### What changes were proposed in this pull request?
This PR proposes to refine the code examples for pandas-on-Spark since some of them still follows the naming for Koalas.
For example,
```python
kdf = ks.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
```
should be refined to
```python
psdf = ps.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
```
Also fixed the several remaining Koalas stuffs in FAQ
### Why are the changes needed?
Because we don't want to use the name "Koalas" in the Apache Spark anymore.
### Does this PR introduce _any_ user-facing change?
Yes, the examples in the documentation will be changed with refined names.
### How was this patch tested?
Manually built the docs and check one by one.
Closes#33017 from itholic/SPARK-35696.
Authored-by: itholic <haejoon.lee@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
We use `DateAdd` to impl `DateType` `+`/`-` `INTERVAL DAY`
### Why are the changes needed?
To improve the impl of `DateType` `+`/`-` `INTERVAL DAY`
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Add ut test
Closes#33033 from Peng-Lei/SPARK-35852.
Authored-by: PengLei <18066542445@189.cn>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
This PR aims to add `fs.s3a.downgrade.syncable.exceptions=true` if it's not provided by the users.
### Why are the changes needed?
Currently, event log feature is broken with Hadoop 3.2 profile due to `UnsupportedOperationException` because [HADOOP-17597](https://issues.apache.org/jira/browse/HADOOP-17597) changes the default behavior to throw exceptions by default since Apache Hadoop 3.3.1. We know that it's because `EventLogFileWriters` is using `hadoopDataStream.foreach(_.hflush())`, but this PR aims to provide the same UX across Spark distributions with Hadoop2/Hadoop 3 at Apache Spark 3.2.0.
```
$ bin/spark-shell -c spark.eventLog.enabled=true -c spark.eventLog.dir=s3a://dongjoon/spark-events/
...
21/06/23 17:34:35 ERROR SparkContext: Error initializing SparkContext.
java.lang.UnsupportedOperationException: S3A streams are not Syncable. See HADOOP-17597.
```
### Does this PR introduce _any_ user-facing change?
Yes, this will recover the existing behavior.
### How was this patch tested?
Manual.
```
$ build/sbt package -Phadoop-3.2 -Phadoop-cloud
$ bin/spark-shell -c spark.eventLog.enabled=true -c spark.eventLog.dir=s3a://dongjoon/spark-events/
...(working)...
```
If the users provide the configuration explicitly, it will return to the original behavior throwing exceptions.
```
$ bin/spark-shell -c spark.eventLog.enabled=true -c spark.eventLog.dir=s3a://dongjoon/spark-events/ -c spark.hadoop.fs.s3a.downgrade.syncable.exceptions=false
...
21/06/23 17:44:41 ERROR Main: Failed to initialize Spark session.
java.lang.UnsupportedOperationException: S3A streams are not Syncable. See HADOOP-17597.
```
Closes#33044 from dongjoon-hyun/SPARK-35868.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
revert changes related to ANN
### Why are the changes needed?
using the new `softmax` may cause flaky failure
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
reverted testsuite
Closes#33049 from zhengruifeng/revert_softmax_ann.
Authored-by: Ruifeng Zheng <ruifengz@foxmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Wrapping `JHashMap[BlockId, BlockStatus]` (used in `blockStatusByShuffleService`) into a new class `BlockStatusPerBlockId` which removes the reference to the map when all the persisted blocks are removed.
### Why are the changes needed?
With https://github.com/apache/spark/pull/32790 a bug is introduced when all the persisted blocks are removed we remove the HashMap which already shared by the block manger infos but when new block is persisted this map is needed to be used again for storing the data (and this HashMap must be the same which shared by the block manger infos created for registered block managers running on the same host where the external shuffle service is).
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Extending `BlockManagerInfoSuite` with test which removes all the persisted blocks then adds another one.
Closes#33020 from attilapiros/SPARK-35543-2.
Authored-by: attilapiros <piros.attila.zsolt@gmail.com>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
Add `python-is-python3` to `create-release/spark-rm/Dockerfile`
### Why are the changes needed?
Systems that use pthon3 by default should explicitly indicate the python version is 3.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Tested during Apache 3.0.3 release.
Closes#33048 from Ngone51/fix-release-script.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Extend the `TransposeWindow` rule to transpose `Window` nodes, that have `Project` between them.
### Why are the changes needed?
The analyzer will turn a `dataset.withColumn("colName", expressionWithWindowFunction)` method call to a `Project - Window - Project` chain in the logical plan. When this method is called multiple times in a row, then the projects can block the `Window` nodes from being transposed by the current `TransposeWindow` rule.
TPCDS q47 and q57 are also improved by this.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
UT
Closes#31980 from tanelk/SPARK-34807_transpose_window.
Lead-authored-by: tanel.kiis@gmail.com <tanel.kiis@gmail.com>
Co-authored-by: Tanel Kiis <tanel.kiis@gmail.com>
Signed-off-by: Yuming Wang <yumwang@ebay.com>
### What changes were proposed in this pull request?
softmax support offset and step, then we can use it in ANN and NB
### Why are the changes needed?
to simplify impl
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
existing testsuite
Closes#32991 from zhengruifeng/softmax_support_offset_step.
Authored-by: Ruifeng Zheng <ruifengz@foxmail.com>
Signed-off-by: Huaxin Gao <huaxin_gao@apple.com>
### What changes were proposed in this pull request?
This PR proposes to fix:
- the Binder integration of pandas API on Spark, and merge them together with the existing PySpark one.
- update quickstart of pandas API on Spark, and make it working
The notebooks can be easily reviewed here:
https://mybinder.org/v2/gh/HyukjinKwon/spark/SPARK-35588-3?filepath=python%2Fdocs%2Fsource%2Fgetting_started%2Fquickstart_ps.ipynb
Original page in Koalas: https://koalas.readthedocs.io/en/latest/getting_started/10min.html
### Why are the changes needed?
- To show the working examples of quickstart to end users.
- To allow users to try out the examples without installation easily.
### Does this PR introduce _any_ user-facing change?
No to end users because the existing quickstart of pandas API on Spark is not released yet.
### How was this patch tested?
I manually tested it by uploading built Spark distribution to Binder. See 3bc15310a0Closes#33041 from HyukjinKwon/SPARK-35588-2.
Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
modify the wrong variable used in GraphGenerators.sampleLogNormal
### Why are the changes needed?
wrong variable used
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
UT
Closes#33010 from zengruios/SPARK-35851.
Authored-by: zengruios <578395184@qq.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Check all day-time interval types in arrow.
### Why are the changes needed?
To improve test coverage.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Added UT.
Closes#33039 from AngersZhuuuu/SPARK-35731.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
This PR adds test to check `sum` and `avg` works with all the `DayTimeIntervalType`.
This PR also moves a dataframe commonly used by tests `SPARK-34837: Support ANSI SQL intervals by the aggregate function avg` and `SPARK-34716: Support ANSI SQL intervals by the aggregate function sum` to `SQLTestData.scala`, and a little bit modifies it.
### Why are the changes needed?
To ensure the results of aggregations are what is expected.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
New test.
Closes#33042 from sarutak/check-interval-agg-dt.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
Introduction: this PR is a part of SPARK-10816 (`EventTime based sessionization (session window)`). Please refer #31937 to see the overall view of the code change. (Note that code diff could be diverged a bit.)
### What changes were proposed in this pull request?
This PR introduces MergingSessionsIterator, which enables to merge elements belong to the same session directly.
MergingSessionsIterator is a variant of SortAggregateIterator which merges the session windows based on the fact input rows are sorted by "group keys + the start time of session window". When merging windows, MergingSessionsIterator also applies aggregations on merged window, which eliminates the necessity on buffering inputs (which requires copying rows) and update the session spec for each input.
MergingSessionsIterator is quite performant compared to UpdatingSessionsIterator brought by SPARK-34888. Note that MergingSessionsIterator can only apply to the cases aggregation can be applied altogether, so there're still rooms for UpdatingSessionIterator to be used.
This issue also introduces MergingSessionsExec which is the physical node on leveraging MergingSessionsIterator to sort the input rows and aggregate rows according to the session windows.
### Why are the changes needed?
This part is a one of required on implementing SPARK-10816.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
New test suite added.
Closes#31987 from HeartSaVioR/SPARK-34889-SPARK-10816-PR-31570-part-2.
Lead-authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Co-authored-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
### What changes were proposed in this pull request?
Check all day-time interval types in HiveInspectors tests.
### Why are the changes needed?
New tests should improve test coverage for day-time interval types.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Added UT.
Closes#33036 from AngersZhuuuu/SPARK-35733.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
When creating a record writer in an AvroDeserializer, or creating a struct converter in an AvroSerializer, look up Avro fields using a map rather than scanning the entire list of Avro fields.
### Why are the changes needed?
A query against an Avro table can be quite slow when all are true:
* There are many columns in the Avro file
* The query contains a wide projection
* There are many splits in the input
* Some of the splits are read serially (e.g., less executors than there are tasks)
A write to an Avro table can be quite slow when all are true:
* There are many columns in the new rows
* The operation is creating many files
For example, a single-threaded query against a 6000 column Avro data set with 50K rows and 20 files takes less than a minute with Spark 3.0.1 but over 7 minutes with Spark 3.2.0-SNAPSHOT.
This PR restores the faster time.
For the 1000 column read benchmark:
Before patch: 108447 ms
After patch: 35925 ms
percent improvement: 66%
For the 1000 column write benchmark:
Before patch: 123307
After patch: 42313
percent improvement: 65%
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
* Ran existing unit tests
* Added new unit tests
* Added new benchmarks
Closes#32969 from bersprockets/SPARK-35817.
Authored-by: Bruce Robbins <bersprockets@gmail.com>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
This's a follow-up of https://github.com/apache/spark/pull/30710.
Rename the conf from `spark.speculation.min.threshold` to `spark.speculation.minTaskRuntime`.
### Why are the changes needed?
To follow the [config naming policy](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/internal/config/ConfigEntry.scala#L21).
### Does this PR introduce _any_ user-facing change?
No (since Spark 3.2 hasn't been released).
### How was this patch tested?
Pass existing tests.
Closes#33037 from Ngone51/spark-33741-followup.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Throw ValueError if version and timestamp are used together in to_delta
### Why are the changes needed?
read_delta has arguments named `version` and `timestamp`, but they cannot be used together.
We should raise the proper error message when they are used together.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
UT
Closes#33023 from Yikun/SPARK-35812.
Authored-by: Yikun Jiang <yikunkero@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Move all the bookkeeping states while scanning a Parquet column chunk into a single class `ParquetReadState`.
### Why are the changes needed?
As suggested [here](https://github.com/apache/spark/pull/32753#discussion_r655580942). To support column index in the vectorized reader path, we'll going to introduce more states to track. These are spread across different classes which make the code harder to maintain. Therefore, this proposes to move them into a single class so they can be managed better.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing UTs.
Closes#33006 from sunchao/SPARK-35846.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Make the ANSI flag part of expression `Cast`'s parameter list, instead of fetching it from the sessional SQLConf.
### Why are the changes needed?
For Views, it is important to show consistent results even the ANSI configuration is different in the running session. This is why many expressions like 'Add'/'Divide' making the ANSI flag part of its case class parameter list.
We should make it consistent for the expression `Cast`
### Does this PR introduce _any_ user-facing change?
Yes, the `Cast` inside a View always behaves the same, independent of the ANSI model SQL configuration in the current session.
### How was this patch tested?
Existing UT
Closes#33027 from gengliangwang/ansiFlagInCast.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
Support UpCast between different field of YearMonthIntervalType/DayTimeIntervalType
### Why are the changes needed?
Since in our encoder we handle Period/Duration as default YearMonthIntervalType/DayTimeIntervalType, when we use udf to handle this type, it will upcast all type of YearMonthIntervalType/DayTimeIntervalType to default YearMonthIntervalType/DayTimeIntervalType, so we need to support this.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added Ut
Closes#33035 from AngersZhuuuu/SPARK-35860.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
Add tests to check that all year-month interval types are supported in (de-)serialization from/to Arrow format.
### Why are the changes needed?
New tests should improve test coverage.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
added ut
Closes#32993 from AngersZhuuuu/SPARK-35776.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
This PR unifies reuse map data structures in non-AQE and AQE rules to a simple `Map[<canonicalized plan>, <plan>]` based on the discussion here: https://github.com/apache/spark/pull/28885#discussion_r655073897
### Why are the changes needed?
The proposed `Map[<canonicalized plan>, <plan>]` is simpler than the currently used `Map[<schema>, ArrayBuffer[<plan>]]` in `ReuseMap`/`ReuseExchangeAndSubquery` (non-AQE) and consistent with the `ReuseAdaptiveSubquery` (AQE) subquery reuse rule.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing UTs.
Closes#33021 from peter-toth/SPARK-35855-unify-reuse-map-data-structures.
Authored-by: Peter Toth <peter.toth@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
The current OuterReference resolution is a bit weird: when the outer plan has more than one child, it resolves OuterReference from the output of each child, one by one, left to right.
This is incorrect in the case of join, as the column name can be ambiguous if both left and right sides output this column.
This PR fixes this bug by resolving OuterReference with `outerPlan.resolveChildren`, instead of something like `outerPlan.children.foreach(_.resolve(...))`
### Why are the changes needed?
bug fix
### Does this PR introduce _any_ user-facing change?
The problem only occurs in join, and join condition doesn't support correlated subquery yet. So this PR only improves the error message. Before this PR, people see
```
java.lang.UnsupportedOperationException
Cannot generate code for expression: outer(t1a#291)
```
### How was this patch tested?
a new test
Closes#33004 from cloud-fan/outer-ref.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
Check all year-month interval types in HiveInspectors tests.
### Why are the changes needed?
To improve test coverage.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added UT.
Closes#32970 from AngersZhuuuu/SPARK-35772.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
This PR fixes an issue that `IntervalUtils.toDayTimeIntervalString` doesn't consider the case that a day-time interval type is casted as another day-time interval type.
if data of `interval day to second` is casted as `interval hour to second`, the value of the day is multiplied by 24 and added to the value of hour. For example, `INTERVAL '1 2' DAY TO HOUR` will be `INTERVAL '26' HOUR` if it's casted.
If this behavior is intended, it should be stringified as `INTERVAL '26' HOUR` but currently, it will be `INTERVAL '2' HOUR`
### Why are the changes needed?
t's a bug if the behavior of cast is intended.
### Does this PR introduce _any_ user-facing change?
No, because this feature is not released yet.
### How was this patch tested?
Modified the tests added in SPARK-35734 (#32891)
Closes#33031 from sarutak/fix-toDayTimeIntervalString.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
There are a few test cases that are supposed to be in CastSuiteBase instead of CastSuite:
- SPARK-35112: Cast string to day-time interval
- SPARK-35111: Cast string to year-month interval
- SPARK-35820: Support cast DayTimeIntervalType in different fields
- SPARK-35819: Support cast YearMonthIntervalType in different fields
This PR is to move them to CastSuiteBase. Also, it adds comments for the scope of CastSuiteBase/CastSuite/AnsiCastSuiteBase.
### Why are the changes needed?
Increase test coverage so that we can test the casting under ANSI mode.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing UT
Closes#33022 from gengliangwang/moveTest.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
This is a followup of https://github.com/apache/spark/pull/32862 , to simplify the code with AQE helper.
### Why are the changes needed?
code cleanup
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
existing tests
Closes#33026 from cloud-fan/follow.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Adds more type annotations in the file `python/pyspark/pandas/groupby.py` and fixes the mypy check failures.
### Why are the changes needed?
We should enable more disallow_untyped_defs mypy checks.
### Does this PR introduce _any_ user-facing change?
Yes.
This PR adds more type annotations in pandas APIs on Spark module, which can impact interaction with development tools for users.
### How was this patch tested?
The mypy check with a new configuration and existing tests should pass.
Closes#33032 from ueshin/issues/SPARK-35473/disallow_untyped_defs_groupby.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
We introduced `SparkSession.withActive` a while ago, and we use it when we need to run some code with a certain SparkSession as the active session.
Somehow we missed `SparkPlan.makeCopy`, which sets active session directly. This PR proposes to call `SparkSession.withActive` there.
### Why are the changes needed?
make sure we don't change the active session unexpectedly.
### Does this PR introduce _any_ user-facing change?
No. `makeCopy` is an internal function and I can't find a real case that this can change the active session. Mostly in an upper level, there is already a `SparkSession.withActive`, like `QueryExecution.executePhase`
### How was this patch tested?
existing tests
Closes#33029 from cloud-fan/minor1.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This is a followup of https://github.com/apache/spark/pull/33001 , to provide a more direct fix.
The regression in 3.1 was caused by the fact that we changed the parser and allow the parser to return CHAR/VARCHAR type. We should have replaced CHAR/VARCHAR with STRING before the data type flows into the query engine, however, `OrcUtils` is missed.
When reading ORC files, at the task side we will read the real schema from ORC file metadata, then apply filter pushdown. For some reason, the implementation turns ORC schema to Spark schema before filter pushdown, and this step does not strip CHAR/VARCHAR. Note, for Parquet we use the Parquet schema directly in filter pushdown, and do not this have problem.
This PR proposes to replace the CHAR/VARCHAR with STRING when turning ORC schema to Spark schema.
### Why are the changes needed?
a more directly bug fix
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
existing tests
Closes#33030 from cloud-fan/help.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Properly set `InternalField` for `DataTypeOps.isnull`.
### Why are the changes needed?
The result of `DataTypeOps.isnull` must always be non-nullable boolean.
We should manage `InternalField` for this case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Added some more tests.
Closes#33005 from ueshin/issues/SPARK-35847/isnull_field.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
### What changes were proposed in this pull request?
Proposed changes in this pull request:
1. Introducing the `TestGroupState` interface which is inherited from `GroupState` so that testing related getters can be exposed in a controlled manner
2. Changing `GroupStateImpl` to inherit from `TestGroupState` interface, instead of directly from `GroupState`
3. Implementing `TestGroupState` object with `create()` method to forward inputs to the private `GroupStateImpl` constructor
4. User input validations have been added into `GroupStateImpl`'s `createForStreaming()` method to prevent users from creating invalid GroupState objects.
5. Replacing existing `GroupStateImpl` usages in sql pkg internal unit tests with the newly added `TestGroupState` to give user best practice about `TestGroupState` usage.
With the changes in this PR, the class hierarchy is changed from `GroupStateImpl` -> `GroupState` to `GroupStateImpl` -> `TestGroupState` -> `GroupState` (-> means inherits from)
### Why are the changes needed?
The internal `GroupStateImpl` implementation for the `GroupState` interface has no public constructors accessible outside of the sql pkg. However, the user-provided state transition function for `[map|flatMap]GroupsWithState` requires a `GroupState` object as the prevState input.
Currently, users are calling the Structured Streaming engine in their unit tests in order to instantiate such `GroupState` instances, which makes UTs cumbersome.
The proposed `TestGroupState` interface is to give users controlled access to the `GroupStateImpl` internal implementation to largely improve testability of Structured Streaming state transition functions.
**Usage Example**
```
import org.apache.spark.sql.streaming.TestGroupState
test(“Structured Streaming state update function”) {
var prevState = TestGroupState.create[UserStatus](
optionalState = Optional.empty[UserStatus],
timeoutConf = EventTimeTimeout,
batchProcessingTimeMs = 1L,
eventTimeWatermarkMs = Optional.of(1L),
hasTimedOut = false)
val userId: String = ...
val actions: Iterator[UserAction] = ...
assert(!prevState.hasUpdated)
updateState(userId, actions, prevState)
assert(prevState.hasUpdated)
}
```
### Does this PR introduce _any_ user-facing change?
Yes, the `TestGroupState` interface and its corresponding `create()` factory function in its companion object are introduced in this pull request for users to use in unit tests.
### How was this patch tested?
- New unit tests are added
- Existing GroupState unit tests are updated
Closes#32938 from lizhangdatabricks/improve-group-state-testability.
Authored-by: Li Zhang <li.zhang@databricks.com>
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
### What changes were proposed in this pull request?
Make DecimalOps astype data-type-based.
See more in:
https://github.com/apache/spark/pull/32821#issuecomment-861119905
### Why are the changes needed?
Make DecimalOps astype data-type-based.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing test NumOpsTest.test_astype in pyspark/pandas/tests/data_type_ops/test_num_ops.py
Closes#33009 from Yikun/SPARK-35849.
Authored-by: Yikun Jiang <yikunkero@gmail.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
### What changes were proposed in this pull request?
This PR revise the installation to describe `pip install pyspark[pandas_on_spark]` and removes pandas-on-Spark installation and videos/blogposts.
### Why are the changes needed?
pandas-on-Spark installation is merged to PySpark installation pages. For videos/blogposts, now this is named pandas API on Spark. Old Koalas blogposts and videos are obsolete.
### Does this PR introduce _any_ user-facing change?
To end users, no because the docs are not released yet.
### How was this patch tested?
I manually built the docs and checked the output
Closes#33018 from HyukjinKwon/SPARK-35645.
Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
When SQL function `to_timestamp_ntz` has invalid format pattern input, throw a runtime exception with hints for the valid patterns, instead of throwing an upgrade exception with suggestions to use legacy formatters.
### Why are the changes needed?
As discussed in https://github.com/apache/spark/pull/32995/files#r655148980, there is an error message saying
"You may get a different result due to the upgrading of Spark 3.0: Fail to recognize 'yyyy-MM-dd GGGGG' pattern in the DateTimeFormatter. 1) You can set spark.sql.legacy.timeParserPolicy to LEGACY to restore the behavior before Spark 3.0"
This is not true for function to_timestamp_ntz, which only uses the Iso8601TimestampFormatter and added since Spark 3.2. We should improve it.
### Does this PR introduce _any_ user-facing change?
No, the new SQL function is not released yet.
### How was this patch tested?
Unit test
Closes#33019 from gengliangwang/improveError.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
What changes were proposed in this pull request?
1. Change the return value type from DayTimeIntervalType(DAY, SECOND) to DayTimeIntervalType(DAY, DAY) of SubtractDates.
Why are the changes needed?
https://issues.apache.org/jira/browse/SPARK-35727
Does this PR introduce any user-facing change?
no
How was this patch tested?
existed ut test
Closes#32999 from Peng-Lei/SPARK-35727.
Lead-authored-by: Lei Peng <peng.8lei@gmail.com>
Co-authored-by: PengLei <18066542445@189.cn>
Co-authored-by: Peng-Lei <peng.8lei@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Similar to SPARK-35532, the main change of this pr is add `scala-2.13` profile to external/kafka-0-10-sql/pom.xml, external/avro/pom.xml and sql/hive-thriftserver/pom.xml, the `scala-2.13` profile include dependency on `scala-parallel-collections_2.13`, then all(34) spark modules can maven test independently.
### Why are the changes needed?
Ensure alll(34) spark modules can be maven test independently in Scala 2.13
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- Pass the GitHub Action Scala 2.13 job
- Manual test：
1. Execute
```
dev/change-scala-version.sh 2.13
mvn clean install -DskipTests -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13
```
2. maven test `external/kafka-0-10-sql` module
```
mvn test -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13 -pl external/kafka-0-10-sql
```
**before**
```
Discovery starting.
Discovery completed in 857 milliseconds.
Run starting. Expected test count is: 464
...
KafkaRelationSuiteV2:
- explicit earliest to latest offsets
- default starting and ending offsets
- explicit offsets
- default starting and ending offsets with headers
- timestamp provided for starting and ending
- timestamp provided for starting, offset provided for ending
- timestamp provided for ending, offset provided for starting
- timestamp provided for starting, ending not provided
- timestamp provided for ending, starting not provided
- global timestamp provided for starting and ending
- no matched offset for timestamp - startingOffsets
- preferences on offset related options
- no matched offset for timestamp - endingOffsets
*** RUN ABORTED ***
java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport
at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:788)
at org.apache.spark.SparkContext.union(SparkContext.scala:1405)
at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:182)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:220)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:217)
...
Cause: java.lang.ClassNotFoundException: scala.collection.parallel.TaskSupport
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:788)
at org.apache.spark.SparkContext.union(SparkContext.scala:1405)
at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697)
...
```
**After**
```
Run completed in 33 minutes, 51 seconds.
Total number of tests run: 464
Suites: completed 31, aborted 0
Tests: succeeded 464, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
3. maven test `external/avro` module
```
mvn test -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13 -pl external/avro
```
**before**
```
Discovery starting.
Discovery completed in 2 seconds, 765 milliseconds.
Run starting. Expected test count is: 255
AvroReadSchemaSuite:
- append column at the end
- hide column at the end
- append column into middle
- hide column in the middle
- add a nested column at the end of the leaf struct column
- add a nested column in the middle of the leaf struct column
- add a nested column at the end of the middle struct column
- add a nested column in the middle of the middle struct column
- hide a nested column at the end of the leaf struct column
- hide a nested column in the middle of the leaf struct column
- hide a nested column at the end of the middle struct column
- hide a nested column in the middle of the middle struct column
*** RUN ABORTED ***
java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport
at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:788)
at org.apache.spark.SparkContext.union(SparkContext.scala:1405)
at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:182)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:220)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:217)
...
Cause: java.lang.ClassNotFoundException: scala.collection.parallel.TaskSupport
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:788)
at org.apache.spark.SparkContext.union(SparkContext.scala:1405)
at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697)
...
```
**After**
```
Run completed in 1 minute, 42 seconds.
Total number of tests run: 255
Suites: completed 12, aborted 0
Tests: succeeded 255, failed 0, canceled 0, ignored 2, pending 0
All tests passed.
```
4. maven test `sql/hive-thriftserver` module
```
mvn test -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13 -pl sql/hive-thriftserver
```
**before**
```
- union.sql *** FAILED ***
"1 a
1 a
2 b
2 b" did not contain "Exception" Exception did not match for query #2
SELECT *
FROM (SELECT * FROM t1
UNION ALL
SELECT * FROM t1), expected: 1 a
1 a
2 b
2 b, but got: java.sql.SQLException
org.apache.hive.service.cli.HiveSQLException: Error running query: java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport
at org.apache.spark.sql.hive.thriftserver.HiveThriftServerErrors$.runningQueryError(HiveThriftServerErrors.scala:38)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.org$apache$spark$sql$hive$thriftserver$SparkExecuteStatementOperation$$execute(SparkExecuteStatementOperation.scala:324)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.$anonfun$run$2(SparkExecuteStatementOperation.scala:229)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18)
at org.apache.spark.sql.hive.thriftserver.SparkOperation.withLocalProperties(SparkOperation.scala:79)
at org.apache.spark.sql.hive.thriftserver.SparkOperation.withLocalProperties$(SparkOperation.scala:63)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.withLocalProperties(SparkExecuteStatementOperation.scala:43)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.run(SparkExecuteStatementOperation.scala:229)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.run(SparkExecuteStatementOperation.scala:224)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1878)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2.run(SparkExecuteStatementOperation.scala:238)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport
at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:788)
at org.apache.spark.SparkContext.union(SparkContext.scala:1405)
at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:182)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:220)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:217)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:178)
at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:323)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:389)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3719)
at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2987)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3710)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:774)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3708)
at org.apache.spark.sql.Dataset.collect(Dataset.scala:2987)
at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.org$apache$spark$sql$hive$thriftserver$SparkExecuteStatementOperation$$execute(SparkExecuteStatementOperation.scala:299)
... 16 more
Caused by: java.lang.ClassNotFoundException: scala.collection.parallel.TaskSupport
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
... 40 more (ThriftServerQueryTestSuite.scala:209)
```
**After**
```
Run completed in 29 minutes, 17 seconds.
Total number of tests run: 535
Suites: completed 20, aborted 0
Tests: succeeded 535, failed 0, canceled 0, ignored 17, pending 0
All tests passed.
```
Closes#32994 from LuciferYang/SPARK-35838.
Authored-by: YangJie <yangjie01@baidu.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
When we call periodToMonths and durationToMicros with certain type field, we should pass endField parameter.
### Why are the changes needed?
When we call periodToMonths and durationToMicros with certain type field, we should pass endField parameter.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existed UT
Closes#32984 from AngersZhuuuu/SPARK-35726-35769.
Lead-authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Co-authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
#32513 added the case class `CommandResult` so as we can eagerly execute command locally. But we forgot to update
`isLocal` of `Dataset`.
### Why are the changes needed?
`Dataset.isLocal` should consider `CommandResult`.
### Does this PR introduce _any_ user-facing change?
Yes. If the SQL plan is `CommandResult`, `Dataset.isLocal` must return true.
### How was this patch tested?
No test.
Closes#32963 from beliefer/SPARK-35378-followup2.
Authored-by: gengjiaan <gengjiaan@360.cn>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Fix how we measure the metric `allUpdatesTimeMs` in `FlatMapGroupsWithStateExec` similar to other streaming stateful operators.
### Why are the changes needed?
Metric `allUpdatesTimeMs` meant to capture the start to end walltime of the operator `FlatMapGroupsWithStateExec`, but currently it just [captures](79362c4efc/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FlatMapGroupsWithStateExec.scala (L121)) the iterator creation time.
Fix it to measure similar to how other stateful operators measure. Example one [here](79362c4efc/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala (L406)). This measurement is not perfect due to the nature of the lazy iterator and also includes the time the consumer operator spent in processing the current operator output, but it should give a good signal when comparing the metric in one microbatch to the metric in another microbatch.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing UTs for regression. Due to the nature of metric type (time), it is hard to write a UT, but have manually verified.
Closes#32952 from vkorukanti/SPARK-35799.
Authored-by: Venki Korukanti <venki.korukanti@gmail.com>
Signed-off-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
This PR aims to upgrade the scala-maven-plugin version to 4.5.3.
### Why are the changes needed?
This will upgrade `sbt-compiler-bridge` from 1.3.1 to 1.5.5 in order to bring the latest bug fixes.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CIs.
Closes#33007 from williamhyun/scalamvnplugin.
Authored-by: William Hyun <william@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Adds more type annotations in the file `python/pyspark/pandas/base.py` and fixes the mypy check failures.
### Why are the changes needed?
We should enable more disallow_untyped_defs mypy checks.
### Does this PR introduce _any_ user-facing change?
Yes.
This PR adds more type annotations in pandas APIs on Spark module, which can impact interaction with development tools for users.
### How was this patch tested?
The mypy check with a new configuration and existing tests should pass.
Closes#32968 from ueshin/issues/SPARK-35470/disallow_untyped_defs_base.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
The char/varchar type should be mapped to orc's string type too, see https://orc.apache.org/docs/types.html
### Why are the changes needed?
fix a regression
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
new tests
Closes#33001 from yaooqinn/SPARK-35700.
Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Improve error message when clients use wrong master URL to submit a job to k8s.
### Why are the changes needed?
Current error messages are not clear for users.
```
(base) ➜ spark git:(master) ./bin/spark-submit \
--master k8s://https://192.168.49.3:8443 \
--name spark-pi \
--class org.apache.spark.examples.SparkPi \
--conf spark.executor.instances=3 \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
--conf spark.kubernetes.container.image=pingsutw/spark:testing \
local:///opt/spark/examples/jars/spark-examples_2.12-3.2.0-SNAPSHOT.jar
21/06/09 20:50:37 WARN Utils: Your hostname, kobe-pc resolves to a loopback address: 127.0.1.1; using 192.168.103.20 instead (on interface ens160)
21/06/09 20:50:37 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
21/06/09 20:50:38 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
21/06/09 20:50:38 INFO SparkKubernetesClientFactory: Auto-configuring K8S client using current context from users K8S config file
21/06/09 20:50:39 INFO KerberosConfDriverFeatureStep: You have not specified a krb5.conf file locally or via a ConfigMap. Make sure that you have the krb5.conf locally on the driver image.
Exception in thread "main" io.fabric8.kubernetes.client.KubernetesClientException: Operation: [create] for kind: [Pod] with name: [null] in namespace: [default] failed.
at io.fabric8.kubernetes.client.KubernetesClientException.launderThrowable(KubernetesClientException.java:64) at io.fabric8.kubernetes.client.KubernetesClientException.launderThrowable(KubernetesClientException.java:64)
at io.fabric8.kubernetes.client.KubernetesClientException.launderThrowable(KubernetesClientException.java:72) at io.fabric8.kubernetes.client.KubernetesClientException.launderThrowable(KubernetesClientException.java:72)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.create(BaseOperation.java:380) at io.fabric8.kubernetes.client.dsl.base.BaseOperation.create(BaseOperation.java:380)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.create(BaseOperation.java:86) at io.fabric8.kubernetes.client.dsl.base.BaseOperation.create(BaseOperation.java:86)
```
Below command to reproduce;
```
./bin/spark-submit \
--master k8s://https://192.168.49.2:8443 \
--deploy-mode cluster \
--name spark-pi \
--class org.apache.spark.examples.SparkPi \
--conf spark.executor.instances=3 \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
--conf spark.kubernetes.container.image=pingsutw/spark:testing \
local:///opt/spark/examples/jars/spark-examples_2.12-3.2.0-SNAPSHOT.jar
```
### Does this PR introduce _any_ user-facing change?
Yes, users will see more clear error messages.
### How was this patch tested?
Pass the CIs.
Closes#32874 from pingsutw/SPARK-35699.
Authored-by: Kevin Su <pingsutw@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Implement new SQL function: `to_timestamp_ntz`.
The syntax is similar to the built-in function `to_timestamp`:
```
to_timestamp_ntz ( <date_expr> )
to_timestamp_ntz ( <timestamp_expr> )
to_timestamp_ntz ( <string_expr> [ , <format> ] )
```
The naming is from snowflake: https://docs.snowflake.com/en/sql-reference/functions/to_timestamp.html
### Why are the changes needed?
Adds a new SQL function to create a literal/column of timestamp without time zone.
It's convenient for both end-users and developers.
### Does this PR introduce _any_ user-facing change?
Yes, a new SQL function `to_timestamp_ntz`.
### How was this patch tested?
Unit tests
Closes#32995 from gengliangwang/toTimestampNtz.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
We propose to
- introduce the Ops class for ExtensionDtypes: `IntegralExtensionOps`, `FractionalExtensionOps`, `StringExtensionOps`
- make the "conversion to pandas" data-type-based for ExtensionDtypes
Non-goal: same arithmetic operation of ExtensionDtypes have different result dtypes between pandas and pandas API on Spark. That should be adjusted in a separated PR if needed.
### Why are the changes needed?
The conversion to pandas includes logic for checking ExtensionDtypes data types and behaving accordingly.
That makes code hard to change or maintain.
Since we have DataTypeOps defined, we are able to dispatch the specific conversion logic to the `ExtensionOps` classes.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unit tests.
Closes#32910 from xinrong-databricks/datatypeops_pd_ext.
Authored-by: Xinrong Meng <xinrong.meng@databricks.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
### What changes were proposed in this pull request?
It is a trivial change to remove the reference to an incorrect configuration for push-based shuffle from a test suite.
Ref: https://github.com/apache/spark/pull/30312
With SPARK-32917, `ShuffleBlockPusher` and its test suite was introduced. `ShuffleBlockPusher` is created only when push-based shuffle is enabled and the tests in `ShuffleBlockPusherSuite` are just testing the functionality in the pusher. So there is no need to have these configs enabled in these test.
### Why are the changes needed?
This change removes an incorrect configuration from the test suite.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
This change just removes an incorrect configuration from the test suite so haven't added any UTs for it.
Closes#32992 from otterc/SPARK-35836.
Authored-by: Chandni Singh <singh.chandni@gmail.com>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
This PR aims to add `hadoop-cloud` profile to `PUBLISH_PROFILES` in order to publish `hadoop-cloud` module.
Note that this doesn't change `BASE_RELEASE_PROFILES` and there is no change in the binary distributions.
### Why are the changes needed?
This is discussed here.
- https://lists.apache.org/thread.html/rf87d755460d5ed85c7b6ac0edad48f53c929a2cd287f30be24afd2ad%40%3Cuser.spark.apache.org%3E
### Does this PR introduce _any_ user-facing change?
Yes, this will provide `hadoop-cloud` module in Maven Central.
### How was this patch tested?
N/A (After merging this, we can check the daily snapshot result)
Closes#33003 from dongjoon-hyun/SPARK-35844.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to be more robust on the underlying Hadoop library changes. Apache Spark's `copyFileToRemote` has an option, `force`, to invoke copying always and it can hit `org.apache.hadoop.fs.PathOperationException` in some Hadoop versions.
From Apache Hadoop 3.3.1, we reverted [HADOOP-16878](https://issues.apache.org/jira/browse/HADOOP-16878) as the last revert commit on `branch-3.3.1`. However, it's still in Apache Hadoop 3.4.0.
- a3b9c37a39
### Why are the changes needed?
Currently, Apache Spark Jenkins hits a flakiness issue.
- https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-3.2/lastCompletedBuild/testReport/org.apache.spark.deploy.yarn/ClientSuite/distribute_jars_archive/history/
- https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-3.2-jdk-11/2459/testReport/junit/org.apache.spark.deploy.yarn/ClientSuite/distribute_jars_archive/
```
org.apache.hadoop.fs.PathOperationException:
`Source (file:/home/jenkins/workspace/spark-master-test-maven-hadoop-3.2/resource-managers/yarn/target/tmp/spark-703b8e99-63cc-4ba6-a9bc-25c7cae8f5f9/testJar9120517778809167117.jar) and destination (/home/jenkins/workspace/spark-master-test-maven-hadoop-3.2/resource-managers/yarn/target/tmp/spark-703b8e99-63cc-4ba6-a9bc-25c7cae8f5f9/testJar9120517778809167117.jar)
are equal in the copy command.': Operation not supported
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:403)
```
Apache Spark has three cases.
- `!compareFs(srcFs, destFs)`: This is safe because we will not have this exception.
- `"file".equals(srcFs.getScheme)`: This is safe because this cannot be a `false` alarm.
- `force=true`:
- For the `good` alarm part, Spark works in the same way.
- For the `false` alarm part, Spark is safe because we use `force = true` only for copying `localConfArchive` instead of a general copy between two random clusters.
```scala
val localConfArchive = new Path(createConfArchive(confsToOverride).toURI())
copyFileToRemote(destDir, localConfArchive, replication, symlinkCache, force = true,
destName = Some(LOCALIZED_CONF_ARCHIVE))
```
### Does this PR introduce _any_ user-facing change?
No. This preserves the previous Apache Spark behavior.
### How was this patch tested?
Pass the Jenkins with Maven.
Closes#32983 from dongjoon-hyun/SPARK-35831.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
After https://github.com/apache/spark/pull/32337, all the `.idea/` in submodules are treated as git difference again.
For example, when I open the project `resource-managers/yarn/` with IntelliJ, the git status becomes
```
Untracked files:
(use "git add <file>..." to include in what will be committed)
resource-managers/yarn/.idea/
```
The same issue happens on opening `sql/hive-thriftserver/` with IntelliJ.
We should ignore all the ".idea" directories instead of the one under the root path.
### Why are the changes needed?
Make it more friendly for developers who using IDEA for the development of submodules like yarn, hive-thriftserver, etc.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Just infra changes.
Closes#32998 from gengliangwang/improveIgnore.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
