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
