Author: Michael Armbrust <michael@databricks.com>
Closes#5545 from marmbrus/addCoalesce and squashes the following commits:
9fdf3f6 [Michael Armbrust] [SPARK-6972][SQL] Add Coalesce to DataFrame
JIRA https://issues.apache.org/jira/browse/SPARK-6899
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5517 from viirya/fix_codegen_average and squashes the following commits:
8ae5f65 [Liang-Chi Hsieh] Add the case of DecimalType.Unlimited to Average.
Fix this error by adding BinaryType comparor in GenerateOrdering.
JIRA https://issues.apache.org/jira/browse/SPARK-6927
Author: 云峤 <chensong.cs@alibaba-inc.com>
Closes#5524 from kaka1992/fix-codegen-sort and squashes the following commits:
d7e2afe [云峤] fix codegen sorting error
[SPARK-5277][SQL] - SparkSqlSerializer doesn't always register user specified KryoRegistrators
There were a few places where new SparkSqlSerializer instances were created with new, empty SparkConfs resulting in user specified registrators sometimes not getting initialized.
The fix is to try and pull a conf from the SparkEnv, and construct a new conf (that loads defaults) if one cannot be found.
The changes touched:
1) SparkSqlSerializer's resource pool (this appears to fix the issue in the comment)
2) execution.Exchange (for all of the partitioners)
3) execution.Limit (for the HashPartitioner)
A few tests were added to ColumnTypeSuite, ensuring that a custom registrator and serde is initialized and used when in-memory columns are written.
Author: Max Seiden <max@platfora.com>
This patch had conflicts when merged, resolved by
Committer: Michael Armbrust <michael@databricks.com>
Closes#5237 from mhseiden/sql_udt_kryo and squashes the following commits:
3175c2f [Max Seiden] [SPARK-5277][SQL] - address code review comments
e5011fb [Max Seiden] [SPARK-5277][SQL] - SparkSqlSerializer does not register user specified KryoRegistrators
Thanks for the initial work from Ishiihara in #3173
This PR introduce a new join method of sort merge join, which firstly ensure that keys of same value are in the same partition, and inside each partition the Rows are sorted by key. Then we can run down both sides together, find matched rows using [sort merge join](http://en.wikipedia.org/wiki/Sort-merge_join). In this way, we don't have to store the whole hash table of one side as hash join, thus we have less memory usage. Also, this PR would benefit from #3438 , making the sorting phrase much more efficient.
We introduced a new configuration of "spark.sql.planner.sortMergeJoin" to switch between this(`true`) and ShuffledHashJoin(`false`), probably we want the default value of it be `false` at first.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Michael Armbrust <michael@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Michael Armbrust <michael@databricks.com>
Closes#5208 from adrian-wang/smj and squashes the following commits:
2493b9f [Daoyuan Wang] fix style
5049d88 [Daoyuan Wang] propagate rowOrdering for RangePartitioning
f91a2ae [Daoyuan Wang] yin's comment: use external sort if option is enabled, add comments
f515cd2 [Daoyuan Wang] yin's comment: outputOrdering, join suite refine
ec8061b [Daoyuan Wang] minor change
413fd24 [Daoyuan Wang] Merge pull request #3 from marmbrus/pr/5208
952168a [Michael Armbrust] add type
5492884 [Michael Armbrust] copy when ordering
7ddd656 [Michael Armbrust] Cleanup addition of ordering requirements
b198278 [Daoyuan Wang] inherit ordering in project
c8e82a3 [Daoyuan Wang] fix style
6e897dd [Daoyuan Wang] hide boundReference from manually construct RowOrdering for key compare in smj
8681d73 [Daoyuan Wang] refactor Exchange and fix copy for sorting
2875ef2 [Daoyuan Wang] fix changed configuration
61d7f49 [Daoyuan Wang] add omitted comment
00a4430 [Daoyuan Wang] fix bug
078d69b [Daoyuan Wang] address comments: add comments, do sort in shuffle, and others
3af6ba5 [Daoyuan Wang] use buffer for only one side
171001f [Daoyuan Wang] change default outputordering
47455c9 [Daoyuan Wang] add apache license ...
a28277f [Daoyuan Wang] fix style
645c70b [Daoyuan Wang] address comments using sort
068c35d [Daoyuan Wang] fix new style and add some tests
925203b [Daoyuan Wang] address comments
07ce92f [Daoyuan Wang] fix ArrayIndexOutOfBound
42fca0e [Daoyuan Wang] code clean
e3ec096 [Daoyuan Wang] fix comment style..
2edd235 [Daoyuan Wang] fix outputpartitioning
57baa40 [Daoyuan Wang] fix sort eval bug
303b6da [Daoyuan Wang] fix several errors
95db7ad [Daoyuan Wang] fix brackets for if-statement
4464f16 [Daoyuan Wang] fix error
880d8e9 [Daoyuan Wang] sort merge join for spark sql
Even if we wrap column names in backticks like `` `a#$b.c` ``, we still handle the "." inside column name specially. I think it's fragile to use a special char to split name parts, why not put name parts in `UnresolvedAttribute` directly?
Author: Wenchen Fan <cloud0fan@outlook.com>
This patch had conflicts when merged, resolved by
Committer: Michael Armbrust <michael@databricks.com>
Closes#5511 from cloud-fan/6898 and squashes the following commits:
48e3e57 [Wenchen Fan] more style fix
820dc45 [Wenchen Fan] do not ignore newName in UnresolvedAttribute
d81ad43 [Wenchen Fan] fix style
11699d6 [Wenchen Fan] completely support special chars in column names
JIRA: https://issues.apache.org/jira/browse/SPARK-6844
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5475 from viirya/cache_memory_leak and squashes the following commits:
0b41235 [Liang-Chi Hsieh] fix style.
dc1d5d5 [Liang-Chi Hsieh] For comments.
78af229 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cache_memory_leak
26c9bb6 [Liang-Chi Hsieh] Add configuration to enable in-memory table scan accumulators.
1c3b06e [Liang-Chi Hsieh] Clean up accumulators used in InMemoryRelation when it is uncached.
This PR change the internal representation for StringType from java.lang.String to UTF8String, which is implemented use ArrayByte.
This PR should not break any public API, Row.getString() will still return java.lang.String.
This is the first step of improve the performance of String in SQL.
cc rxin
Author: Davies Liu <davies@databricks.com>
Closes#5350 from davies/string and squashes the following commits:
3b7bfa8 [Davies Liu] fix schema of AddJar
2772f0d [Davies Liu] fix new test failure
6d776a9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into string
59025c8 [Davies Liu] address comments from @marmbrus
341ec2c [Davies Liu] turn off scala style check in UTF8StringSuite
744788f [Davies Liu] Merge branch 'master' of github.com:apache/spark into string
b04a19c [Davies Liu] add comment for getString/setString
08d897b [Davies Liu] Merge branch 'master' of github.com:apache/spark into string
5116b43 [Davies Liu] rollback unrelated changes
1314a37 [Davies Liu] address comments from Yin
867bf50 [Davies Liu] fix String filter push down
13d9d42 [Davies Liu] Merge branch 'master' of github.com:apache/spark into string
2089d24 [Davies Liu] add hashcode check back
ac18ae6 [Davies Liu] address comment
fd11364 [Davies Liu] optimize UTF8String
8d17f21 [Davies Liu] fix hive compatibility tests
e5fa5b8 [Davies Liu] remove clone in UTF8String
28f3d81 [Davies Liu] Merge branch 'master' of github.com:apache/spark into string
28d6f32 [Davies Liu] refactor
537631c [Davies Liu] some comment about Date
9f4c194 [Davies Liu] convert data type for data source
956b0a4 [Davies Liu] fix hive tests
73e4363 [Davies Liu] Merge branch 'master' of github.com:apache/spark into string
9dc32d1 [Davies Liu] fix some hive tests
23a766c [Davies Liu] refactor
8b45864 [Davies Liu] fix codegen with UTF8String
bb52e44 [Davies Liu] fix scala style
c7dd4d2 [Davies Liu] fix some catalyst tests
38c303e [Davies Liu] fix python sql tests
5f9e120 [Davies Liu] fix sql tests
6b499ac [Davies Liu] fix style
a85fb27 [Davies Liu] refactor
d32abd1 [Davies Liu] fix utf8 for python api
4699c3a [Davies Liu] use Array[Byte] in UTF8String
21f67c6 [Davies Liu] cleanup
685fd07 [Davies Liu] use UTF8String instead of String for StringType
JIRA: https://issues.apache.org/jira/browse/SPARK-6730
It is very possible that keyword will be used as identifier in `OPTIONS`, this pr makes it works.
However, another approach is that we can request that `OPTIONS` can't include keywords and has to use alternative identifier (e.g. table -> cassandraTable) if needed.
If so, please let me know to close this pr. Thanks.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5520 from viirya/relax_options and squashes the following commits:
339fd68 [Liang-Chi Hsieh] Use regex parser.
92be11c [Liang-Chi Hsieh] Allow using keyword as identifier in OPTIONS.
JIRA https://issues.apache.org/jira/browse/SPARK-6871
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5480 from viirya/no_cte_after_cte and squashes the following commits:
4da3712 [Liang-Chi Hsieh] Create new test.
40b38ed [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into no_cte_after_cte
0edf568 [Liang-Chi Hsieh] for comments.
6591b79 [Liang-Chi Hsieh] WITH clause in CTE can not following another WITH clause.
Currently `min` is not supported in code generation. This pr adds the support for it.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5487 from viirya/add_min_codegen and squashes the following commits:
0ddec23 [Liang-Chi Hsieh] Add code generation support for Min.
In `leftsemijoin.q`, there is a data loading command for table `sales` already, but in `TestHive`, it also created the table `sales`, which causes duplicated records inserted into the `sales`.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#4506 from chenghao-intel/df_table and squashes the following commits:
0be05f7 [Cheng Hao] Remove the table `sales` creating from TestHive
Add a DirectParquetOutputCommitter class that skips _temporary directory when saving to s3. Add new config value "spark.sql.parquet.useDirectParquetOutputCommitter" (default false) to choose between the default output committer.
Author: Pei-Lun Lee <pllee@appier.com>
Closes#5042 from ypcat/spark-6352 and squashes the following commits:
e17bf47 [Pei-Lun Lee] Merge branch 'master' of https://github.com/apache/spark into spark-6352
9ae7545 [Pei-Lun Lee] [SPARL-6352] [SQL] Change to allow custom parquet output committer.
0d540b9 [Pei-Lun Lee] [SPARK-6352] [SQL] add license
c42468c [Pei-Lun Lee] [SPARK-6352] [SQL] add test case
0fc03ca [Pei-Lun Lee] [SPARK-6532] [SQL] hide class DirectParquetOutputCommitter
769bd67 [Pei-Lun Lee] DirectParquetOutputCommitter
f75e261 [Pei-Lun Lee] DirectParquetOutputCommitter
Supports replacing values with other values in DataFrames.
Python support should be in a separate pull request.
Author: Reynold Xin <rxin@databricks.com>
Closes#5282 from rxin/df-na-replace and squashes the following commits:
4b72434 [Reynold Xin] Removed println.
c8d9946 [Reynold Xin] col -> cols
fbb3c21 [Reynold Xin] [SPARK-6562][SQL] DataFrame.replace
This PR adds internal UDTs for expressions that are hijacking existing data types.
The following UDTs are added:
* `HyperLogLogUDT` (`BinaryType` as the SQL type) for `ApproxCountDistinctPartition`
* `OpenHashSetUDT` (`ArrayType` as the SQL type) for `CollectHashSet`, `NewSet`, `AddItemToSet`, and `CombineSets`.
I am also adding more unit tests for aggregation with code gen enabled.
JIRA: https://issues.apache.org/jira/browse/SPARK-6367
Author: Yin Huai <yhuai@databricks.com>
Closes#5094 from yhuai/expressionType and squashes the following commits:
8bcd11a [Yin Huai] Return types.
61a1d66 [Yin Huai] Merge remote-tracking branch 'upstream/master' into expressionType
e8b4599 [Yin Huai] Merge remote-tracking branch 'upstream/master' into expressionType
2753156 [Yin Huai] Ignore aggregations having sum functions for now.
b5eb259 [Yin Huai] Case object for HyperLogLog type.
00ebdbd [Yin Huai] deserialize/serialize.
54b87ae [Yin Huai] Add UDTs for expressions that return HyperLogLog and OpenHashSet.
This is useful for using pre-defined UDFs in SQLContext;
val df = Seq(("id1", 1), ("id2", 4), ("id3", 5)).toDF("id", "value")
val sqlctx = df.sqlContext
sqlctx.udf.register("simpleUdf", (v: Int) => v * v)
df.select($"id", sqlctx.callUdf("simpleUdf", $"value"))
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes#5061 from maropu/SupportUDFConversionInSparkContext and squashes the following commits:
f858aff [Takeshi YAMAMURO] Move the function into functions.scala
afd0380 [Takeshi YAMAMURO] Add a return type of callUDF
599b76c [Takeshi YAMAMURO] Remove the implicit conversion and add SqlContext#callUdf
8b56f10 [Takeshi YAMAMURO] Support an implicit conversion from udf"name" to an UDF defined in SQLContext
Author: haiyang <huhaiyang@huawei.com>
Closes#4929 from haiyangsea/cte and squashes the following commits:
220b67d [haiyang] add golden files for cte test
d3c7681 [haiyang] Merge branch 'master' into cte-repair
0ba2070 [haiyang] modify code style
9ce6b58 [haiyang] fix conflict
ff74741 [haiyang] add comment for With plan
0d56af4 [haiyang] code indention
776a440 [haiyang] add comments for resolve relation strategy
2fccd7e [haiyang] add comments for resolve relation strategy
241bbe2 [haiyang] fix cte problem of view
e9e1237 [haiyang] fix test case problem
614182f [haiyang] add test cases for CTE feature
32e415b [haiyang] add comment
1cc8c15 [haiyang] support with
03f1097 [haiyang] support with
e960099 [haiyang] support with
9aaa874 [haiyang] support with
0566978 [haiyang] support with
a99ecd2 [haiyang] support with
c3fa4c2 [haiyang] support with
3b6077f [haiyang] support with
5f8abe3 [haiyang] support with
4572b05 [haiyang] support with
f801f54 [haiyang] support with
cc marmbrus
Author: Volodymyr Lyubinets <vlyubin@gmail.com>
Closes#5279 from vlyubin/speedup and squashes the following commits:
e75a387 [Volodymyr Lyubinets] Changes to ScalaUDF
11a20ec [Volodymyr Lyubinets] Avoid creating a tuple
c327bc9 [Volodymyr Lyubinets] Moved the only remaining function from DataTypeConversions to DateUtils
dec6802 [Volodymyr Lyubinets] Addresed review feedback
74301fa [Volodymyr Lyubinets] Addressed review comments
afa3aa5 [Volodymyr Lyubinets] Minor refactoring, added license, removed debug output
881dc60 [Volodymyr Lyubinets] Moved to a separate module; addressed review comments; one extra place of usage; changed behaviour for Java
8cad6e2 [Volodymyr Lyubinets] Addressed review commments
41b2aa9 [Volodymyr Lyubinets] Creating converters for ScalaReflection stuff, and more
Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>
Closes#5138 from gvramana/sum_fix_codegen and squashes the following commits:
95f5fe4 [Venkata Ramana Gollamudi] rebase merge changes
12f45a5 [Venkata Ramana Gollamudi] Combined and added code generations tests as per comment
d6a76ac [Venkata Ramana Gollamudi] added support for codegeneration for CombineSum and tests
Now trait `StringComparison` is a `BinaryExpression`. In fact, it should be a `BinaryPredicate`.
By making `StringComparison` as `BinaryPredicate`, we can throw error when a `expressions.Predicate` can't translate to a data source `Filter` in function `selectFilters`.
Without this modification, because we will wrap a `Filter` outside the scanned results in `pruneFilterProjectRaw`, we can't detect about something is wrong in translating predicates to filters in `selectFilters`.
The unit test of #5285 demonstrates such problem. In that pr, even `expressions.Contains` is not properly translated to `sources.StringContains`, the filtering is still performed by the `Filter` and so the test passes.
Of course, by doing this modification, all `expressions.Predicate` classes need to have its data source `Filter` correspondingly.
There is a small bug in `FilteredScanSuite` for doing `StringEndsWith` filter. This pr also fixes it.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5309 from viirya/translate_predicate and squashes the following commits:
b176385 [Liang-Chi Hsieh] Address comment.
275a493 [Liang-Chi Hsieh] More properly test for StringStartsWith, StringEndsWith and StringContains.
caf2347 [Liang-Chi Hsieh] Make trait StringComparison as BinaryPredicate and throw error when Predicate can't translate to data source Filter.
This is a workaround for a problem reported on the user list. This doesn't fix the core problem, but in general is a more robust way to do renames.
Author: Michael Armbrust <michael@databricks.com>
Closes#5337 from marmbrus/toDFrename and squashes the following commits:
6a3159d [Michael Armbrust] [SPARK-6686][SQL] Use resolved output instead of names for toDF rename
We assume that `RDD[Row]` contains Scala types. So we need to convert them into catalyst types in createDataFrame. liancheng
Author: Xiangrui Meng <meng@databricks.com>
Closes#5329 from mengxr/SPARK-6672 and squashes the following commits:
2d52644 [Xiangrui Meng] set needsConversion = false in jsonRDD
06896e4 [Xiangrui Meng] add createDataFrame without conversion
4a3767b [Xiangrui Meng] convert Row to catalyst
In order to do inbound checking and type conversion, we should use Literal.create() instead of constructor.
Author: Davies Liu <davies@databricks.com>
Closes#5320 from davies/literal and squashes the following commits:
1667604 [Davies Liu] fix style and add comment
5f8c0fd [Davies Liu] use Literal.create instread of constructor
This PR is based on work by cloud-fan in #4904, but with two differences:
- We isolate the logic for Sort's special handling into `ResolveSortReferences`
- We avoid creating UnresolvedGetField expressions during resolution. Instead we either resolve GetField or we return None. This avoids us going down the wrong path early on.
Author: Michael Armbrust <michael@databricks.com>
Closes#5189 from marmbrus/nestedOrderBy and squashes the following commits:
b8cae45 [Michael Armbrust] fix another test
0f36a11 [Michael Armbrust] WIP
91820cd [Michael Armbrust] Fix bug.
Filters such as startsWith, endsWith, contains will be very useful for data sources that provide search functionality, e.g. Succinct, Elastic Search, Solr.
I also took this chance to improve documentation for the data source filters.
Author: Reynold Xin <rxin@databricks.com>
Closes#5285 from rxin/ds-string-filters and squashes the following commits:
f021727 [Reynold Xin] Fixed grammar.
7695a52 [Reynold Xin] [SPARK-6625][SQL] Add common string filters to data sources.
This pull request adds variants of DataFrame.na.drop and DataFrame.na.fill to the Scala/Java API, and DataFrame.fillna and DataFrame.dropna to the Python API.
Author: Reynold Xin <rxin@databricks.com>
Closes#5274 from rxin/df-missing-value and squashes the following commits:
4ee1b98 [Reynold Xin] Improve error reporting in Python.
33a330c [Reynold Xin] Remove replace for now.
bc4fdbb [Reynold Xin] Added documentation for replace.
d56f5a5 [Reynold Xin] Added replace for Scala/Java.
2385d00 [Reynold Xin] Feedback from Xiangrui on "how".
914a374 [Reynold Xin] fill with map.
185c67e [Reynold Xin] Allow specifying column subsets in fill.
749eb47 [Reynold Xin] fillna
249b94e [Reynold Xin] Removing undefined functions.
6a73c68 [Reynold Xin] Missing file.
67d7003 [Reynold Xin] [SPARK-6119][SQL] DataFrame.na.drop (Scala/Java) and DataFrame.dropna (Python)
Opening to replace #5188.
When Spark SQL infers a schema for a DataFrame, it will take the union of all field types present in the structured source data (e.g. an RDD of JSON data). When the source data for a row doesn't define a particular field on the DataFrame's schema, a null value will simply be assumed for this field. This workflow makes it very easy to construct tables and query over a set of structured data with a nonuniform schema. However, this behavior is not consistent in some cases when dealing with Parquet files and an external table managed by an external Hive metastore.
In our particular usecase, we use Spark Streaming to parse and transform our input data and then apply a window function to save an arbitrary-sized batch of data as a Parquet file, which itself will be added as a partition to an external Hive table via an *"ALTER TABLE... ADD PARTITION..."* statement. Since our input data is nonuniform, it is expected that not every partition batch will contain every field present in the table's schema obtained from the Hive metastore. As such, we expect that the schema of some of our Parquet files may not contain the same set fields present in the full metastore schema.
In such cases, it seems natural that Spark SQL would simply assume null values for any missing fields in the partition's Parquet file, assuming these fields are specified as nullable by the metastore schema. This is not the case in the current implementation of ParquetRelation2. The **mergeMetastoreParquetSchema()** method used to reconcile differences between a Parquet file's schema and a schema retrieved from the Hive metastore will raise an exception if the Parquet file doesn't match the same set of fields specified by the metastore.
This pull requests alters the behavior of **mergeMetastoreParquetSchema()** by having it first add any nullable fields from the metastore schema to the Parquet file schema if they aren't already present there.
Author: Adam Budde <budde@amazon.com>
Closes#5214 from budde/nullable-fields and squashes the following commits:
a52d378 [Adam Budde] Refactor ParquetSchemaSuite.scala for cases now permitted by SPARK-6471 and SPARK-6538
9041bfa [Adam Budde] Add missing nullable Metastore fields when merging a Parquet schema
Author: Reynold Xin <rxin@databricks.com>
Closes#5226 from rxin/empty-df and squashes the following commits:
1306d88 [Reynold Xin] Proper fix.
e135bb9 [Reynold Xin] [SPARK-6564][SQL] SQLContext.emptyDataFrame should contain 0 rows, not 1 row.
This is based on bug and test case proposed by viirya. See #5203 for a excellent description of the problem.
TLDR; The problem occurs because the function `groupBy(String)` calls `resolve`, which returns an `AttributeReference`. However, this `AttributeReference` is based on an analyzed plan which is thrown away. At execution time, we once again analyze the plan. However, in the case of self-joins, each call to analyze will produce a new tree for the left side of the join, rendering the previously returned `AttributeReference` invalid.
As a fix, I propose we keep the analyzed plan instead of the unresolved plan inside of a `DataFrame`.
Author: Michael Armbrust <michael@databricks.com>
Closes#5217 from marmbrus/preanalyzer and squashes the following commits:
1f98e2d [Michael Armbrust] revert change
dd4dec1 [Michael Armbrust] Use the analyzed plan in DataFrame
089c52e [Michael Armbrust] WIP
There are two cases for the new Parquet data source:
1. Partition columns exist in the Parquet data files
We don't need to push-down these predicates since partition pruning already handles them.
1. Partition columns don't exist in the Parquet data files
We can't push-down these predicates since they are considered as invalid columns by Parquet.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/5210)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#5210 from liancheng/spark-6554 and squashes the following commits:
4f7ec03 [Cheng Lian] Adds comments
e134ced [Cheng Lian] Don't push down predicates which reference partition column(s)
1. Slightly modifications to the code to make it more readable.
2. Added Python implementation.
3. Updated the documentation to state that we don't guarantee the output schema for this function and it should only be used for exploratory data analysis.
Author: Reynold Xin <rxin@databricks.com>
Closes#5201 from rxin/df-describe and squashes the following commits:
25a7834 [Reynold Xin] Reset run-tests.
6abdfee [Reynold Xin] [SPARK-6117] [SQL] Improvements to DataFrame.describe()
Currently in the parquet relation 2 implementation, error is thrown in case merged schema is not exactly the same as metastore schema.
But to support cases like deletion of column using replace column command, we can relax the restriction so that even if metastore schema is a subset of merged parquet schema, the query will work.
Author: Yash Datta <Yash.Datta@guavus.com>
Closes#5141 from saucam/replace_col and squashes the following commits:
e858d5b [Yash Datta] SPARK-6471: Fix test cases, add a new test case for metastore schema to be subset of parquet schema
5f2f467 [Yash Datta] SPARK-6471: Metastore schema should only be a subset of parquet schema to support dropping of columns using replace columns
Author: Michael Armbrust <michael@databricks.com>
Closes#5191 from marmbrus/kryoRowsWithSchema and squashes the following commits:
bb83522 [Michael Armbrust] Fix serialization of GenericRowWithSchema using kryo
f914f16 [Michael Armbrust] Add no arg constructor to GenericRowWithSchema
Please review my solution for SPARK-6117
Author: azagrebin <azagrebin@gmail.com>
Closes#5073 from azagrebin/SPARK-6117 and squashes the following commits:
f9056ac [azagrebin] [SPARK-6117] [SQL] create one aggregation and split it locally into resulting DF, colocate test data with test case
ddb3950 [azagrebin] [SPARK-6117] [SQL] simplify implementation, add test for DF without numeric columns
9daf31e [azagrebin] [SPARK-6117] [SQL] add describe function to DataFrame for summary statistics
Previously it was okay to throw away subqueries after analysis, as we would never try to use that tree for resolution again. However, with eager analysis in `DataFrame`s this can cause errors for queries such as:
```scala
val df = Seq(1,2,3).map(i => (i, i.toString)).toDF("int", "str")
df.as('x).join(df.as('y), $"x.str" === $"y.str").groupBy("x.str").count()
```
As a result, in this PR we defer the elimination of subqueries until the optimization phase.
Author: Michael Armbrust <michael@databricks.com>
Closes#5160 from marmbrus/subqueriesInDfs and squashes the following commits:
a9bb262 [Michael Armbrust] Update Optimizer.scala
27d25bf [Michael Armbrust] fix hive tests
9137e03 [Michael Armbrust] add type
81cd597 [Michael Armbrust] Avoid eliminating subqueries until optimization
Due to a recent change that made `StructType` a `Seq` we started inadvertently turning `StructType`s into generic `Traversable` when attempting nested tree transformations. In this PR we explicitly avoid descending into `DataType`s to avoid this bug.
Author: Michael Armbrust <michael@databricks.com>
Closes#5157 from marmbrus/udfFix and squashes the following commits:
26f7087 [Michael Armbrust] Fix transformations of TreeNodes that hold StructTypes
This is used by ML pipelines to embed ML attributes in columns created by ML transformers/estimators. marmbrus
Author: Xiangrui Meng <meng@databricks.com>
Closes#5151 from mengxr/SPARK-6361 and squashes the following commits:
bb30de3 [Xiangrui Meng] support adding a column with metadata in DF
Right now if there is a array field in a JavaBean, the user wold see an exception in `createDataFrame`. liancheng
Author: Xiangrui Meng <meng@databricks.com>
Closes#5146 from mengxr/SPARK-6475 and squashes the following commits:
51e87e5 [Xiangrui Meng] validate schemas
4f2df5e [Xiangrui Meng] recognize array types when infer data types from JavaBeans
One more thing if this PR is considered to be OK - it might make sense to add extra .jdbc() API's that take Properties to SQLContext.
Author: Volodymyr Lyubinets <vlyubin@gmail.com>
Closes#4859 from vlyubin/jdbcProperties and squashes the following commits:
7a8cfda [Volodymyr Lyubinets] Support jdbc connection properties in OPTIONS part of the query
This PR might have some issues with #3732 ,
and this would have merge conflicts with #3820 so the review can be delayed till that 2 were merged.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3822 from adrian-wang/parquetdate and squashes the following commits:
2c5d54d [Daoyuan Wang] add a test case
faef887 [Daoyuan Wang] parquet support for primitive date
97e9080 [Daoyuan Wang] parquet support for date type
When using "CREATE TEMPORARY TABLE AS SELECT" to create JSON table, we first delete the path file or directory and then generate a new directory with the same name. But if only read permission was granted, the delete failed.
Here we just throwing an error message to let users know what happened.
ParquetRelation2 may also hit this problem. I think to restrict JSONRelation and ParquetRelation2 must base on directory is more reasonable for access control. Maybe I can do it in follow up works.
Author: Yanbo Liang <ybliang8@gmail.com>
Author: Yanbo Liang <yanbohappy@gmail.com>
Closes#4610 from yanboliang/jsonInsertImprovements and squashes the following commits:
c387fce [Yanbo Liang] fix typos
42d7fb6 [Yanbo Liang] add unittest & fix output format
46f0d9d [Yanbo Liang] Update JSONRelation.scala
e2df8d5 [Yanbo Liang] check path exisit when write
79f7040 [Yanbo Liang] Update JSONRelation.scala
e4bc229 [Yanbo Liang] Update JSONRelation.scala
5a42d83 [Yanbo Liang] JSONRelation CTAS should check if delete is successful
When writing Parquet files, Spark 1.1.x persists the schema string into Parquet metadata with the result of `StructType.toString`, which was then deprecated in Spark 1.2 by a schema string in JSON format. But we still need to take the old schema format into account while reading Parquet files.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/5034)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#5034 from liancheng/spark-6315 and squashes the following commits:
a182f58 [Cheng Lian] Adds a regression test
b9c6dbe [Cheng Lian] Also tries the case class string parser while reading Parquet schema
Use `Utils.createTempDir()` to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
Author: Sean Owen <sowen@cloudera.com>
Closes#5029 from srowen/SPARK-6338 and squashes the following commits:
27b740a [Sean Owen] Fix hive-thriftserver tests that don't expect an existing dir
4a212fa [Sean Owen] Standardize a bit more temp dir management
9004081 [Sean Owen] Revert some added recursive-delete calls
57609e4 [Sean Owen] Use Utils.createTempDir() to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
We need to handle ambiguous `exprId`s that are produced by new aliases as well as those caused by leaf nodes (`MultiInstanceRelation`).
Attempting to fix this revealed a bug in `equals` for `Alias` as these objects were comparing equal even when the expression ids did not match. Additionally, `LocalRelation` did not correctly provide statistics, and some tests in `catalyst` and `hive` were not using the helper functions for comparing plans.
Based on #4991 by chenghao-intel
Author: Michael Armbrust <michael@databricks.com>
Closes#5062 from marmbrus/selfJoins and squashes the following commits:
8e9b84b [Michael Armbrust] check qualifier too
8038a36 [Michael Armbrust] handle aggs too
0b9c687 [Michael Armbrust] fix more tests
c3c574b [Michael Armbrust] revert change.
725f1ab [Michael Armbrust] add statistics
a925d08 [Michael Armbrust] check for conflicting attributes in join resolution
b022ef7 [Michael Armbrust] Handle project aliases.
d8caa40 [Michael Armbrust] test case: SPARK-6247
f9c67c2 [Michael Armbrust] Check for duplicate attributes in join resolution.
898af73 [Michael Armbrust] Fix Alias equality.
When getting file statuses, create file system from each path instead of a single one from hadoop configuration.
Author: Pei-Lun Lee <pllee@appier.com>
Closes#5039 from ypcat/spark-6351 and squashes the following commits:
a19a3fe [Pei-Lun Lee] [SPARK-6330] [SQL] fix test
506f5a0 [Pei-Lun Lee] [SPARK-6351] [SQL] fix test
fa2290e [Pei-Lun Lee] [SPARK-6330] [SQL] Rename test case and add comment
606c967 [Pei-Lun Lee] Merge branch 'master' of https://github.com/apache/spark into spark-6351
896e80a [Pei-Lun Lee] [SPARK-6351] [SQL] Add test case
2ae0916 [Pei-Lun Lee] [SPARK-6351] [SQL] ParquetRelation2 supporting multiple file systems
This PR adds a specialized in-memory column type for fixed-precision decimals.
For all other column types, a single integer column type ID is enough to determine which column type to use. However, this doesn't apply to fixed-precision decimal types with different precision and scale parameters. Moreover, according to the previous design, there seems no trivial way to encode precision and scale information into the columnar byte buffer. On the other hand, considering we always know the data type of the column to be built / scanned ahead of time. This PR no longer use column type ID to construct `ColumnBuilder`s and `ColumnAccessor`s, but resorts to the actual column data type. In this way, we can pass precision / scale information along the way.
The column type ID is now not used anymore and can be removed in a future PR.
### Micro benchmark result
The following micro benchmark builds a simple table with 2 million decimals (precision = 10, scale = 0), cache it in memory, then count all the rows. Code (simply paste it into Spark shell):
```scala
import sc._
import sqlContext._
import sqlContext.implicits._
import org.apache.spark.sql.types._
import com.google.common.base.Stopwatch
def benchmark(n: Int)(f: => Long) {
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: ${records.sum / n.toDouble} ms")
}
// Explicit casting is required because ScalaReflection can't inspect decimal precision
parallelize(1 to 2000000)
.map(i => Tuple1(Decimal(i, 10, 0)))
.toDF("dec")
.select($"dec" cast DecimalType(10, 0))
.registerTempTable("dec")
sql("CACHE TABLE dec")
val df = table("dec")
// Warm up
df.count()
df.count()
benchmark(5) {
df.count()
}
```
With `FIXED_DECIMAL` column type:
- Round 0: 75 ms
- Round 1: 97 ms
- Round 2: 75 ms
- Round 3: 70 ms
- Round 4: 72 ms
- Average: 77.8 ms
Without `FIXED_DECIMAL` column type:
- Round 0: 1233 ms
- Round 1: 1170 ms
- Round 2: 1171 ms
- Round 3: 1141 ms
- Round 4: 1141 ms
- Average: 1171.2 ms
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4938)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4938 from liancheng/decimal-column-type and squashes the following commits:
fef5338 [Cheng Lian] Updates fixed decimal column type related test cases
e08ab5b [Cheng Lian] Only resorts to FIXED_DECIMAL when the value can be held in a long
4db713d [Cheng Lian] Adds in-memory column type for fixed-precision decimals
Author: Volodymyr Lyubinets <vlyubin@gmail.com>
Closes#4988 from vlyubin/columncomp and squashes the following commits:
92d7c8f [Volodymyr Lyubinets] Added equals to Column
Avoid `UnsupportedOperationException` from JsonRDD.inferSchema on empty RDD.
Not sure if this is supposed to be an error (but a better one), but it seems like this case can come up if the input is down-sampled so much that nothing is sampled.
Now stuff like this:
```
sqlContext.jsonRDD(sc.parallelize(List[String]()))
```
just results in
```
org.apache.spark.sql.DataFrame = []
```
Author: Sean Owen <sowen@cloudera.com>
Closes#4971 from srowen/SPARK-6245 and squashes the following commits:
3699964 [Sean Owen] Set() -> Set.empty
3c619e1 [Sean Owen] Avoid UnsupportedOperationException from JsonRDD.inferSchema on empty RDD
Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
Author: Sean Owen <sowen@cloudera.com>
Closes#4950 from srowen/SPARK-6225 and squashes the following commits:
3080972 [Sean Owen] Ordered imports: Java, Scala, 3rd party, Spark
c67985b [Sean Owen] Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
jira: https://issues.apache.org/jira/browse/SPARK-6163
Author: Yin Huai <yhuai@databricks.com>
Closes#4896 from yhuai/SPARK-6163 and squashes the following commits:
45e023e [Yin Huai] Address @chenghao-intel's comment.
2e8734e [Yin Huai] Use JSON data source for jsonFile.
92a4a33 [Yin Huai] Test.
Based on #4904 with style errors fixed.
`LogicalPlan#resolve` will not only produce `Attribute`, but also "`GetField` chain".
So in `ResolveSortReferences`, after resolve the ordering expressions, we should not just collect the `Attribute` results, but also `Attribute` at the bottom of "`GetField` chain".
Author: Wenchen Fan <cloud0fan@outlook.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#4918 from marmbrus/pr/4904 and squashes the following commits:
997f84e [Michael Armbrust] fix style
3eedbfc [Wenchen Fan] fix 6145
Integration test suites in the JDBC data source (`MySQLIntegration` and `PostgresIntegration`) depend on docker-client 2.7.5, which transitively depends on Guava 17.0. Unfortunately, Guava 17.0 is causing test runtime binary compatibility issues when Spark is compiled against Hive 0.12.0, or Hadoop 2.4.
Considering `MySQLIntegration` and `PostgresIntegration` are ignored right now, I'd suggest moving them from the Spark project to the [Spark integration tests] [1] project. This PR removes both the JDBC data source integration tests and the docker-client test dependency.
[1]: |https://github.com/databricks/spark-integration-tests
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4872)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4872 from liancheng/remove-docker-client and squashes the following commits:
1f4169e [Cheng Lian] Removes DockerHacks
159b24a [Cheng Lian] Removed JDBC integration tests which depends on docker-client
- Various Fixes to docs
- Make data source traits actually interfaces
Based on #4862 but with fixed conflicts.
Author: Reynold Xin <rxin@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#4868 from marmbrus/pr/4862 and squashes the following commits:
fe091ea [Michael Armbrust] Merge remote-tracking branch 'origin/master' into pr/4862
0208497 [Reynold Xin] Test fixes.
34e0a28 [Reynold Xin] [SPARK-5310][SQL] Various fixes to Spark SQL docs.
This PR contains the following changes:
1. Add a new method, `DataType.equalsIgnoreCompatibleNullability`, which is the middle ground between DataType's equality check and `DataType.equalsIgnoreNullability`. For two data types `from` and `to`, it does `equalsIgnoreNullability` as well as if the nullability of `from` is compatible with that of `to`. For example, the nullability of `ArrayType(IntegerType, containsNull = false)` is compatible with that of `ArrayType(IntegerType, containsNull = true)` (for an array without null values, we can always say it may contain null values). However, the nullability of `ArrayType(IntegerType, containsNull = true)` is incompatible with that of `ArrayType(IntegerType, containsNull = false)` (for an array that may have null values, we cannot say it does not have null values).
2. For the `resolved` field of `InsertIntoTable`, use `equalsIgnoreCompatibleNullability` to replace the equality check of the data types.
3. For our data source write path, when appending data, we always use the schema of existing table to write the data. This is important for parquet, since nullability direct impacts the way to encode/decode values. If we do not do this, we may see corrupted values when reading values from a set of parquet files generated with different nullability settings.
4. When generating a new parquet table, we always set nullable/containsNull/valueContainsNull to true. So, we will not face situations that we cannot append data because containsNull/valueContainsNull in an Array/Map column of the existing table has already been set to `false`. This change makes the whole data pipeline more robust.
5. Update the equality check of JSON relation. Since JSON does not really cares nullability, `equalsIgnoreNullability` seems a better choice to compare schemata from to JSON tables.
JIRA: https://issues.apache.org/jira/browse/SPARK-5950
Thanks viirya for the initial work in #4729.
cc marmbrus liancheng
Author: Yin Huai <yhuai@databricks.com>
Closes#4826 from yhuai/insertNullabilityCheck and squashes the following commits:
3b61a04 [Yin Huai] Revert change on equals.
80e487e [Yin Huai] asNullable in UDT.
587d88b [Yin Huai] Make methods private.
0cb7ea2 [Yin Huai] marmbrus's comments.
3cec464 [Yin Huai] Cheng's comments.
486ed08 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertNullabilityCheck
d3747d1 [Yin Huai] Remove unnecessary change.
8360817 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertNullabilityCheck
8a3f237 [Yin Huai] Use equalsIgnoreNullability instead of equality check.
0eb5578 [Yin Huai] Fix tests.
f6ed813 [Yin Huai] Update old parquet path.
e4f397c [Yin Huai] Unit tests.
b2c06f8 [Yin Huai] Ignore nullability in JSON relation's equality check.
8bd008b [Yin Huai] nullable, containsNull, and valueContainsNull will be always true for parquet data.
bf50d73 [Yin Huai] When appending data, we use the schema of the existing table instead of the schema of the new data.
0a703e7 [Yin Huai] Test failed again since we cannot read correct content.
9a26611 [Yin Huai] Make InsertIntoTable happy.
8f19fe5 [Yin Huai] equalsIgnoreCompatibleNullability
4ec17fd [Yin Huai] Failed test.
Always set `containsNull = true` when infer the schema of JSON datasets. If we set `containsNull` based on records we scanned, we may miss arrays with null values when we do sampling. Also, because future data can have arrays with null values, if we convert JSON data to parquet, always setting `containsNull = true` is a more robust way to go.
JIRA: https://issues.apache.org/jira/browse/SPARK-6052
Author: Yin Huai <yhuai@databricks.com>
Closes#4806 from yhuai/jsonArrayContainsNull and squashes the following commits:
05eab9d [Yin Huai] Change containsNull to true.
It is useful to let the user decide the number of rows to show in DataFrame.show
Author: Jacky Li <jacky.likun@huawei.com>
Closes#4767 from jackylk/show and squashes the following commits:
a0e0f4b [Jacky Li] fix testcase
7cdbe91 [Jacky Li] modify according to comment
bb54537 [Jacky Li] for Java compatibility
d7acc18 [Jacky Li] modify according to comments
981be52 [Jacky Li] add numRows param in DataFrame.show()
`ReadContext.init` calls `InitContext.getMergedKeyValueMetadata`, which doesn't know how to merge conflicting user defined key-value metadata and throws exception. In our case, when dealing with different but compatible schemas, we have different Spark SQL schema JSON strings in different Parquet part-files, thus causes this problem. Reading similar Parquet files generated by Hive doesn't suffer from this issue.
In this PR, we manually merge the schemas before passing it to `ReadContext` to avoid the exception.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4768)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4768 from liancheng/spark-6010 and squashes the following commits:
9002f0a [Cheng Lian] Fixes SPARK-6010
Author: Michael Armbrust <michael@databricks.com>
Closes#4757 from marmbrus/udtConversions and squashes the following commits:
3714aad [Michael Armbrust] [SPARK-5996][SQL] Fix specialized outbound conversions
Also added desc/asc function for constructing sorting expressions more conveniently. And added a small fix to lift alias out of cast expression.
Author: Reynold Xin <rxin@databricks.com>
Closes#4752 from rxin/SPARK-5985 and squashes the following commits:
aeda5ae [Reynold Xin] Added Experimental flag to ColumnName.
047ad03 [Reynold Xin] Lift alias out of cast.
c9cf17c [Reynold Xin] [SPARK-5985][SQL] DataFrame sortBy -> orderBy in Python.
Added a new test suite to make sure Java DF programs can use varargs properly.
Also moved all suites into test.org.apache.spark package to make sure the suites also test for method visibility.
Author: Reynold Xin <rxin@databricks.com>
Closes#4751 from rxin/df-tests and squashes the following commits:
1e8b8e4 [Reynold Xin] Fixed imports and renamed JavaAPISuite.
a6ca53b [Reynold Xin] [SPARK-5904][SQL] DataFrame Java API test suites.
Author: Michael Armbrust <michael@databricks.com>
Closes#4738 from marmbrus/udtRepart and squashes the following commits:
c06d7b5 [Michael Armbrust] fix compilation
91c8829 [Michael Armbrust] [SQL][SPARK-5532] Repartition should not use external rdd representation
Author: Michael Armbrust <michael@databricks.com>
Closes#4736 from marmbrus/asExprs and squashes the following commits:
5ba97e4 [Michael Armbrust] [SPARK-5910][SQL] Support for as in selectExpr
1. Column is no longer a DataFrame to simplify class hierarchy.
2. Don't use varargs on abstract methods (see Scala compiler bug SI-9013).
Author: Reynold Xin <rxin@databricks.com>
Closes#4686 from rxin/SPARK-5904 and squashes the following commits:
fd9b199 [Reynold Xin] Fixed Python tests.
df25cef [Reynold Xin] Non final.
5221530 [Reynold Xin] [SPARK-5904][SQL] DataFrame API fixes.
Also added test cases for checking the serializability of HiveContext and SQLContext.
Author: Reynold Xin <rxin@databricks.com>
Closes#4628 from rxin/SPARK-5840 and squashes the following commits:
ecb3bcd [Reynold Xin] test cases and reviews.
55eb822 [Reynold Xin] [SPARK-5840][SQL] HiveContext cannot be serialized due to tuple extraction.
This pull request replaces calls to deprecated methods from `java.util.Date` with near-equivalents in `java.util.Calendar`.
Author: Tor Myklebust <tmyklebu@gmail.com>
Closes#4668 from tmyklebu/master and squashes the following commits:
66215b1 [Tor Myklebust] Use GregorianCalendar instead of Timestamp get methods.
Although we've migrated to the DataFrame API, lots of code still uses `rdd` or `srdd` as local variable names. This PR tries to address these naming inconsistencies and some other minor DataFrame related style issues.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4670)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4670 from liancheng/df-cleanup and squashes the following commits:
3e14448 [Cheng Lian] Cleans up DataFrame variable names and toDF() calls
Author: Reynold Xin <rxin@databricks.com>
Closes#4640 from rxin/SPARK-5853 and squashes the following commits:
9c6f569 [Reynold Xin] [SPARK-5853][SQL] Schema support in Row.
This PR adds a `ShowTablesCommand` to support `SHOW TABLES [IN databaseName]` SQL command. The result of `SHOW TABLE` has two columns, `tableName` and `isTemporary`. For temporary tables, the value of `isTemporary` column will be `false`.
JIRA: https://issues.apache.org/jira/browse/SPARK-4865
Author: Yin Huai <yhuai@databricks.com>
Closes#4618 from yhuai/showTablesCommand and squashes the following commits:
0c09791 [Yin Huai] Use ShowTablesCommand.
85ee76d [Yin Huai] Since SHOW TABLES is not a Hive native command any more and we will not see "OK" (originally generated by Hive's driver), use SHOW DATABASES in the test.
94bacac [Yin Huai] Add SHOW TABLES to the list of noExplainCommands.
d71ed09 [Yin Huai] Fix test.
a4a6ec3 [Yin Huai] Add SHOW TABLE command.
JIRA: https://issues.apache.org/jira/browse/SPARK-5839
Author: Yin Huai <yhuai@databricks.com>
Closes#4626 from yhuai/SPARK-5839 and squashes the following commits:
f779d85 [Yin Huai] Use subqeury to wrap replaced ParquetRelation.
2695f13 [Yin Huai] Merge remote-tracking branch 'upstream/master' into SPARK-5839
f1ba6ca [Yin Huai] Address comment.
2c7fa08 [Yin Huai] Use Subqueries to wrap a data source table.
JIRA: https://issues.apache.org/jira/browse/SPARK-5746
liancheng marmbrus
Author: Yin Huai <yhuai@databricks.com>
Closes#4617 from yhuai/insertOverwrite and squashes the following commits:
8e3019d [Yin Huai] Fix compilation error.
499e8e7 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertOverwrite
e76e85a [Yin Huai] Address comments.
ac31b3c [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertOverwrite
f30bdad [Yin Huai] Use toDF.
99da57e [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertOverwrite
6b7545c [Yin Huai] Add a pre write check to the data source API.
a88c516 [Yin Huai] DDLParser will take a parsering function to take care CTAS statements.
This PR adds the following filter types for data sources API:
- `IsNull`
- `IsNotNull`
- `Not`
- `And`
- `Or`
The code which converts Catalyst predicate expressions to data sources filters is very similar to filter conversion logics in `ParquetFilters` which converts Catalyst predicates to Parquet filter predicates. In this way we can support nested AND/OR/NOT predicates without changing current `BaseScan` type hierarchy.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4623)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Michael Armbrust <michael@databricks.com>
Closes#4623 from liancheng/more-fiters and squashes the following commits:
1b296f4 [Cheng Lian] Add more filter types for data sources API
This PR migrates the Parquet data source to the new data source write support API. Now users can also overwriting and appending to existing tables. Notice that inserting into partitioned tables is not supported yet.
When Parquet data source is enabled, insertion to Hive Metastore Parquet tables is also fullfilled by the Parquet data source. This is done by the newly introduced `HiveMetastoreCatalog.ParquetConversions` rule, which is a "proper" implementation of the original hacky `HiveStrategies.ParquetConversion`. The latter is still preserved, and can be removed together with the old Parquet support in the future.
TODO:
- [x] Update outdated comments in `newParquet.scala`.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4563)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4563 from liancheng/parquet-refining and squashes the following commits:
fa98d27 [Cheng Lian] Fixes test cases which should disable off Parquet data source
2476e82 [Cheng Lian] Fixes compilation error introduced during rebasing
a83d290 [Cheng Lian] Passes Hive Metastore partitioning information to ParquetRelation2
Author: Yin Huai <yhuai@databricks.com>
Closes#4542 from yhuai/moveSaveMode and squashes the following commits:
65a4425 [Yin Huai] Move SaveMode to sql package.
Author: Yin Huai <yhuai@databricks.com>
Closes#4544 from yhuai/jsonUseLongTypeByDefault and squashes the following commits:
6e2ffc2 [Yin Huai] Use LongType as the default type for integers in JSON schema inference.
Author: Michael Armbrust <michael@databricks.com>
Author: wangfei <wangfei1@huawei.com>
Closes#4558 from marmbrus/errorMessages and squashes the following commits:
5e5ab50 [Michael Armbrust] Merge pull request #15 from scwf/errorMessages
fa38881 [wangfei] fix for grouping__id
f279a71 [wangfei] make right references for ScriptTransformation
d29fbde [Michael Armbrust] extra case
1a797b4 [Michael Armbrust] comments
d4e9015 [Michael Armbrust] add comment
af9e668 [Michael Armbrust] no braces
34eb3a4 [Michael Armbrust] more work
6197cd5 [Michael Armbrust] [SQL] Better error messages for analysis failures
- Removed DataFrame.apply for projection & filtering since they are extremely confusing.
- Added implicits for RDD[Int], RDD[Long], and RDD[String]
Author: Reynold Xin <rxin@databricks.com>
Closes#4543 from rxin/df-cleanup and squashes the following commits:
81ec915 [Reynold Xin] [SQL] More DataFrame fixes.
Also I fix a bunch of bad output in test cases.
Author: Michael Armbrust <michael@databricks.com>
Closes#4520 from marmbrus/selfJoin and squashes the following commits:
4f4a85c [Michael Armbrust] comments
49c8e26 [Michael Armbrust] fix tests
6fc38de [Michael Armbrust] fix style
55d64b3 [Michael Armbrust] fix dataframe selfjoins
Also took the chance to fixed up some style ...
Author: Reynold Xin <rxin@databricks.com>
Closes#4489 from rxin/SPARK-5702 and squashes the following commits:
74f42e3 [Reynold Xin] [SPARK-5702][SQL] Allow short names for built-in data sources.
Do not recursively strip out projects. Only strip the first level project.
```scala
df("colA") + df("colB").as("colC")
```
Previously, the above would construct an invalid plan.
Author: Reynold Xin <rxin@databricks.com>
Closes#4519 from rxin/computability and squashes the following commits:
87ff763 [Reynold Xin] Code review feedback.
015c4fc [Reynold Xin] [SQL][DataFrame] Fix column computability.
Deprecate inferSchema() and applySchema(), use createDataFrame() instead, which could take an optional `schema` to create an DataFrame from an RDD. The `schema` could be StructType or list of names of columns.
Author: Davies Liu <davies@databricks.com>
Closes#4498 from davies/create and squashes the following commits:
08469c1 [Davies Liu] remove Scala/Java API for now
c80a7a9 [Davies Liu] fix hive test
d1bd8f2 [Davies Liu] cleanup applySchema
9526e97 [Davies Liu] createDataFrame from RDD with columns
Author: Cheng Hao <hao.cheng@intel.com>
Closes#4468 from chenghao-intel/json and squashes the following commits:
aeb7801 [Cheng Hao] avoid multiple json generator created
Also start from the bottom so we show the first error instead of the top error.
Author: Michael Armbrust <michael@databricks.com>
Closes#4439 from marmbrus/analysisException and squashes the following commits:
45862a0 [Michael Armbrust] fix hive test
a773bba [Michael Armbrust] Merge remote-tracking branch 'origin/master' into analysisException
f88079f [Michael Armbrust] update more cases
fede90a [Michael Armbrust] newline
fbf4bc3 [Michael Armbrust] move to sql
6235db4 [Michael Armbrust] [SQL] Add an exception for analysis errors.
Author: Michael Armbrust <michael@databricks.com>
Closes#4436 from marmbrus/dfToString and squashes the following commits:
8a3c35f [Michael Armbrust] Merge remote-tracking branch 'origin/master' into dfToString
b72a81b [Michael Armbrust] add toString
~~The rule is simple: If you want `a.b` work, then `a` must be some level of nested array of struct(level 0 means just a StructType). And the result of `a.b` is same level of nested array of b-type.
An optimization is: the resolve chain looks like `Attribute -> GetItem -> GetField -> GetField ...`, so we could transmit the nested array information between `GetItem` and `GetField` to avoid repeated computation of `innerDataType` and `containsNullList` of that nested array.~~
marmbrus Could you take a look?
to evaluate `a.b`, if `a` is array of struct, then `a.b` means get field `b` on each element of `a`, and return a result of array.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#2405 from cloud-fan/nested-array-dot and squashes the following commits:
08a228a [Wenchen Fan] support dot notation on array of struct
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4440)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4440 from liancheng/parquet-oops and squashes the following commits:
f21ede4 [Cheng Lian] HiveParquetSuite was disabled by mistake, re-enable them.
Sometimes tests were failing due to the creation of multiple `SparkContext`s in a single JVM.
Author: Michael Armbrust <michael@databricks.com>
Closes#4441 from marmbrus/javaTests and squashes the following commits:
657b1e0 [Michael Armbrust] [SQL] Use TestSQLContext in Java tests
This PR adds a rule to Analyzer that will add preinsert data type casting and field renaming to the select clause in an `INSERT INTO/OVERWRITE` statement. Also, with the change of this PR, we always invalidate our in memory data cache after inserting into a BaseRelation.
cc marmbrus liancheng
Author: Yin Huai <yhuai@databricks.com>
Closes#4373 from yhuai/insertFollowUp and squashes the following commits:
08237a7 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertFollowUp
316542e [Yin Huai] Doc update.
c9ccfeb [Yin Huai] Revert a unnecessary change.
84aecc4 [Yin Huai] Address comments.
1951fe1 [Yin Huai] Merge remote-tracking branch 'upstream/master'
c18da34 [Yin Huai] Invalidate cache after insert.
727f21a [Yin Huai] Preinsert casting and renaming.
Author: Reynold Xin <rxin@databricks.com>
Closes#4410 from rxin/df-renameCol and squashes the following commits:
a6a796e [Reynold Xin] [SPARK-5639][SQL] Support DataFrame.renameColumn.
Author: Reynold Xin <rxin@databricks.com>
Closes#4408 from rxin/df-config-eager and squashes the following commits:
c0204cf [Reynold Xin] [SPARK-5638][SQL] Add a config flag to disable eager analysis of DataFrames.
This PR adds three major improvements to Parquet data source:
1. Partition discovery
While reading Parquet files resides in Hive style partition directories, `ParquetRelation2` automatically discovers partitioning information and infers partition column types.
This is also a partial work for [SPARK-5182] [1], which aims to provide first class partitioning support for the data source API. Related code in this PR can be easily extracted to the data source API level in future versions.
1. Schema merging
When enabled, Parquet data source collects schema information from all Parquet part-files and tries to merge them. Exceptions are thrown when incompatible schemas are detected. This feature is controlled by data source option `parquet.mergeSchema`, and is enabled by default.
1. Metastore Parquet table conversion moved to analysis phase
This greatly simplifies the conversion logic. `ParquetConversion` strategy can be removed once the old Parquet implementation is removed in the future.
This version of Parquet data source aims to entirely replace the old Parquet implementation. However, the old version hasn't been removed yet. Users can fall back to the old version by turning off SQL configuration `spark.sql.parquet.useDataSourceApi`.
Other JIRA tickets fixed as side effects in this PR:
- [SPARK-5509] [3]: `EqualTo` now uses a proper `Ordering` to compare binary types.
- [SPARK-3575] [4]: Metastore schema is now preserved and passed to `ParquetRelation2` via data source option `parquet.metastoreSchema`.
TODO:
- [ ] More test cases for partition discovery
- [x] Fix write path after data source write support (#4294) is merged
It turned out to be non-trivial to fall back to old Parquet implementation on the write path when Parquet data source is enabled. Since we're planning to include data source write support in 1.3.0, I simply ignored two test cases involving Parquet insertion for now.
- [ ] Fix outdated comments and documentations
PS: This PR looks big, but more than a half of the changed lines in this PR are trivial changes to test cases. To test Parquet with and without the new data source, almost all Parquet test cases are moved into wrapper driver functions. This introduces hundreds of lines of changes.
[1]: https://issues.apache.org/jira/browse/SPARK-5182
[2]: https://issues.apache.org/jira/browse/SPARK-5528
[3]: https://issues.apache.org/jira/browse/SPARK-5509
[4]: https://issues.apache.org/jira/browse/SPARK-3575
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4308)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4308 from liancheng/parquet-partition-discovery and squashes the following commits:
b6946e6 [Cheng Lian] Fixes MiMA issues, addresses comments
8232e17 [Cheng Lian] Write support for Parquet data source
a49bd28 [Cheng Lian] Fixes spelling typo in trait name "CreateableRelationProvider"
808380f [Cheng Lian] Fixes issues introduced while rebasing
50dd8d1 [Cheng Lian] Addresses @rxin's comment, fixes UDT schema merging
adf2aae [Cheng Lian] Fixes compilation error introduced while rebasing
4e0175f [Cheng Lian] Fixes Python Parquet API, we need Py4J array to call varargs method
0d8ec1d [Cheng Lian] Adds more test cases
b35c8c6 [Cheng Lian] Fixes some typos and outdated comments
dd704fd [Cheng Lian] Fixes Python Parquet API
596c312 [Cheng Lian] Uses switch to control whether use Parquet data source or not
7d0f7a2 [Cheng Lian] Fixes Metastore Parquet table conversion
a1896c7 [Cheng Lian] Fixes all existing Parquet test suites except for ParquetMetastoreSuite
5654c9d [Cheng Lian] Draft version of Parquet partition discovery and schema merging
Hi, rxin marmbrus
I considered your suggestion (in #4127) and now re-write it. This is now up-to-date.
Could u please review it ?
Author: OopsOutOfMemory <victorshengli@126.com>
Closes#4227 from OopsOutOfMemory/describe and squashes the following commits:
053826f [OopsOutOfMemory] describe
SQLQuerySuite test failure:
[info] - simple select (22 milliseconds)
[info] - sorting (722 milliseconds)
[info] - external sorting (728 milliseconds)
[info] - limit (95 milliseconds)
[info] - date row *** FAILED *** (35 milliseconds)
[info] Results do not match for query:
[info] 'Limit 1
[info] 'Project [CAST(2015-01-28, DateType) AS c0#3630]
[info] 'UnresolvedRelation [testData], None
[info]
[info] == Analyzed Plan ==
[info] Limit 1
[info] Project [CAST(2015-01-28, DateType) AS c0#3630]
[info] LogicalRDD [key#0,value#1], MapPartitionsRDD[1] at mapPartitions at ExistingRDD.scala:35
[info]
[info] == Physical Plan ==
[info] Limit 1
[info] Project [16463 AS c0#3630]
[info] PhysicalRDD [key#0,value#1], MapPartitionsRDD[1] at mapPartitions at ExistingRDD.scala:35
[info]
[info] == Results ==
[info] !== Correct Answer - 1 == == Spark Answer - 1 ==
[info] ![2015-01-28] [2015-01-27] (QueryTest.scala:77)
[info] org.scalatest.exceptions.TestFailedException:
[info] at org.scalatest.Assertions$class.newAssertionFailedException(Assertions.scala:495)
[info] at org.scalatest.FunSuite.newAssertionFailedException(FunSuite.scala:1555)
[info] at org.scalatest.Assertions$class.fail(Assertions.scala:1328)
[info] at org.scalatest.FunSuite.fail(FunSuite.scala:1555)
[info] at org.apache.spark.sql.QueryTest.checkAnswer(QueryTest.scala:77)
[info] at org.apache.spark.sql.QueryTest.checkAnswer(QueryTest.scala:95)
[info] at org.apache.spark.sql.SQLQuerySuite$$anonfun$23.apply$mcV$sp(SQLQuerySuite.scala:300)
[info] at org.apache.spark.sql.SQLQuerySuite$$anonfun$23.apply(SQLQuerySuite.scala:300)
[info] at org.apache.spark.sql.SQLQuerySuite$$anonfun$23.apply(SQLQuerySuite.scala:300)
[info] at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
[info] at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
[info] at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
[info] at org.scalatest.Transformer.apply(Transformer.scala:22)
[info] at org.scalatest.Transformer.apply(Transformer.scala:20)
[info] at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166)
[info] at org.scalatest.Suite$class.withFixture(Suite.scala:1122)
[info] at org.scalatest.FunSuite.withFixture(FunSuite.scala:1555)
[info] at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
[info] at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
[info] at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:175)
[info] at org.scalatest.FunSuite.runTest(FunSuite.scala:1555)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208)
[info] at org.scalatest.SuperEngine$$anonfun$traverseSubNode
Author: wangfei <wangfei1@huawei.com>
Closes#4395 from scwf/SQLQuerySuite and squashes the following commits:
1431a2d [wangfei] fix conflicts
c35fe5e [wangfei] minor fix
01dab3a [wangfei] fix test failure of SQLQuerySuite
Author: Reynold Xin <rxin@databricks.com>
Closes#4379 from rxin/CachedTableSuite and squashes the following commits:
f2b44ce [Reynold Xin] [SQL] Fix flaky CachedTableSuite.
...aised in SPARK-4520.
The exception is thrown only for a thrift generated parquet file. The array element schema name is assumed as "array" as per ParquetAvro but for thrift generated parquet files, it is array_name + "_tuple". This leads to missing child of array group type and hence when the parquet rows are being materialized leads to the exception.
Author: Sadhan Sood <sadhan@tellapart.com>
Closes#4148 from sadhan/SPARK-4520 and squashes the following commits:
c5ccde8 [Sadhan Sood] [SPARK-4520] [SQL] This pr fixes the ArrayIndexOutOfBoundsException as raised in SPARK-4520.
Right now the PR adds few helper methods for java apis. But the issue was opened mainly to get rid of transformations in java api like `.rdd` and `.toJavaRDD` while working with `SQLContext` or `HiveContext`.
Author: kul <kuldeep.bora@gmail.com>
Closes#4243 from kul/master and squashes the following commits:
2390fba [kul] [SPARK-5426][SQL] Add SparkSQL Java API helper methods.
```scala
df.selectExpr("abs(colA)", "colB")
df.filter("age > 21")
```
Author: Reynold Xin <rxin@databricks.com>
Closes#4348 from rxin/SPARK-5579 and squashes the following commits:
2baeef2 [Reynold Xin] Fix Python.
b416372 [Reynold Xin] [SPARK-5579][SQL][DataFrame] Support for project/filter using SQL expressions.
The previous #3732 is reverted due to some test failure.
Have fixed that.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4325 from adrian-wang/datenative and squashes the following commits:
096e20d [Daoyuan Wang] fix for mixed timezone
0ed0fdc [Daoyuan Wang] fix test data
a2fdd4e [Daoyuan Wang] getDate
c37832b [Daoyuan Wang] row to catalyst
f0005b1 [Daoyuan Wang] add date in sql parser and java type conversion
024c9a6 [Daoyuan Wang] clean some import order
d6715fc [Daoyuan Wang] refactoring Date as Primitive Int internally
374abd5 [Daoyuan Wang] spark native date type support
This PR aims to support `INSERT INTO/OVERWRITE TABLE tableName` and `CREATE TABLE tableName AS SELECT` for the data source API (partitioned tables are not supported).
In this PR, I am also adding the support of `IF NOT EXISTS` for our ddl parser. The current semantic of `IF NOT EXISTS` is explained as follows.
* For a `CREATE TEMPORARY TABLE` statement, it does not `IF NOT EXISTS` for now.
* For a `CREATE TABLE` statement (we are creating a metastore table), if there is an existing table having the same name ...
* when `IF NOT EXISTS` clause is used, we will do nothing.
* when `IF NOT EXISTS` clause is not used, the user will see an exception saying the table already exists.
TODOs:
- [x] CTAS support
- [x] Programmatic APIs
- [ ] Python API (another PR)
- [x] More unit tests
- [ ] Documents (another PR)
marmbrus liancheng rxin
Author: Yin Huai <yhuai@databricks.com>
Closes#4294 from yhuai/writeSupport and squashes the following commits:
3db1539 [Yin Huai] save does not take overwrite.
1c98881 [Yin Huai] Fix test.
142372a [Yin Huai] Merge remote-tracking branch 'upstream/master' into writeSupport
34e1bfb [Yin Huai] Address comments.
1682ca6 [Yin Huai] Better support for CTAS statements.
e789d64 [Yin Huai] For the Scala API, let users to use tuples to provide options.
0128065 [Yin Huai] Short hand versions of save and load.
66ebd74 [Yin Huai] Formatting.
9203ec2 [Yin Huai] Merge remote-tracking branch 'upstream/master' into writeSupport
e5d29f2 [Yin Huai] Programmatic APIs.
1a719a5 [Yin Huai] CREATE TEMPORARY TABLE with IF NOT EXISTS is not allowed for now.
909924f [Yin Huai] Add saveAsTable for the data source API to DataFrame.
95a7c71 [Yin Huai] Fix bug when handling IF NOT EXISTS clause in a CREATE TEMPORARY TABLE statement.
d37b19c [Yin Huai] Cheng's comments.
fd6758c [Yin Huai] Use BeforeAndAfterAll.
7880891 [Yin Huai] Support CREATE TABLE AS SELECT STATEMENT and the IF NOT EXISTS clause.
cb85b05 [Yin Huai] Initial write support.
2f91354 [Yin Huai] Make INSERT OVERWRITE/INTO statements consistent between HiveQL and SqlParser.
This pull request contains a Spark SQL data source that can pull data from, and can put data into, a JDBC database.
I have tested both read and write support with H2, MySQL, and Postgres. It would surprise me if both read and write support worked flawlessly out-of-the-box for any other database; different databases have different names for different JDBC data types and different meanings for SQL types with the same name. However, this code is designed (see `DriverQuirks.scala`) to make it *relatively* painless to add support for another database by augmenting the type mapping contained in this PR.
Author: Tor Myklebust <tmyklebu@gmail.com>
Closes#4261 from tmyklebu/master and squashes the following commits:
cf167ce [Tor Myklebust] Work around other Java tests ruining TestSQLContext.
67893bf [Tor Myklebust] Move the jdbcRDD methods into SQLContext itself.
585f95b [Tor Myklebust] Dependencies go into the project's pom.xml.
829d5ba [Tor Myklebust] Merge branch 'master' of https://github.com/apache/spark
41647ef [Tor Myklebust] Hide a couple things that don't need to be public.
7318aea [Tor Myklebust] Fix scalastyle warnings.
a09eeac [Tor Myklebust] JDBC data source for Spark SQL.
176bb98 [Tor Myklebust] Add test deps for JDBC support.
1. Throw UnsupportedOperationException if a Column is not computable.
2. Perform eager analysis on DataFrame so we can catch errors when they happen (not when an action is run).
Author: Reynold Xin <rxin@databricks.com>
Author: Davies Liu <davies@databricks.com>
Closes#4296 from rxin/col-computability and squashes the following commits:
6527b86 [Reynold Xin] Merge pull request #8 from davies/col-computability
fd92bc7 [Reynold Xin] Merge branch 'master' into col-computability
f79034c [Davies Liu] fix python tests
5afe1ff [Reynold Xin] Fix scala test.
17f6bae [Reynold Xin] Various fixes.
b932e86 [Reynold Xin] Added eager analysis for error reporting.
e6f00b8 [Reynold Xin] [SQL][API] ComputableColumn vs IncomputableColumn
Store daysSinceEpoch as an Int value(4 bytes) to represent DateType, instead of using java.sql.Date(8 bytes as Long) in catalyst row. This ensures the same comparison behavior of Hive and Catalyst.
Subsumes #3381
I thinks there are already some tests in JavaSQLSuite, and for python it will not affect python's datetime class.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3732 from adrian-wang/datenative and squashes the following commits:
0ed0fdc [Daoyuan Wang] fix test data
a2fdd4e [Daoyuan Wang] getDate
c37832b [Daoyuan Wang] row to catalyst
f0005b1 [Daoyuan Wang] add date in sql parser and java type conversion
024c9a6 [Daoyuan Wang] clean some import order
d6715fc [Daoyuan Wang] refactoring Date as Primitive Int internally
374abd5 [Daoyuan Wang] spark native date type support
I'll add test case in #4040
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4057 from adrian-wang/coal and squashes the following commits:
4d0111a [Daoyuan Wang] address Yin's comments
c393e18 [Daoyuan Wang] fix rebase conflicts
e47c03a [Daoyuan Wang] add coalesce in parser
c74828d [Daoyuan Wang] cast types for coalesce
Support `comment` in create a table field.
__CREATE TEMPORARY TABLE people(name string `comment` "the name of a person")__
Author: OopsOutOfMemory <victorshengli@126.com>
Closes#3999 from OopsOutOfMemory/meta_comment and squashes the following commits:
39150d4 [OopsOutOfMemory] add comment and refine test suite
This PR makes Star a trait, and provides two implementations: UnresolvedStar (used for *, tblName.*) and ResolvedStar (used for df("*")).
Author: Reynold Xin <rxin@databricks.com>
Closes#4283 from rxin/df-star and squashes the following commits:
c9cba3e [Reynold Xin] Removed mapFunction in UnresolvedStar.
1a3a1d7 [Reynold Xin] [SQL] Support df("*") to select all columns in a data frame.
This patch changes DataFrame's `apply()` method to use an analyzed query plan when resolving column names. This fixes a bug where `apply` would throw "invalid call to qualifiers on unresolved object" errors when called on DataFrames constructed via `SQLContext.sql()`.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#4282 from JoshRosen/SPARK-5462 and squashes the following commits:
b9e6da2 [Josh Rosen] [SPARK-5462] Use analyzed query plan in DataFrame.apply().
1. Added Dsl.column in case Dsl.col is shadowed.
2. Allow using String to specify the target data type in cast.
3. Support sorting on multiple columns using column names.
4. Added Java API test file.
Author: Reynold Xin <rxin@databricks.com>
Closes#4280 from rxin/dsl1 and squashes the following commits:
33ecb7a [Reynold Xin] Add the Java test.
d06540a [Reynold Xin] [SQL] DataFrame API improvements.
`select key, count( * ) from src group by key, 1` will get the wrong answer.
e.g. for this table
```
val testData2 =
TestSQLContext.sparkContext.parallelize(
TestData2(1, 1) ::
TestData2(1, 2) ::
TestData2(2, 1) ::
TestData2(2, 2) ::
TestData2(3, 1) ::
TestData2(3, 2) :: Nil, 2).toSchemaRDD
testData2.registerTempTable("testData2")
```
result of `SELECT a, count(1) FROM testData2 GROUP BY a, 1` is
```
[1,1]
[2,2]
[3,1]
```
Author: wangfei <wangfei1@huawei.com>
Closes#4169 from scwf/agg-bug and squashes the following commits:
05751db [wangfei] fix bugs when literal in agg grouping expressioons
Enable parquet filter pushdown of castable types like short, byte that can be cast to integer
Author: Yash Datta <Yash.Datta@guavus.com>
Closes#4156 from saucam/filter_short and squashes the following commits:
a403979 [Yash Datta] SPARK-4786: Fix styling issues
d029866 [Yash Datta] SPARK-4786: Add test case
cb2e0d9 [Yash Datta] SPARK-4786: Parquet filter pushdown for castable types
...gs.
Parquet Converters allow developers to take advantage of dictionary encoding of column data to reduce Column Binary decoding.
The Spark PrimitiveConverter was not using that API and consequently for String columns that used dictionary compression repeated Binary to String conversions for the same String.
In measurements this could account for over 25% of entire query time.
For example a 500M row table split across 16 blocks was aggregated and summed in a litte under 30s before this change and a little under 20s after the change.
Author: Michael Davies <Michael.BellDavies@gmail.com>
Closes#4187 from MickDavies/SPARK-5309-2 and squashes the following commits:
327287e [Michael Davies] SPARK-5309: Add support for dictionaries in PrimitiveConverter for Strings.
33c002c [Michael Davies] SPARK-5309: Add support for dictionaries in PrimitiveConverter for Strings.
Turns out Scala does generate static methods for ones defined in a companion object. Finally no need to separate api.java.dsl and api.scala.dsl.
Author: Reynold Xin <rxin@databricks.com>
Closes#4276 from rxin/dsl and squashes the following commits:
30aa611 [Reynold Xin] Add all files.
1a9d215 [Reynold Xin] [SPARK-5445][SQL] Consolidate Java and Scala DSL static methods.
Also removed the literal implicit transformation since it is pretty scary for API design. Instead, created a new lit method for creating literals. This doesn't break anything from a compatibility perspective because Literal was added two days ago.
Author: Reynold Xin <rxin@databricks.com>
Closes#4241 from rxin/df-docupdate and squashes the following commits:
c0f4810 [Reynold Xin] Fix Python merge conflict.
094c7d7 [Reynold Xin] Minor style fix. Reset Python tests.
3c89f4a [Reynold Xin] Package.
dfe6962 [Reynold Xin] Updated Python aggregate.
5dd4265 [Reynold Xin] Made dsl Java callable.
14b3c27 [Reynold Xin] Fix literal expression for symbols.
68b31cb [Reynold Xin] Literal.
4cfeb78 [Reynold Xin] [SPARK-5097][SQL] Address DataFrame code review feedback.
and
[SPARK-5448][SQL] Make CacheManager a concrete class and field in SQLContext
Author: Reynold Xin <rxin@databricks.com>
Closes#4242 from rxin/sqlCleanup and squashes the following commits:
e351cb2 [Reynold Xin] Fixed toDataFrame.
6545c42 [Reynold Xin] More changes.
728c017 [Reynold Xin] [SPARK-5447][SQL] Replaced reference to SchemaRDD with DataFrame.
Author: Reynold Xin <rxin@databricks.com>
Closes#4235 from rxin/df-tests1 and squashes the following commits:
f341db6 [Reynold Xin] [SPARK-5097][SQL] Test cases for DataFrame expressions.
This PR removes the deprecated `ParquetQuerySuite`, renamed `ParquetQuerySuite2` to `ParquetQuerySuite`, and refactored changes introduced in #4115 to `ParquetFilterSuite` . It is a follow-up of #3644.
Notice that test cases in the old `ParquetQuerySuite` have already been well covered by other test suites introduced in #3644.
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4116)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#4116 from liancheng/remove-deprecated-parquet-tests and squashes the following commits:
f73b8f9 [Cheng Lian] Removes deprecated Parquet test suite
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4040 from adrian-wang/coalesce and squashes the following commits:
0ac8e8f [Daoyuan Wang] add coalesce() in sql parser
JIRA: https://issues.apache.org/jira/browse/SPARK-5287
This PR only add `defaultSizeOf` to data types and make those internal type classes `protected[sql]`. I will use another PR to cleanup the type hierarchy of data types.
Author: Yin Huai <yhuai@databricks.com>
Closes#4081 from yhuai/SPARK-5287 and squashes the following commits:
90cec75 [Yin Huai] Update unit test.
e1c600c [Yin Huai] Make internal classes protected[sql].
7eaba68 [Yin Huai] Add `defaultSize` method to data types.
fd425e0 [Yin Huai] Add all native types to NativeType.defaultSizeOf.
Author: Reynold Xin <rxin@databricks.com>
Closes#4092 from rxin/bigdecimal and squashes the following commits:
27b08c9 [Reynold Xin] Fixed test.
10cb496 [Reynold Xin] [SPARK-5279][SQL] Use java.math.BigDecimal as the exposed Decimal type.
As part of SPARK-5193:
1. Removed UDFRegistration as a mixin in SQLContext and made it a field ("udf").
2. For Java UDFs, renamed dataType to returnType.
3. For Scala UDFs, added type tags.
4. Added all Java UDF registration methods to Scala's UDFRegistration.
5. Documentation
Author: Reynold Xin <rxin@databricks.com>
Closes#4056 from rxin/udf-registration and squashes the following commits:
ae9c556 [Reynold Xin] Updated example.
675a3c9 [Reynold Xin] Style fix
47c24ff [Reynold Xin] Python fix.
5f00c45 [Reynold Xin] Restore data type position in java udf and added typetags.
032f006 [Reynold Xin] [SPARK-5193][SQL] Reconcile Java and Scala UDFRegistration.
1. Removed 2 implicits (logicalPlanToSparkQuery and baseRelationToSchemaRDD)
2. Moved extraStrategies into ExperimentalMethods.
3. Made private methods protected[sql] so they don't show up in javadocs.
4. Removed createParquetFile.
5. Added Java version of applySchema to SQLContext.
Author: Reynold Xin <rxin@databricks.com>
Closes#4049 from rxin/sqlContext-refactor and squashes the following commits:
a326a1a [Reynold Xin] Remove createParquetFile and add applySchema for Java to SQLContext.
ecd6685 [Reynold Xin] Added baseRelationToSchemaRDD back.
4a38c9b [Reynold Xin] [SPARK-5193][SQL] Tighten up SQLContext API
rxin follow up of #3732
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4041 from adrian-wang/decimal and squashes the following commits:
aa3d738 [Daoyuan Wang] fix auto refactor
7777a58 [Daoyuan Wang] move sql.types.decimal.Decimal to sql.types.Decimal
Having two versions of the data type APIs (one for Java, one for Scala) requires downstream libraries to also have two versions of the APIs if the library wants to support both Java and Scala. I took a look at the Scala version of the data type APIs - it can actually work out pretty well for Java out of the box.
As part of the PR, I created a sql.types package and moved all type definitions there. I then removed the Java specific data type API along with a lot of the conversion code.
This subsumes https://github.com/apache/spark/pull/3925
Author: Reynold Xin <rxin@databricks.com>
Closes#3958 from rxin/SPARK-5123-datatype-2 and squashes the following commits:
66505cc [Reynold Xin] [SPARK-5123] Expose only one version of the data type APIs (i.e. remove the Java-specific API).
This change should be binary and source backward compatible since we didn't change any user facing APIs.
Author: Reynold Xin <rxin@databricks.com>
Closes#3965 from rxin/SPARK-5168-sqlconf and squashes the following commits:
42eec09 [Reynold Xin] Fix default conf value.
0ef86cc [Reynold Xin] Fix constructor ordering.
4d7f910 [Reynold Xin] Properly override config.
ccc8e6a [Reynold Xin] [SPARK-5168] Make SQLConf a field rather than mixin in SQLContext
With changes in this PR, users can persist metadata of tables created based on the data source API in metastore through DDLs.
Author: Yin Huai <yhuai@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#3960 from yhuai/persistantTablesWithSchema2 and squashes the following commits:
069c235 [Yin Huai] Make exception messages user friendly.
c07cbc6 [Yin Huai] Get the location of test file in a correct way.
4456e98 [Yin Huai] Test data.
5315dfc [Yin Huai] rxin's comments.
7fc4b56 [Yin Huai] Add DDLStrategy and HiveDDLStrategy to plan DDLs based on the data source API.
aeaf4b3 [Yin Huai] Add comments.
06f9b0c [Yin Huai] Revert unnecessary changes.
feb88aa [Yin Huai] Merge remote-tracking branch 'apache/master' into persistantTablesWithSchema2
172db80 [Yin Huai] Fix unit test.
49bf1ac [Yin Huai] Unit tests.
8f8f1a1 [Yin Huai] [SPARK-4574][SQL] Adding support for defining schema in foreign DDL commands. #3431
f47fda1 [Yin Huai] Unit tests.
2b59723 [Michael Armbrust] Set external when creating tables
c00bb1b [Michael Armbrust] Don't use reflection to read options
1ea6e7b [Michael Armbrust] Don't fail when trying to uncache a table that doesn't exist
6edc710 [Michael Armbrust] Add tests.
d7da491 [Michael Armbrust] First draft of persistent tables.
Enable from follow multiple brackets:
```
select key from ((select * from testData limit 1) union all (select * from testData limit 1)) x limit 1
```
Author: scwf <wangfei1@huawei.com>
Closes#3853 from scwf/from and squashes the following commits:
14f110a [scwf] enable from follow multiple brackets
Adding support for defining schema in foreign DDL commands. Now foreign DDL support commands like:
```
CREATE TEMPORARY TABLE avroTable
USING org.apache.spark.sql.avro
OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")
```
With this PR user can define schema instead of infer from file, so support ddl command as follows:
```
CREATE TEMPORARY TABLE avroTable(a int, b string)
USING org.apache.spark.sql.avro
OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")
```
Author: scwf <wangfei1@huawei.com>
Author: Yin Huai <yhuai@databricks.com>
Author: Fei Wang <wangfei1@huawei.com>
Author: wangfei <wangfei1@huawei.com>
Closes#3431 from scwf/ddl and squashes the following commits:
7e79ce5 [Fei Wang] Merge pull request #22 from yhuai/pr3431yin
38f634e [Yin Huai] Remove Option from createRelation.
65e9c73 [Yin Huai] Revert all changes since applying a given schema has not been testd.
a852b10 [scwf] remove cleanIdentifier
f336a16 [Fei Wang] Merge pull request #21 from yhuai/pr3431yin
baf79b5 [Yin Huai] Test special characters quoted by backticks.
50a03b0 [Yin Huai] Use JsonRDD.nullTypeToStringType to convert NullType to StringType.
1eeb769 [Fei Wang] Merge pull request #20 from yhuai/pr3431yin
f5c22b0 [Yin Huai] Refactor code and update test cases.
f1cffe4 [Yin Huai] Revert "minor refactory"
b621c8f [scwf] minor refactory
d02547f [scwf] fix HiveCompatibilitySuite test failure
8dfbf7a [scwf] more tests for complex data type
ddab984 [Fei Wang] Merge pull request #19 from yhuai/pr3431yin
91ad91b [Yin Huai] Parse data types in DDLParser.
cf982d2 [scwf] fixed test failure
445b57b [scwf] address comments
02a662c [scwf] style issue
44eb70c [scwf] fix decimal parser issue
83b6fc3 [scwf] minor fix
9bf12f8 [wangfei] adding test case
7787ec7 [wangfei] added SchemaRelationProvider
0ba70df [wangfei] draft version
The pull only fixes the parsing error and changes API to use tableIdentifier. Joining different catalog datasource related change is not done in this pull.
Author: Alex Liu <alex_liu68@yahoo.com>
Closes#3941 from alexliu68/SPARK-SQL-4943-3 and squashes the following commits:
343ae27 [Alex Liu] [SPARK-4943][SQL] refactoring according to review
29e5e55 [Alex Liu] [SPARK-4943][SQL] fix failed Hive CTAS tests
6ae77ce [Alex Liu] [SPARK-4943][SQL] fix TestHive matching error
3652997 [Alex Liu] [SPARK-4943][SQL] Allow table name having dot to support db/catalog ...
Author: Reynold Xin <rxin@databricks.com>
Closes#3862 from rxin/stringcontext-attr and squashes the following commits:
9b10f57 [Reynold Xin] Rename StrongToAttributeConversionHelper
72121af [Reynold Xin] [SPARK-5040][SQL] Support expressing unresolved attributes using $"attribute name" notation in SQL DSL.
