warning.
Author: Cheng Lian <lian@databricks.com>
Closes#6214 from liancheng/remove-unreachable-code and squashes the following commits:
c38ca7c [Cheng Lian] Removes an unreachable case clause
Also moved all the deprecated functions into one place for SQLContext and DataFrame, and updated tests to use the new API.
Author: Reynold Xin <rxin@databricks.com>
Closes#6210 from rxin/df-writer-reader-jdbc and squashes the following commits:
7465c2c [Reynold Xin] Fixed unit test.
118e609 [Reynold Xin] Updated tests.
3441b57 [Reynold Xin] Updated javadoc.
13cdd1c [Reynold Xin] [SPARK-7654][SQL] Move JDBC into DataFrame's reader/writer interface.
We forgot an assignment there.
/cc rxin
Author: Cheng Lian <lian@databricks.com>
Closes#6212 from liancheng/fix-df-writer and squashes the following commits:
711fbb0 [Cheng Lian] Adds a test case
3b72d78 [Cheng Lian] Fixes DataFrameWriter.mode(String)
