[SPARK-33492][SQL] DSv2: Append/Overwrite/ReplaceTable should invalidate cache #30429
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Kubernetes integration test starting |
|
Kubernetes integration test status failure |
|
Test build #131361 has finished for PR 30429 at commit
|
dongjoon-hyun
approved these changes
Nov 19, 2020
|
Retest this please. |
|
Kubernetes integration test starting |
|
Kubernetes integration test status success |
|
The failing test in github action is unrelated - I should have rebased to the latest master. |
|
Test build #131431 has finished for PR 30429 at commit
|
ahshahid
added a commit
to ahshahid/spark
that referenced
this pull request
Nov 23, 2020
* [SPARK-33045][SQL][FOLLOWUP] Fix build failure with Scala 2.13 ### What changes were proposed in this pull request? Explicitly convert `scala.collection.mutable.Buffer` to `Seq`. In Scala 2.13 `Seq` is an alias of `scala.collection.immutable.Seq` instead of `scala.collection.Seq`. ### Why are the changes needed? Without the change build with Scala 2.13 fails with the following: ``` [error] /home/runner/work/spark/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala:1417:41: type mismatch; [error] found : scala.collection.mutable.Buffer[org.apache.spark.unsafe.types.UTF8String] [error] required: Seq[org.apache.spark.unsafe.types.UTF8String] [error] case null => LikeAll(e, patterns) [error] ^ [error] /home/runner/work/spark/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala:1418:41: type mismatch; [error] found : scala.collection.mutable.Buffer[org.apache.spark.unsafe.types.UTF8String] [error] required: Seq[org.apache.spark.unsafe.types.UTF8String] [error] case _ => NotLikeAll(e, patterns) [error] ^ ``` ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? N/A Closes apache#30431 from sunchao/SPARK-33045-followup. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [MINOR] Structured Streaming statistics page indent fix ### What changes were proposed in this pull request? Structured Streaming statistics page code contains an indentation issue. This PR fixes it. ### Why are the changes needed? Indent fix. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Existing unit tests. Closes apache#30434 from gaborgsomogyi/STAT-INDENT-FIX. Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [MINOR][DOCS] Document 'without' value for HADOOP_VERSION in pip installation ### What changes were proposed in this pull request? I believe it's self-descriptive. ### Why are the changes needed? To document supported features. ### Does this PR introduce _any_ user-facing change? Yes, the docs are updated. It's master only. ### How was this patch tested? Manually built the docs via `cd python/docs` and `make clean html`:  Closes apache#30436 from HyukjinKwon/minor-doc-fix. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-32919][SHUFFLE][TEST-MAVEN][TEST-HADOOP2.7] Driver side changes for coordinating push based shuffle by selecting external shuffle services for merging partitions ### What changes were proposed in this pull request? Driver side changes for coordinating push based shuffle by selecting external shuffle services for merging partitions. This PR includes changes related to `ShuffleMapStage` preparation which is selection of merger locations and initializing them as part of `ShuffleDependency`. Currently this code is not used as some of the changes would come subsequently as part of https://issues.apache.org/jira/browse/SPARK-32917 (shuffle blocks push as part of `ShuffleMapTask`), https://issues.apache.org/jira/browse/SPARK-32918 (support for finalize API) and https://issues.apache.org/jira/browse/SPARK-32920 (finalization of push/merge phase). This is why the tests here are also partial, once these above mentioned changes are raised as PR we will have enough tests for DAGScheduler piece of code as well. ### Why are the changes needed? Added a new API in `SchedulerBackend` to get merger locations for push based shuffle. This is currently implemented for Yarn and other cluster managers can have separate implementations which is why a new API is introduced. ### Does this PR introduce _any_ user-facing change? Yes, user facing config to enable push based shuffle is introduced ### How was this patch tested? Added unit tests partially and some of the changes in DAGScheduler depends on future changes, DAGScheduler tests will be added along with those changes. Lead-authored-by: Venkata krishnan Sowrirajan vsowrirajanlinkedin.com Co-authored-by: Min Shen mshenlinkedin.com Closes apache#30164 from venkata91/upstream-SPARK-32919. Lead-authored-by: Venkata krishnan Sowrirajan <vsowrirajan@linkedin.com> Co-authored-by: Min Shen <mshen@linkedin.com> Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com> * [SPARK-33441][BUILD][FOLLOWUP] Make unused-imports check for SBT specific ### What changes were proposed in this pull request? Move "unused-imports" check config to `SparkBuild.scala` and make it SBT specific. ### Why are the changes needed? Make unused-imports check for SBT specific. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Pass the Jenkins or GitHub Action Closes apache#30441 from LuciferYang/SPARK-33441-FOLLOWUP. Authored-by: yangjie01 <yangjie01@baidu.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-32512][SQL][TESTS][FOLLOWUP] Remove duplicate tests for ALTER TABLE .. PARTITIONS from DataSourceV2SQLSuite ### What changes were proposed in this pull request? Remove tests from `DataSourceV2SQLSuite` that were copied to `AlterTablePartitionV2SQLSuite` by apache#29339. ### Why are the changes needed? - To reduce tests execution time - To improve test maintenance ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running the modified tests: ``` $ build/sbt "test:testOnly *DataSourceV2SQLSuite" $ build/sbt "test:testOnly *AlterTablePartitionV2SQLSuite" ``` Closes apache#30444 from MaxGekk/dedup-tests-AlterTablePartitionV2SQLSuite. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> * [SPARK-33422][DOC] Fix the correct display of left menu item ### What changes were proposed in this pull request? Limit the height of the menu area on the left to display vertical scroll bar ### Why are the changes needed? The bottom menu item cannot be displayed when the left menu tree is long ### Does this PR introduce any user-facing change? Yes, if the menu item shows more, you'll see it by pulling down the vertical scroll bar before:  after:  ### How was this patch tested? NA Closes apache#30335 from liucht-inspur/master. Authored-by: liucht <liucht@inspur.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-33468][SQL] ParseUrl in ANSI mode should fail if input string is not a valid url ### What changes were proposed in this pull request? With `ParseUrl`, instead of return null we throw exception if input string is not a vaild url. ### Why are the changes needed? For ANSI mode. ### Does this PR introduce _any_ user-facing change? Yes, user will get exception if `set spark.sql.ansi.enabled=true`. ### How was this patch tested? Add test. Closes apache#30399 from ulysses-you/SPARK-33468. Lead-authored-by: ulysses <youxiduo@weidian.com> Co-authored-by: ulysses-you <youxiduo@weidian.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> * [SPARK-28704][SQL][TEST] Add back Skiped HiveExternalCatalogVersionsSuite in HiveSparkSubmitSuite at JDK9+ ### What changes were proposed in this pull request? We skip test HiveExternalCatalogVersionsSuite when testing with JAVA_9 or later because our previous version does not support JAVA_9 or later. We now add it back since we have a version supports JAVA_9 or later. ### Why are the changes needed? To recover test coverage. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Check CI logs. Closes apache#30428 from AngersZhuuuu/SPARK-28704. Authored-by: angerszhu <angers.zhu@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [SPARK-33466][ML][PYTHON] Imputer support mode(most_frequent) strategy ### What changes were proposed in this pull request? impl a new strategy `mode`: replace missing using the most frequent value along each column. ### Why are the changes needed? it is highly scalable, and had been a function in [sklearn.impute.SimpleImputer](https://scikit-learn.org/stable/modules/generated/sklearn.impute.SimpleImputer.html#sklearn.impute.SimpleImputer) for a long time. ### Does this PR introduce _any_ user-facing change? Yes, a new strategy is added ### How was this patch tested? updated testsuites Closes apache#30397 from zhengruifeng/imputer_max_freq. Lead-authored-by: Ruifeng Zheng <ruifengz@foxmail.com> Co-authored-by: zhengruifeng <ruifengz@foxmail.com> Signed-off-by: Sean Owen <srowen@gmail.com> * [MINOR][TESTS][DOCS] Use fully-qualified class name in docker integration test ### What changes were proposed in this pull request? change ``` ./build/sbt -Pdocker-integration-tests "testOnly *xxxIntegrationSuite" ``` to ``` ./build/sbt -Pdocker-integration-tests "testOnly org.apache.spark.sql.jdbc.xxxIntegrationSuite" ``` ### Why are the changes needed? We only want to start v1 ```xxxIntegrationSuite```, not the newly added```v2.xxxIntegrationSuite```. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Manually checked Closes apache#30448 from huaxingao/dockertest. Authored-by: Huaxin Gao <huaxing@us.ibm.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [SPARK-33492][SQL] DSv2: Append/Overwrite/ReplaceTable should invalidate cache ### What changes were proposed in this pull request? This adds changes in the following places: - logic to also refresh caches referencing the target table in v2 `AppendDataExec`, `OverwriteByExpressionExec`, `OverwritePartitionsDynamicExec`, as well as their v1 fallbacks `AppendDataExecV1` and `OverwriteByExpressionExecV1`. - logic to invalidate caches referencing the target table in v2 `ReplaceTableAsSelectExec` and its atomic version `AtomicReplaceTableAsSelectExec`. These are only supported in v2 at the moment though. In addition to the above, in order to test the v1 write fallback behavior, I extended `InMemoryTableWithV1Fallback` to also support batch reads. ### Why are the changes needed? Currently in DataSource v2 we don't refresh or invalidate caches referencing the target table when the table content is changed by operations such as append, overwrite, or replace table. This is different from DataSource v1, and could potentially cause data correctness issue if the staled caches are queried later. ### Does this PR introduce _any_ user-facing change? Yes. Now When a data source v2 is cached (either directly or indirectly), all the relevant caches will be refreshed or invalidated if the table is replaced. ### How was this patch tested? Added unit tests for the new code path. Closes apache#30429 from sunchao/SPARK-33492. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [SPARK-32670][SQL] Group exception messages in Catalyst Analyzer in one file ### What changes were proposed in this pull request? Group all messages of `AnalysisExcpetions` created and thrown directly in org.apache.spark.sql.catalyst.analysis.Analyzer in one file. * Create a new object: `org.apache.spark.sql.CatalystErrors` with many exception-creating functions. * When the `Analyzer` wants to create and throw a new `AnalysisException`, call functions of `CatalystErrors` ### Why are the changes needed? This is the sample PR that groups exception messages together in several files. It will largely help with standardization of error messages and its maintenance. ### Does this PR introduce _any_ user-facing change? No. Error messages remain unchanged. ### How was this patch tested? No new tests - pass all original tests to make sure it doesn't break any existing behavior. ### Naming of exception functions All function names ended with `Error`. * For specific errors like `groupingIDMismatch` and `groupingColInvalid`, directly use them as name, just like `groupingIDMismatchError` and `groupingColInvalidError`. * For generic errors like `dataTypeMismatch`, * if confident with the context, prefix and condition can be added, like `pivotValDataTypeMismatchError` * if not sure about the context, add a `For` suffix of the specific component that this exception is related to, like `dataTypeMismatchForDeserializerError` Closes apache#29497 from anchovYu/32670. Lead-authored-by: anchovYu <aureole@sjtu.edu.cn> Co-authored-by: anchovYu <xyyu15@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-33223][SS][FOLLOWUP] Clarify the meaning of "number of rows dropped by watermark" in SS UI page ### What changes were proposed in this pull request? This PR fixes the representation to clarify the meaning of "number of rows dropped by watermark" in SS UI page. ### Why are the changes needed? `Aggregated Number Of State Rows Dropped By Watermark` says that the dropped rows are from the state, whereas they're not. We say "evicted from the state" for the case, which is "normal" to emit outputs and reduce memory usage of the state. The metric actually represents the number of "input" rows dropped by watermark, and the meaning of "input" is relative to the "stateful operator". That's a bit confusing as we normally think "input" as "input from source" whereas it's not. ### Does this PR introduce _any_ user-facing change? Yes, UI element & tooltip change. ### How was this patch tested? Only text change in UI, so we know how thing will be changed intuitively. Closes apache#30439 from HeartSaVioR/SPARK-33223-FOLLOWUP. Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com> Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com> * [SPARK-33505][SQL][TESTS] Fix adding new partitions by INSERT INTO `InMemoryPartitionTable` ### What changes were proposed in this pull request? 1. Add a hook method to `addPartitionKey()` of `InMemoryTable` which is called per every row. 2. Override `addPartitionKey()` in `InMemoryPartitionTable`, and add partition key every time when new row is inserted to the table. ### Why are the changes needed? To be able to write unified tests for datasources V1 and V2. Currently, INSERT INTO a V1 table creates partitions but the same doesn't work for the custom catalog `InMemoryPartitionTableCatalog` used in DSv2 tests. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running the affected test suite `DataSourceV2SQLSuite`. Closes apache#30449 from MaxGekk/insert-into-InMemoryPartitionTable. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [SPARK-32381][CORE][FOLLOWUP][TEST-HADOOP2.7] Don't remove SerializableFileStatus and SerializableBlockLocation for Hadoop 2.7 ### What changes were proposed in this pull request? Revert the change in apache#29959 and don't remove `SerializableFileStatus` and `SerializableBlockLocation`. ### Why are the changes needed? In Hadoop 2.7 `FileStatus` and `BlockLocation` are not serializable, so we still need the two wrapper classes. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? N/A Closes apache#30447 from sunchao/SPARK-32381-followup. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * Revert "[SPARK-28704][SQL][TEST] Add back Skiped HiveExternalCatalogVersionsSuite in HiveSparkSubmitSuite at JDK9+" This reverts commit 47326ac. * [SPARK-33463][SQL] Keep Job Id during incremental collect in Spark Thrift Server ### What changes were proposed in this pull request? When enabling **spark.sql.thriftServer.incrementalCollect** Job Ids get lost and tracing queries in Spark Thrift Server ends up being too complicated. ### Why are the changes needed? Because it will make easier tracing Spark Thrift Server queries. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? The current tests are enough. No need of more tests. Closes apache#30390 from gumartinm/master. Authored-by: Gustavo Martin Morcuende <gu.martinm@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [SPARK-28704][SQL][TEST] Add back Skiped HiveExternalCatalogVersionsSuite in HiveSparkSubmitSuite at JDK9+ ### What changes were proposed in this pull request? We skip test HiveExternalCatalogVersionsSuite when testing with JAVA_9 or later because our previous version does not support JAVA_9 or later. We now add it back since we have a version supports JAVA_9 or later. ### Why are the changes needed? To recover test coverage. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Check CI logs. Closes apache#30451 from AngersZhuuuu/SPARK-28704. Authored-by: angerszhu <angers.zhu@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [SPARK-31962][SQL] Provide modifiedAfter and modifiedBefore options when filtering from a batch-based file data source ### What changes were proposed in this pull request? Two new options, _modifiiedBefore_ and _modifiedAfter_, is provided expecting a value in 'YYYY-MM-DDTHH:mm:ss' format. _PartioningAwareFileIndex_ considers these options during the process of checking for files, just before considering applied _PathFilters_ such as `pathGlobFilter.` In order to filter file results, a new PathFilter class was derived for this purpose. General house-keeping around classes extending PathFilter was performed for neatness. It became apparent support was needed to handle multiple potential path filters. Logic was introduced for this purpose and the associated tests written. ### Why are the changes needed? When loading files from a data source, there can often times be thousands of file within a respective file path. In many cases I've seen, we want to start loading from a folder path and ideally be able to begin loading files having modification dates past a certain point. This would mean out of thousands of potential files, only the ones with modification dates greater than the specified timestamp would be considered. This saves a ton of time automatically and reduces significant complexity managing this in code. ### Does this PR introduce _any_ user-facing change? This PR introduces an option that can be used with batch-based Spark file data sources. A documentation update was made to reflect an example and usage of the new data source option. **Example Usages** _Load all CSV files modified after date:_ `spark.read.format("csv").option("modifiedAfter","2020-06-15T05:00:00").load()` _Load all CSV files modified before date:_ `spark.read.format("csv").option("modifiedBefore","2020-06-15T05:00:00").load()` _Load all CSV files modified between two dates:_ `spark.read.format("csv").option("modifiedAfter","2019-01-15T05:00:00").option("modifiedBefore","2020-06-15T05:00:00").load() ` ### How was this patch tested? A handful of unit tests were added to support the positive, negative, and edge case code paths. It's also live in a handful of our Databricks dev environments. (quoted from cchighman) Closes apache#30411 from HeartSaVioR/SPARK-31962. Lead-authored-by: CC Highman <christopher.highman@microsoft.com> Co-authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com> Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com> * [SPARK-33469][SQL] Add current_timezone function ### What changes were proposed in this pull request? Add a `CurrentTimeZone` function and replace the value at `Optimizer` side. ### Why are the changes needed? Let user get current timezone easily. Then user can call ``` SELECT current_timezone() ``` Presto: https://prestodb.io/docs/current/functions/datetime.html SQL Server: https://docs.microsoft.com/en-us/sql/t-sql/functions/current-timezone-transact-sql?view=sql-server-ver15 ### Does this PR introduce _any_ user-facing change? Yes, a new function. ### How was this patch tested? Add test. Closes apache#30400 from ulysses-you/SPARK-33469. Lead-authored-by: ulysses <youxiduo@weidian.com> Co-authored-by: ulysses-you <youxiduo@weidian.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [SPARK-33512][BUILD] Upgrade test libraries ### What changes were proposed in this pull request? This PR aims to update the test libraries. - ScalaTest: 3.2.0 -> 3.2.3 - JUnit: 4.12 -> 4.13.1 - Mockito: 3.1.0 -> 3.4.6 - JMock: 2.8.4 -> 2.12.0 - maven-surefire-plugin: 3.0.0-M3 -> 3.0.0-M5 - scala-maven-plugin: 4.3.0 -> 4.4.0 ### Why are the changes needed? This will make the test frameworks up-to-date for Apache Spark 3.1.0. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Pass the CIs. Closes apache#30456 from dongjoon-hyun/SPARK-33512. Authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * [MINOR][INFRA] Suppress warning in check-license ### What changes were proposed in this pull request? This PR aims to suppress the warning `File exists` in check-license ### Why are the changes needed? **BEFORE** ``` % dev/check-license Attempting to fetch rat RAT checks passed. % dev/check-license mkdir: target: File exists RAT checks passed. ``` **AFTER** ``` % dev/check-license Attempting to fetch rat RAT checks passed. % dev/check-license RAT checks passed. ``` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Manually do dev/check-license twice. Closes apache#30460 from williamhyun/checklicense. Authored-by: William Hyun <williamhyun3@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-33427][SQL][FOLLOWUP] Put key and value into IdentityHashMap sequantially ### What changes were proposed in this pull request? This follow-up fixes an issue when inserting key/value pairs into `IdentityHashMap` in `SubExprEvaluationRuntime`. ### Why are the changes needed? The last commits to apache#30341 follows review comment to use `IdentityHashMap`. Because we leverage `IdentityHashMap` to compare keys in reference, we should not convert expression pairs to Scala map before inserting. Scala map compares keys by equality so we will loss keys with different references. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Run benchmark to verify. Closes apache#30459 from viirya/SPARK-33427-map. Authored-by: Liang-Chi Hsieh <viirya@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-33143][PYTHON] Add configurable timeout to python server and client ### What changes were proposed in this pull request? Spark creates local server to serialize several type of data for python. The python code tries to connect to the server, immediately after it's created but there are several system calls in between (this may change in each Spark version): * getaddrinfo * socket * settimeout * connect Under some circumstances in heavy user environments these calls can be super slow (more than 15 seconds). These issues must be analyzed one-by-one but since these are system calls the underlying OS and/or DNS servers must be debugged and fixed. This is not trivial task and at the same time data processing must work somehow. In this PR I'm only intended to add a configuration possibility to increase the mentioned timeouts in order to be able to provide temporary workaround. The rootcause analysis is ongoing but I think this can vary in each case. Because the server part doesn't contain huge amount of log entries to with one can measure time, I've added some. ### Why are the changes needed? Provide workaround when localhost python server connection timeout appears. ### Does this PR introduce _any_ user-facing change? Yes, new configuration added. ### How was this patch tested? Existing unit tests + manual test. ``` #Compile Spark echo "spark.io.encryption.enabled true" >> conf/spark-defaults.conf echo "spark.python.authenticate.socketTimeout 10" >> conf/spark-defaults.conf $ ./bin/pyspark Python 3.8.5 (default, Jul 21 2020, 10:48:26) [Clang 11.0.3 (clang-1103.0.32.62)] on darwin Type "help", "copyright", "credits" or "license" for more information. 20/11/20 10:17:03 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). 20/11/20 10:17:03 WARN SparkEnv: I/O encryption enabled without RPC encryption: keys will be visible on the wire. Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /__ / .__/\_,_/_/ /_/\_\ version 3.1.0-SNAPSHOT /_/ Using Python version 3.8.5 (default, Jul 21 2020 10:48:26) Spark context Web UI available at http://192.168.0.189:4040 Spark context available as 'sc' (master = local[*], app id = local-1605863824276). SparkSession available as 'spark'. >>> sc.setLogLevel("TRACE") >>> sc.parallelize([0, 2, 3, 4, 6], 5).glom().collect() 20/11/20 10:17:09 TRACE PythonParallelizeServer: Creating listening socket 20/11/20 10:17:09 TRACE PythonParallelizeServer: Setting timeout to 10 sec 20/11/20 10:17:09 TRACE PythonParallelizeServer: Waiting for connection on port 59726 20/11/20 10:17:09 TRACE PythonParallelizeServer: Connection accepted from address /127.0.0.1:59727 20/11/20 10:17:09 TRACE PythonParallelizeServer: Client authenticated 20/11/20 10:17:09 TRACE PythonParallelizeServer: Closing server ... 20/11/20 10:17:10 TRACE SocketFuncServer: Creating listening socket 20/11/20 10:17:10 TRACE SocketFuncServer: Setting timeout to 10 sec 20/11/20 10:17:10 TRACE SocketFuncServer: Waiting for connection on port 59735 20/11/20 10:17:10 TRACE SocketFuncServer: Connection accepted from address /127.0.0.1:59736 20/11/20 10:17:10 TRACE SocketFuncServer: Client authenticated 20/11/20 10:17:10 TRACE SocketFuncServer: Closing server [[0], [2], [3], [4], [6]] >>> ``` Closes apache#30389 from gaborgsomogyi/SPARK-33143. Lead-authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com> Co-authored-by: Hyukjin Kwon <gurwls223@gmail.com> Co-authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-33510][BUILD] Update SBT to 1.4.4 ### What changes were proposed in this pull request? This PR aims to update SBT from 1.4.2 to 1.4.4. ### Why are the changes needed? This will bring the latest bug fixes. - https://github.com/sbt/sbt/releases/tag/v1.4.3 - https://github.com/sbt/sbt/releases/tag/v1.4.4 ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Pass the CIs. Closes apache#30453 from williamhyun/sbt143. Authored-by: William Hyun <williamhyun3@gmail.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> * Revert "[SPARK-32481][CORE][SQL] Support truncate table to move data to trash" ### What changes were proposed in this pull request? This reverts commit 065f173, which is not part of any released version. That is, this is an unreleased feature ### Why are the changes needed? I like the concept of Trash, but I think this PR might just resolve a very specific issue by introducing a mechanism without a proper design doc. This could make the usage more complex. I think we need to consider the big picture. Trash directory is an important concept. If we decide to introduce it, we should consider all the code paths of Spark SQL that could delete the data, instead of Truncate only. We also need to consider what is the current behavior if the underlying file system does not provide the API `Trash.moveToAppropriateTrash`. Is the exception good? How about the performance when users are using the object store instead of HDFS? Will it impact the GDPR compliance? In sum, I think we should not merge the PR apache#29552 without the design doc and implementation plan. That is why I reverted it before the code freeze of Spark 3.1 ### Does this PR introduce _any_ user-facing change? Reverted the original commit ### How was this patch tested? The existing tests. Closes apache#30463 from gatorsmile/revertSpark-32481. Authored-by: Xiao Li <gatorsmile@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org> * [SPARK-33515][SQL] Improve exception messages while handling UnresolvedTable ### What changes were proposed in this pull request? This PR proposes to improve the exception messages while `UnresolvedTable` is handled based on this suggestion: apache#30321 (comment). Currently, when an identifier is resolved to a view when a table is expected, the following exception message is displayed (e.g., for `COMMENT ON TABLE`): ``` v is a temp view not table. ``` After this PR, the message will be: ``` v is a temp view. 'COMMENT ON TABLE' expects a table. ``` Also, if an identifier is not resolved, the following exception message is currently used: ``` Table not found: t ``` After this PR, the message will be: ``` Table not found for 'COMMENT ON TABLE': t ``` ### Why are the changes needed? To improve the exception message. ### Does this PR introduce _any_ user-facing change? Yes, the exception message will be changed as described above. ### How was this patch tested? Updated existing tests. Closes apache#30461 from imback82/unresolved_table_message. Authored-by: Terry Kim <yuminkim@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> * [SPARK-33511][SQL] Respect case sensitivity while resolving V2 partition specs ### What changes were proposed in this pull request? 1. Pre-process partition specs in `ResolvePartitionSpec`, and convert partition names according to the partition schema and the SQL config `spark.sql.caseSensitive`. In the PR, I propose to invoke `normalizePartitionSpec` for that. The function is used in DSv1 commands, so, the behavior will be similar to DSv1. 2. Move `normalizePartitionSpec()` from `sql/core/.../datasources/PartitioningUtils` to `sql/catalyst/.../util/PartitioningUtils` to use it in Catalyst's rule `ResolvePartitionSpec` ### Why are the changes needed? DSv1 commands like `ALTER TABLE .. ADD PARTITION` and `ALTER TABLE .. DROP PARTITION` respect the SQL config `spark.sql.caseSensitive` while resolving partition specs. For example: ```sql spark-sql> CREATE TABLE tbl1 (id bigint, data string) USING parquet PARTITIONED BY (id); spark-sql> ALTER TABLE tbl1 ADD PARTITION (ID=1); spark-sql> SHOW PARTITIONS tbl1; id=1 ``` The same command fails on V2 Table catalog with error: ``` AnalysisException: Partition key ID not exists ``` ### Does this PR introduce _any_ user-facing change? Yes. After the changes, partition spec resolution works as for DSv1 (without the exception showed above). ### How was this patch tested? By running `AlterTablePartitionV2SQLSuite`. Closes apache#30454 from MaxGekk/partition-spec-case-sensitivity. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> * [SPARK-33278][SQL][FOLLOWUP] Improve OptimizeWindowFunctions to avoid transfer first to nth_value ### What changes were proposed in this pull request? apache#30178 provided `OptimizeWindowFunctions` used to transfer `first` to `nth_value`. If the window frame is `UNBOUNDED PRECEDING AND CURRENT ROW` or `UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING`, `nth_value` has better performance than `first`. But the `OptimizeWindowFunctions` need to exclude other window frame. ### Why are the changes needed? Improve `OptimizeWindowFunctions` to avoid transfer `first` to `nth_value` if the specified window frame isn't `UNBOUNDED PRECEDING AND CURRENT ROW` or `UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING`. ### Does this PR introduce _any_ user-facing change? 'No'. ### How was this patch tested? Jenkins test. Closes apache#30419 from beliefer/SPARK-33278_followup. Lead-authored-by: gengjiaan <gengjiaan@360.cn> Co-authored-by: beliefer <beliefer@163.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> Co-authored-by: Chao Sun <sunchao@apple.com> Co-authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com> Co-authored-by: HyukjinKwon <gurwls223@apache.org> Co-authored-by: Venkata krishnan Sowrirajan <vsowrirajan@linkedin.com> Co-authored-by: Min Shen <mshen@linkedin.com> Co-authored-by: yangjie01 <yangjie01@baidu.com> Co-authored-by: Max Gekk <max.gekk@gmail.com> Co-authored-by: liucht <liucht@inspur.com> Co-authored-by: ulysses <youxiduo@weidian.com> Co-authored-by: angerszhu <angers.zhu@gmail.com> Co-authored-by: Ruifeng Zheng <ruifengz@foxmail.com> Co-authored-by: Huaxin Gao <huaxing@us.ibm.com> Co-authored-by: anchovYu <aureole@sjtu.edu.cn> Co-authored-by: anchovYu <xyyu15@gmail.com> Co-authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com> Co-authored-by: Dongjoon Hyun <dongjoon@apache.org> Co-authored-by: Gustavo Martin Morcuende <gu.martinm@gmail.com> Co-authored-by: CC Highman <christopher.highman@microsoft.com> Co-authored-by: William Hyun <williamhyun3@gmail.com> Co-authored-by: Liang-Chi Hsieh <viirya@gmail.com> Co-authored-by: Hyukjin Kwon <gurwls223@gmail.com> Co-authored-by: Xiao Li <gatorsmile@gmail.com> Co-authored-by: Terry Kim <yuminkim@gmail.com> Co-authored-by: gengjiaan <gengjiaan@360.cn> Co-authored-by: beliefer <beliefer@163.com>
|
Sorry I'm late to help review, but this overall looks good to me. The one minor issue I have is passing the Spark session and logical plan through the plans as new parameters. I would rather use a callback to refresh instead, so that case AppendData(r: DataSourceV2Relation, query, writeOptions, _) =>
val refresh = () => session.sharedState.cacheManager.recacheByPlan(session, r)
r.table.asWritable match {
case v1 if v1.supports(TableCapability.V1_BATCH_WRITE) =>
AppendDataExecV1(v1, writeOptions.asOptions, query, afterWrite = refresh) :: Nil
case v2 =>
AppendDataExec(v2, r, writeOptions.asOptions, planLater(query), afterWrite = refresh) :: Nil
} |
|
+1, it makes the query plan more general. |
|
Thanks @rdblue and @cloud-fan ! yes this seems like a nice improvement. I'll address your comment in a follow-up PR. |
|
Thank you, @rdblue , @cloud-fan , @sunchao . |
cloud-fan
pushed a commit
that referenced
this pull request
Nov 30, 2020
…n and v2 relation for refreshing cache ### What changes were proposed in this pull request? This replaces Spark session and `DataSourceV2Relation` in V2 write plans by replacing them with a callback `afterWrite`. ### Why are the changes needed? Per discussion in #30429, it's better to not pass Spark session and `DataSourceV2Relation` through Spark plans. Instead we can use a callback which makes the interface cleaner. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? N/A Closes #30491 from sunchao/SPARK-33492-followup. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
ahshahid
added a commit
to ahshahid/spark
that referenced
this pull request
Dec 8, 2020
* [SPARK-33287][SS][UI] Expose state custom metrics information on SS UI
### What changes were proposed in this pull request?
Structured Streaming UI is not containing state custom metrics information. In this PR I've added it.
### Why are the changes needed?
Missing state custom metrics information.
### Does this PR introduce _any_ user-facing change?
Additional UI elements appear.
### How was this patch tested?
Existing unit tests + manual test.
```
#Compile Spark
echo "spark.sql.streaming.ui.enabledCustomMetricList stateOnCurrentVersionSizeBytes" >> conf/spark-defaults.conf
sbin/start-master.sh
sbin/start-worker.sh spark://gsomogyi-MBP16:7077
./bin/spark-submit --master spark://gsomogyi-MBP16:7077 --deploy-mode client --class com.spark.Main ../spark-test/target/spark-test-1.0-SNAPSHOT-jar-with-dependencies.jar
```
<img width="1119" alt="Screenshot 2020-11-18 at 12 45 36" src="https://user-images.githubusercontent.com/18561820/99527506-2f979680-299d-11eb-9187-4ae7fbd2596a.png">
Closes #30336 from gaborgsomogyi/SPARK-33287.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
* [SPARK-33457][PYTHON] Adjust mypy configuration
### What changes were proposed in this pull request?
This pull request:
- Adds following flags to the main mypy configuration:
- [`strict_optional`](https://mypy.readthedocs.io/en/stable/config_file.html#confval-strict_optional)
- [`no_implicit_optional`](https://mypy.readthedocs.io/en/stable/config_file.html#confval-no_implicit_optional)
- [`disallow_untyped_defs`](https://mypy.readthedocs.io/en/stable/config_file.html#confval-disallow_untyped_calls)
These flags are enabled only for public API and disabled for tests and internal modules.
Additionally, these PR fixes missing annotations.
### Why are the changes needed?
Primary reason to propose this changes is to use standard configuration as used by typeshed project. This will allow us to be more strict, especially when interacting with JVM code. See for example https://github.com/apache/spark/pull/29122#pullrequestreview-513112882
Additionally, it will allow us to detect cases where annotations have unintentionally omitted.
### Does this PR introduce _any_ user-facing change?
Annotations only.
### How was this patch tested?
`dev/lint-python`.
Closes #30382 from zero323/SPARK-33457.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33252][PYTHON][DOCS] Migration to NumPy documentation style in MLlib (pyspark.mllib.*)
### What changes were proposed in this pull request?
This PR proposes migration of `pyspark.mllib` to NumPy documentation style.
### Why are the changes needed?
To improve documentation style.
Before:
After:
### Does this PR introduce _any_ user-facing change?
Yes, this changes both rendered HTML docs and console representation (SPARK-33243).
### How was this patch tested?
`dev/lint-python` and manual inspection.
Closes #30413 from zero323/SPARK-33252.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33494][SQL][AQE] Do not use local shuffle reader for repartition
### What changes were proposed in this pull request?
This PR updates `ShuffleExchangeExec` to carry more information about how much we can change the partitioning. For `repartition(col)`, we should preserve the user-specified partitioning and don't apply the AQE local shuffle reader.
### Why are the changes needed?
Similar to `repartition(number, col)`, we should respect the user-specified partitioning.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
a new test
Closes #30432 from cloud-fan/aqe.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33543][SQL] Migrate SHOW COLUMNS command to use UnresolvedTableOrView to resolve the identifier
### What changes were proposed in this pull request?
This PR proposes to migrate `SHOW COLUMNS` to use `UnresolvedTableOrView` to resolve the table/view identifier. This allows consistent resolution rules (temp view first, etc.) to be applied for both v1/v2 commands. More info about the consistent resolution rule proposal can be found in [JIRA](https://issues.apache.org/jira/browse/SPARK-29900) or [proposal doc](https://docs.google.com/document/d/1hvLjGA8y_W_hhilpngXVub1Ebv8RsMap986nENCFnrg/edit?usp=sharing).
Note that `SHOW COLUMNS` is not yet supported for v2 tables.
### Why are the changes needed?
To use `UnresolvedTableOrView` for table/view resolution. Note that `ShowColumnsCommand` internally resolves to a temp view first, so there is no resolution behavior change with this PR.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated existing tests.
Closes #30490 from imback82/show_columns.
Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33224][SS][WEBUI] Add watermark gap information into SS UI page
### What changes were proposed in this pull request?
This PR proposes to add the watermark gap information in SS UI page. Please refer below screenshots to see what we'd like to show in UI.
Please note that this PR doesn't plot the watermark value - knowing the gap between actual wall clock and watermark looks more useful than the absolute value.
### Why are the changes needed?
Watermark is the one of major metrics the end users need to track for stateful queries. Watermark defines "when" the output will be emitted for append mode, hence knowing how much gap between wall clock and watermark (input data) is very helpful to make expectation of the output.
### Does this PR introduce _any_ user-facing change?
Yes, SS UI query page will contain the watermark gap information.
### How was this patch tested?
Basic UT added. Manually tested with two queries:
> simple case
You'll see consistent watermark gap with (15 seconds + a) = 10 seconds are from delay in watermark definition, 5 seconds are trigger interval.
```
import org.apache.spark.sql.streaming.Trigger
spark.conf.set("spark.sql.shuffle.partitions", "10")
val query = spark
.readStream
.format("rate")
.option("rowsPerSecond", 1000)
.option("rampUpTime", "10s")
.load()
.selectExpr("timestamp", "mod(value, 100) as mod", "value")
.withWatermark("timestamp", "10 seconds")
.groupBy(window($"timestamp", "1 minute", "10 seconds"), $"mod")
.agg(max("value").as("max_value"), min("value").as("min_value"), avg("value").as("avg_value"))
.writeStream
.format("console")
.trigger(Trigger.ProcessingTime("5 seconds"))
.outputMode("append")
.start()
query.awaitTermination()
```
> complicated case
This randomizes the timestamp, hence producing random watermark gap. This won't be smaller than 15 seconds as I described earlier.
```
import org.apache.spark.sql.streaming.Trigger
spark.conf.set("spark.sql.shuffle.partitions", "10")
val query = spark
.readStream
.format("rate")
.option("rowsPerSecond", 1000)
.option("rampUpTime", "10s")
.load()
.selectExpr("*", "CAST(CAST(timestamp AS BIGINT) - CAST((RAND() * 100000) AS BIGINT) AS TIMESTAMP) AS tsMod")
.selectExpr("tsMod", "mod(value, 100) as mod", "value")
.withWatermark("tsMod", "10 seconds")
.groupBy(window($"tsMod", "1 minute", "10 seconds"), $"mod")
.agg(max("value").as("max_value"), min("value").as("min_value"), avg("value").as("avg_value"))
.writeStream
.format("console")
.trigger(Trigger.ProcessingTime("5 seconds"))
.outputMode("append")
.start()
query.awaitTermination()
```
Closes #30427 from HeartSaVioR/SPARK-33224.
Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
* [SPARK-33533][SQL] Fix the regression bug that ConnectionProviders don't consider case-sensitivity for properties
### What changes were proposed in this pull request?
This PR fixes an issue that `BasicConnectionProvider` doesn't consider case-sensitivity for properties.
For example, the property `oracle.jdbc.mapDateToTimestamp` should be considered case-sensitivity but it is not considered.
### Why are the changes needed?
This is a bug introduced by #29024 .
Caused by this issue, `OracleIntegrationSuite` doesn't pass.
```
[info] - SPARK-16625: General data types to be mapped to Oracle *** FAILED *** (32 seconds, 129 milliseconds)
[info] types.apply(9).equals(org.apache.spark.sql.types.DateType) was false (OracleIntegrationSuite.scala:238)
[info] org.scalatest.exceptions.TestFailedException:
[info] at org.scalatest.Assertions.newAssertionFailedException(Assertions.scala:472)
[info] at org.scalatest.Assertions.newAssertionFailedException$(Assertions.scala:471)
[info] at org.scalatest.Assertions$.newAssertionFailedException(Assertions.scala:1231)
[info] at org.scalatest.Assertions$AssertionsHelper.macroAssert(Assertions.scala:1295)
[info] at org.apache.spark.sql.jdbc.OracleIntegrationSuite.$anonfun$new$4(OracleIntegrationSuite.scala:238)
[info] at org.scalatest.OutcomeOf.outcomeOf(OutcomeOf.scala:85)
[info] at org.scalatest.OutcomeOf.outcomeOf$(OutcomeOf.scala:83)
[info] at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
[info] at org.scalatest.Transformer.apply(Transformer.scala:22)
[info] at org.scalatest.Transformer.apply(Transformer.scala:20)
[info] at org.scalatest.funsuite.AnyFunSuiteLike$$anon$1.apply(AnyFunSuiteLike.scala:190)
[info] at org.apache.spark.SparkFunSuite.withFixture(SparkFunSuite.scala:176)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.invokeWithFixture$1(AnyFunSuiteLike.scala:188)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.$anonfun$runTest$1(AnyFunSuiteLike.scala:200)
[info] at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.runTest(AnyFunSuiteLike.scala:200)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.runTest$(AnyFunSuiteLike.scala:182)
[info] at org.apache.spark.SparkFunSuite.org$scalatest$BeforeAndAfterEach$$super$runTest(SparkFunSuite.scala:61)
[info] at org.scalatest.BeforeAndAfterEach.runTest(BeforeAndAfterEach.scala:234)
[info] at org.scalatest.BeforeAndAfterEach.runTest$(BeforeAndAfterEach.scala:227)
[info] at org.apache.spark.SparkFunSuite.runTest(SparkFunSuite.scala:61)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.$anonfun$runTests$1(AnyFunSuiteLike.scala:233)
[info] at org.scalatest.SuperEngine.$anonfun$runTestsInBranch$1(Engine.scala:413)
[info] at scala.collection.immutable.List.foreach(List.scala:392)
[info] at org.scalatest.SuperEngine.traverseSubNodes$1(Engine.scala:401)
[info] at org.scalatest.SuperEngine.runTestsInBranch(Engine.scala:396)
[info] at org.scalatest.SuperEngine.runTestsImpl(Engine.scala:475)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.runTests(AnyFunSuiteLike.scala:233)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.runTests$(AnyFunSuiteLike.scala:232)
[info] at org.scalatest.funsuite.AnyFunSuite.runTests(AnyFunSuite.scala:1563)
[info] at org.scalatest.Suite.run(Suite.scala:1112)
[info] at org.scalatest.Suite.run$(Suite.scala:1094)
[info] at org.scalatest.funsuite.AnyFunSuite.org$scalatest$funsuite$AnyFunSuiteLike$$super$run(AnyFunSuite.scala:1563)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.$anonfun$run$1(AnyFunSuiteLike.scala:237)
[info] at org.scalatest.SuperEngine.runImpl(Engine.scala:535)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.run(AnyFunSuiteLike.scala:237)
[info] at org.scalatest.funsuite.AnyFunSuiteLike.run$(AnyFunSuiteLike.scala:236)
[info] at org.apache.spark.SparkFunSuite.org$scalatest$BeforeAndAfterAll$$super$run(SparkFunSuite.scala:61)
[info] at org.scalatest.BeforeAndAfterAll.liftedTree1$1(BeforeAndAfterAll.scala:213)
[info] at org.scalatest.BeforeAndAfterAll.run(BeforeAndAfterAll.scala:210)
[info] at org.scalatest.BeforeAndAfterAll.run$(BeforeAndAfterAll.scala:208)
[info] at org.apache.spark.SparkFunSuite.run(SparkFunSuite.scala:61)
[info] at org.scalatest.tools.Framework.org$scalatest$tools$Framework$$runSuite(Framework.scala:318)
[info] at org.scalatest.tools.Framework$ScalaTestTask.execute(Framework.scala:513)
[info] at sbt.ForkMain$Run.lambda$runTest$1(ForkMain.java:413)
[info] at java.util.concurrent.FutureTask.run(FutureTask.java:266)
[info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
[info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
[info] at java.lang.Thread.run(Thread.java:748)
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
With this change, I confirmed that `OracleIntegrationSuite` passes with the following command.
```
$ git clone https://github.com/oracle/docker-images.git
$ cd docker-images/OracleDatabase/SingleInstance/dockerfiles
$ ./buildDockerImage.sh -v 18.4.0 -x
$ ORACLE_DOCKER_IMAGE_NAME=oracle/database:18.4.0-xe build/sbt -Pdocker-integration-tests -Phive -Phive-thriftserver "testOnly org.apache.spark.sql.jdbc.OracleIntegrationSuite"
```
Closes #30485 from sarutak/fix-oracle-integration-suite.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33477][SQL] Hive Metastore support filter by date type
### What changes were proposed in this pull request?
Hive Metastore supports strings and integral types in filters. It could also support dates. Please see [HIVE-5679](https://github.com/apache/hive/commit/5106bf1c8671740099fca8e1a7d4b37afe97137f) for more details.
This pr add support it.
### Why are the changes needed?
Improve query performance.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unit test.
Closes #30408 from wangyum/SPARK-33477.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33549][SQL] Remove configuration spark.sql.legacy.allowCastNumericToTimestamp
### What changes were proposed in this pull request?
Remove SQL configuration spark.sql.legacy.allowCastNumericToTimestamp
### Why are the changes needed?
In the current master branch, there is a new configuration `spark.sql.legacy.allowCastNumericToTimestamp` which controls whether to cast Numeric types to Timestamp or not. The default value is true.
After https://github.com/apache/spark/pull/30260, the type conversion between Timestamp type and Numeric type is disallowed in ANSI mode. So, we don't need to a separate configuration `spark.sql.legacy.allowCastNumericToTimestamp` for disallowing the conversion. Users just need to set `spark.sql.ansi.enabled` for the behavior.
As the configuration is not in any released yet, we should remove the configuration to make things simpler.
### Does this PR introduce _any_ user-facing change?
No, since the configuration is not released yet.
### How was this patch tested?
Existing test cases
Closes #30493 from gengliangwang/LEGACY_ALLOW_CAST_NUMERIC_TO_TIMESTAMP.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33509][SQL] List partition by names from a V2 table which supports partition management
### What changes were proposed in this pull request?
1. Add new method `listPartitionByNames` to the `SupportsPartitionManagement` interface. It allows to list partitions by partition names and their values.
2. Implement new method in `InMemoryPartitionTable` which is used in DSv2 tests.
### Why are the changes needed?
Currently, the `SupportsPartitionManagement` interface exposes only `listPartitionIdentifiers` which allows to list partitions by partition values. And it requires to specify all values for partition schema fields in the prefix. This restriction does not allow to list partitions by some of partition names (not all of them).
For example, the table `tableA` is partitioned by two column `year` and `month`
```
CREATE TABLE tableA (price int, year int, month int)
USING _
partitioned by (year, month)
```
and has the following partitions:
```
PARTITION(year = 2015, month = 1)
PARTITION(year = 2015, month = 2)
PARTITION(year = 2016, month = 2)
PARTITION(year = 2016, month = 3)
```
If we want to list all partitions with `month = 2`, we have to specify `year` for **listPartitionIdentifiers()** which not always possible as we don't know all `year` values in advance. New method **listPartitionByNames()** allows to specify partition values only for `month`, and get two partitions:
```
PARTITION(year = 2015, month = 2)
PARTITION(year = 2016, month = 2)
```
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running the affected test suite `SupportsPartitionManagementSuite`.
Closes #30452 from MaxGekk/column-names-listPartitionIdentifiers.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-27194][SPARK-29302][SQL] Fix commit collision in dynamic partition overwrite mode
### What changes were proposed in this pull request?
When using dynamic partition overwrite, each task has its working dir under staging dir like `stagingDir/.spark-staging-{jobId}`, each task commits to `outputPath/.spark-staging-{jobId}/{partitionId}/part-{taskId}-{jobId}{ext}`.
When speculation enable, multiple task attempts would be setup for one task, **they have same task id and they would commit to same file concurrently**. Due to host done or node preemption, the partly-committed files aren't cleaned up, a FileAlreadyExistsException would be raised in this situation, resulting in job failure.
I don't try to change task commit process for dynamic partition overwrite, like adding attempt id to task working dir for each attempts and committing to final output dir via a new outputCommitCoordinator, here is reason:
1. `FileOutputCommitter` already has commit coordinator for each task attempts, we can leverage it rather than build a new one.
2. To say the least, we implement a coordinator solving task attempts commit conflict, suppose a severe case, application master failover, tasks with same attempt id and same task id would commit to same files, the `FileAlreadyExistsException` risk still exists
In this pr, I leverage FileOutputCommitter to solve the problem:
1. when initing a write job description, set `outputPath/.spark-staging-{jobId}` as the output dir
2. each task attempt writes output to `outputPath/.spark-staging-{jobId}/_temporary/${appAttemptId}/_temporary/${taskAttemptId}/{partitionId}/part-{taskId}-{jobId}{ext}`
3. leverage `FileOutputCommitter` coordinator, write job firstly commits output to `outputPath/.spark-staging-{jobId}/{partitionId}`
4. for dynamic partition overwrite, write job finally move `outputPath/.spark-staging-{jobId}/{partitionId}` to `outputPath/{partitionId}`
### Why are the changes needed?
Without this pr, dynamic partition overwrite would fail
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
added UT.
Closes #29000 from WinkerDu/master-fix-dynamic-partition-multi-commit.
Authored-by: duripeng <duripeng@baidu.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-31257][SPARK-33561][SQL] Unify create table syntax
### What changes were proposed in this pull request?
* Unify the create table syntax in the parser by merging Hive and DataSource clauses
* Add `SerdeInfo` and `external` boolean to statement plans and update AstBuilder to produce them
* Add conversion from create statement plan to v1 create plans in ResolveSessionCatalog
* Support new statement clauses in ResolveCatalogs conversion to v2 create plans
* Remove SparkSqlParser rules for Hive syntax
* Add "option." namespace to distinguish SERDEPROPERTIES and OPTIONS in table properties
### Why are the changes needed?
* Current behavior is confusing.
* A way to pass the Hive create options to DSv2 is needed for a Hive source.
### Does this PR introduce any user-facing change?
Not by default, but v2 sources will be able to handle STORED AS and other Hive clauses.
### How was this patch tested?
Existing tests validate there are no behavior changes.
Update unit tests for using a statement plan for Hive create syntax:
* Move create tests from spark-sql DDLParserSuite into PlanResolutionSuite
* Add parser tests to spark-catalyst DDLParserSuite
Closes #28026 from rdblue/unify-create-table.
Lead-authored-by: Ryan Blue <blue@apache.org>
Co-authored-by: Wenchen Fan <cloud0fan@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33496][SQL] Improve error message of ANSI explicit cast
### What changes were proposed in this pull request?
After https://github.com/apache/spark/pull/30260, there are some type conversions disallowed under ANSI mode.
We should tell users what they can do if they have to use the disallowed casting.
### Why are the changes needed?
Make it more user-friendly.
### Does this PR introduce _any_ user-facing change?
Yes, the error message is improved on casting failure when ANSI mode is enabled
### How was this patch tested?
Unit tests.
Closes #30440 from gengliangwang/improveAnsiCastErrorMSG.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
* [SPARK-33540][SQL] Subexpression elimination for interpreted predicate
### What changes were proposed in this pull request?
This patch proposes to support subexpression elimination for interpreted predicate.
### Why are the changes needed?
Similar to interpreted projection, there are use cases when codegen predicate is not able to work, e.g. too complex schema, non-codegen expression, etc. When there are frequently occurring expressions (subexpressions) among predicate expression, the performance is quite bad as we need to re-compute same expressions. We should be able to support subexpression elimination for interpreted predicate like interpreted projection.
### Does this PR introduce _any_ user-facing change?
No, this doesn't change user behavior.
### How was this patch tested?
Unit test and benchmark.
Closes #30497 from viirya/SPARK-33540.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-31257][SPARK-33561][SQL][FOLLOWUP] Fix Scala 2.13 compilation
### What changes were proposed in this pull request?
This PR is a follow-up to fix Scala 2.13 compilation.
### Why are the changes needed?
To support Scala 2.13 in Apache Spark 3.1.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the GitHub Action Scala 2.13 compilation job.
Closes #30502 from dongjoon-hyun/SPARK-31257.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33525][SQL] Update hive-service-rpc to 3.1.2
### What changes were proposed in this pull request?
We supported Hive metastore are 0.12.0 through 3.1.2, but we supported hive-jdbc are 0.12.0 through 2.3.7. It will throw `TProtocolException` if we use hive-jdbc 3.x:
```
[rootspark-3267648 apache-hive-3.1.2-bin]# bin/beeline -u jdbc:hive2://localhost:10000/default
Connecting to jdbc:hive2://localhost:10000/default
Connected to: Spark SQL (version 3.1.0-SNAPSHOT)
Driver: Hive JDBC (version 3.1.2)
Transaction isolation: TRANSACTION_REPEATABLE_READ
Beeline version 3.1.2 by Apache Hive
0: jdbc:hive2://localhost:10000/default> create table t1(id int) using parquet;
Unexpected end of file when reading from HS2 server. The root cause might be too many concurrent connections. Please ask the administrator to check the number of active connections, and adjust hive.server2.thrift.max.worker.threads if applicable.
Error: org.apache.thrift.transport.TTransportException (state=08S01,code=0)
```
```
org.apache.thrift.protocol.TProtocolException: Missing version in readMessageBegin, old client?
at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:234)
at org.apache.thrift.TBaseProcessor.process(TBaseProcessor.java:27)
at org.apache.hive.service.auth.TSetIpAddressProcessor.process(TSetIpAddressProcessor.java:53)
at org.apache.thrift.server.TThreadPoolServer$WorkerProcess.run(TThreadPoolServer.java:310)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1130)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:630)
at java.base/java.lang.Thread.run(Thread.java:832)
```
This pr upgrade hive-service-rpc to 3.1.2 to fix this issue.
### Why are the changes needed?
To support hive-jdbc 3.x.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manual test:
```
[rootspark-3267648 apache-hive-3.1.2-bin]# bin/beeline -u jdbc:hive2://localhost:10000/default
Connecting to jdbc:hive2://localhost:10000/default
Connected to: Spark SQL (version 3.1.0-SNAPSHOT)
Driver: Hive JDBC (version 3.1.2)
Transaction isolation: TRANSACTION_REPEATABLE_READ
Beeline version 3.1.2 by Apache Hive
0: jdbc:hive2://localhost:10000/default> create table t1(id int) using parquet;
+---------+
| Result |
+---------+
+---------+
No rows selected (1.051 seconds)
0: jdbc:hive2://localhost:10000/default> insert into t1 values(1);
+---------+
| Result |
+---------+
+---------+
No rows selected (2.08 seconds)
0: jdbc:hive2://localhost:10000/default> select * from t1;
+-----+
| id |
+-----+
| 1 |
+-----+
1 row selected (0.605 seconds)
```
Closes #30478 from wangyum/SPARK-33525.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33565][BUILD][PYTHON] remove python3.8 and fix breakage
### What changes were proposed in this pull request?
remove python 3.8 from python/run-tests.py and stop build breaks
### Why are the changes needed?
the python tests are running against the bare-bones system install of python3, rather than an anaconda environment.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
via jenkins
Closes #30506 from shaneknapp/remove-py38.
Authored-by: shane knapp <incomplete@gmail.com>
Signed-off-by: shane knapp <incomplete@gmail.com>
* [SPARK-33523][SQL][TEST][FOLLOWUP] Fix benchmark case name in SubExprEliminationBenchmark
### What changes were proposed in this pull request?
Fix the wrong benchmark case name.
### Why are the changes needed?
The last commit to refactor the benchmark code missed a change of case name.
### Does this PR introduce _any_ user-facing change?
No, dev only.
### How was this patch tested?
Unit test.
Closes #30505 from viirya/SPARK-33523-followup.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33562][UI] Improve the style of the checkbox in executor page
### What changes were proposed in this pull request?
1. Remove the fixed width style of class `container-fluid-div`. So that the UI looks clean when the text is long.
2. Add one space between a checkbox and the text on the right side, which is consistent with the stage page.
### Why are the changes needed?
The width of class `container-fluid-div` is set as 200px after https://github.com/apache/spark/pull/21688 . This makes the checkbox in the executor page messy.
We should remove the width limit.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manual test.
After the changes:
Closes #30500 from gengliangwang/reviseStyle.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33565][INFRA][FOLLOW-UP] Keep the test coverage with Python 3.8 in GitHub Actions
### What changes were proposed in this pull request?
This PR proposes to keep the test coverage with Python 3.8 in GitHub Actions. It is not tested for now in Jenkins due to an env issue.
**Before this change in GitHub Actions:**
```
========================================================================
Running PySpark tests
========================================================================
Running PySpark tests. Output is in /__w/spark/spark/python/unit-tests.log
Will test against the following Python executables: ['python3.6', 'pypy3']
...
```
**After this change in GitHub Actions:**
```
========================================================================
Running PySpark tests
========================================================================
Running PySpark tests. Output is in /__w/spark/spark/python/unit-tests.log
Will test against the following Python executables: ['python3.6', 'python3.8', 'pypy3']
```
### Why are the changes needed?
To keep the test coverage with Python 3.8 in GitHub Actions.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
GitHub Actions in this build will test.
Closes #30510 from HyukjinKwon/SPARK-33565.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33551][SQL] Do not use custom shuffle reader for repartition
### What changes were proposed in this pull request?
This PR fixes an AQE issue where local shuffle reader, partition coalescing, or skew join optimization can be mistakenly applied to a shuffle introduced by repartition or a regular shuffle that logically replaces a repartition shuffle.
The proposed solution checks for the presence of any repartition shuffle and filters out not applicable optimization rules for the final stage in an AQE plan.
### Why are the changes needed?
Without the change, the output of a repartition query may not be correct.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Added UT.
Closes #30494 from maryannxue/csr-repartition.
Authored-by: Maryann Xue <maryann.xue@gmail.com>
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
* [SPARK-33563][PYTHON][R][SQL] Expose inverse hyperbolic trig functions in PySpark and SparkR
### What changes were proposed in this pull request?
This PR adds the following functions (introduced in Scala API with SPARK-33061):
- `acosh`
- `asinh`
- `atanh`
to Python and R.
### Why are the changes needed?
Feature parity.
### Does this PR introduce _any_ user-facing change?
New functions.
### How was this patch tested?
New unit tests.
Closes #30501 from zero323/SPARK-33563.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33566][CORE][SQL][SS][PYTHON] Make unescapedQuoteHandling option configurable when read CSV
### What changes were proposed in this pull request?
There are some differences between Spark CSV, opencsv and commons-csv, the typical case are described in SPARK-33566, When there are both unescaped quotes and unescaped qualifier in value, the results of parsing are different.
The reason for the difference is Spark use `STOP_AT_DELIMITER` as default `UnescapedQuoteHandling` to build `CsvParser` and it not configurable.
On the other hand, opencsv and commons-csv use the parsing mechanism similar to `STOP_AT_CLOSING_QUOTE ` by default.
So this pr make `unescapedQuoteHandling` option configurable to get the same parsing result as opencsv and commons-csv.
### Why are the changes needed?
Make unescapedQuoteHandling option configurable when read CSV to make parsing more flexible。
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- Pass the Jenkins or GitHub Action
- Add a new case similar to that described in SPARK-33566
Closes #30518 from LuciferYang/SPARK-33566.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33575][SQL] Fix misleading exception for "ANALYZE TABLE ... FOR COLUMNS" on temporary views
### What changes were proposed in this pull request?
This PR proposes to fix the exception message for `ANALYZE TABLE ... FOR COLUMNS` on temporary views.
The current behavior throws `NoSuchTableException` even if the temporary view exists:
```
sql("CREATE TEMP VIEW t AS SELECT 1 AS id")
sql("ANALYZE TABLE t COMPUTE STATISTICS FOR COLUMNS id")
org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 't' not found in database 'db';
at org.apache.spark.sql.execution.command.AnalyzeColumnCommand.analyzeColumnInTempView(AnalyzeColumnCommand.scala:76)
at org.apache.spark.sql.execution.command.AnalyzeColumnCommand.run(AnalyzeColumnCommand.scala:54)
```
After this PR, more reasonable exception is thrown:
```
org.apache.spark.sql.AnalysisException: Temporary view `testView` is not cached for analyzing columns.;
[info] at org.apache.spark.sql.execution.command.AnalyzeColumnCommand.analyzeColumnInTempView(AnalyzeColumnCommand.scala:74)
[info] at org.apache.spark.sql.execution.command.AnalyzeColumnCommand.run(AnalyzeColumnCommand.scala:54)
```
### Why are the changes needed?
To fix a misleading exception.
### Does this PR introduce _any_ user-facing change?
Yes, the exception thrown is changed as shown above.
### How was this patch tested?
Updated existing test.
Closes #30519 from imback82/analyze_table_message.
Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33522][SQL] Improve exception messages while handling UnresolvedTableOrView
### What changes were proposed in this pull request?
This PR proposes to improve the exception messages while `UnresolvedTableOrView` is handled based on this suggestion: https://github.com/apache/spark/pull/30321#discussion_r521127001.
Currently, when an identifier is resolved to a temp view when a table/permanent view is expected, the following exception message is displayed (e.g., for `SHOW CREATE TABLE`):
```
t is a temp view not table or permanent view.
```
After this PR, the message will be:
```
t is a temp view. 'SHOW CREATE TABLE' expects a table or permanent view.
```
Also, if an identifier is not resolved, the following exception message is currently used:
```
Table or view not found: t
```
After this PR, the message will be:
```
Table or permanent view not found for 'SHOW CREATE TABLE': t
```
or
```
Table or view not found for 'ANALYZE TABLE ... FOR COLUMNS ...': t
```
### Why are the changes needed?
To improve the exception message.
### Does this PR introduce _any_ user-facing change?
Yes, the exception message will be changed as described above.
### How was this patch tested?
Updated existing tests.
Closes #30475 from imback82/unresolved_table_or_view.
Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-28645][SQL] ParseException is thrown when the window is redefined
### What changes were proposed in this pull request?
Currently in Spark one could redefine a window. For instance:
`select count(*) OVER w FROM tenk1 WINDOW w AS (ORDER BY unique1), w AS (ORDER BY unique1);`
The window `w` is defined two times. In PgSQL, on the other hand, a thrown will happen:
`ERROR: window "w" is already defined`
### Why are the changes needed?
The current implement gives the following window definitions a higher priority. But it wasn't Spark's intention and users can't know from any document of Spark.
This PR fixes the bug.
### Does this PR introduce _any_ user-facing change?
Yes.
There is an example query output with/without this fix.
```
SELECT
employee_name,
salary,
first_value(employee_name) OVER w highest_salary,
nth_value(employee_name, 2) OVER w second_highest_salary
FROM
basic_pays
WINDOW
w AS (ORDER BY salary DESC ROWS BETWEEN UNBOUNDED PRECEDING AND 1 FOLLOWING),
w AS (ORDER BY salary DESC ROWS BETWEEN UNBOUNDED PRECEDING AND 2 FOLLOWING)
ORDER BY salary DESC
```
The output before this fix:
```
Larry Bott 11798 Larry Bott Gerard Bondur
Gerard Bondur 11472 Larry Bott Gerard Bondur
Pamela Castillo 11303 Larry Bott Gerard Bondur
Barry Jones 10586 Larry Bott Gerard Bondur
George Vanauf 10563 Larry Bott Gerard Bondur
Loui Bondur 10449 Larry Bott Gerard Bondur
Mary Patterson 9998 Larry Bott Gerard Bondur
Steve Patterson 9441 Larry Bott Gerard Bondur
Julie Firrelli 9181 Larry Bott Gerard Bondur
Jeff Firrelli 8992 Larry Bott Gerard Bondur
William Patterson 8870 Larry Bott Gerard Bondur
Diane Murphy 8435 Larry Bott Gerard Bondur
Leslie Jennings 8113 Larry Bott Gerard Bondur
Gerard Hernandez 6949 Larry Bott Gerard Bondur
Foon Yue Tseng 6660 Larry Bott Gerard Bondur
Anthony Bow 6627 Larry Bott Gerard Bondur
Leslie Thompson 5186 Larry Bott Gerard Bondur
```
The output after this fix:
```
struct<>
-- !query output
org.apache.spark.sql.catalyst.parser.ParseException
The definition of window 'w' is repetitive(line 8, pos 0)
```
### How was this patch tested?
Jenkins test.
Closes #30512 from beliefer/SPARK-28645.
Lead-authored-by: gengjiaan <gengjiaan@360.cn>
Co-authored-by: beliefer <beliefer@163.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33498][SQL] Datetime parsing should fail if the input string can't be parsed, or the pattern string is invalid
### What changes were proposed in this pull request?
Datetime parsing should fail if the input string can't be parsed, or the pattern string is invalid, when ANSI mode is enable. This patch should update GetTimeStamp, UnixTimeStamp, ToUnixTimeStamp and Cast.
### Why are the changes needed?
For ANSI mode.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Added UT and Existing UT.
Closes #30442 from leanken/leanken-SPARK-33498.
Authored-by: xuewei.linxuewei <xuewei.linxuewei@alibaba-inc.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33141][SQL] Capture SQL configs when creating permanent views
### What changes were proposed in this pull request?
This PR makes CreateViewCommand/AlterViewAsCommand capturing runtime SQL configs and store them as view properties. These configs will be applied during the parsing and analysis phases of the view resolution. Users can set `spark.sql.legacy.useCurrentConfigsForView` to `true` to restore the behavior before.
### Why are the changes needed?
This PR is a sub-task of [SPARK-33138](https://issues.apache.org/jira/browse/SPARK-33138) that proposes to unify temp view and permanent view behaviors. This PR makes permanent views mimicking the temp view behavior that "fixes" view semantic by directly storing resolved LogicalPlan. For example, if a user uses spark 2.4 to create a view that contains null values from division-by-zero expressions, she may not want that other users' queries which reference her view throw exceptions when running on spark 3.x with ansi mode on.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
added UT + existing UTs (improved)
Closes #30289 from luluorta/SPARK-33141.
Authored-by: luluorta <luluorta@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* Spelling r common dev mlib external project streaming resource managers python
### What changes were proposed in this pull request?
This PR intends to fix typos in the sub-modules:
* `R`
* `common`
* `dev`
* `mlib`
* `external`
* `project`
* `streaming`
* `resource-managers`
* `python`
Split per srowen https://github.com/apache/spark/pull/30323#issuecomment-728981618
NOTE: The misspellings have been reported at https://github.com/jsoref/spark/commit/706a726f87a0bbf5e31467fae9015218773db85b#commitcomment-44064356
### Why are the changes needed?
Misspelled words make it harder to read / understand content.
### Does this PR introduce _any_ user-facing change?
There are various fixes to documentation, etc...
### How was this patch tested?
No testing was performed
Closes #30402 from jsoref/spelling-R_common_dev_mlib_external_project_streaming_resource-managers_python.
Authored-by: Josh Soref <jsoref@users.noreply.github.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
* [SPARK-33570][SQL][TESTS] Set the proper version of gssapi plugin automatically for MariaDBKrbIntegrationSuite
### What changes were proposed in this pull request?
This PR changes mariadb_docker_entrypoint.sh to set the proper version automatically for mariadb-plugin-gssapi-server.
The proper version is based on the one of mariadb-server.
Also, this PR enables to use arbitrary docker image by setting the environment variable `MARIADB_CONTAINER_IMAGE_NAME`.
### Why are the changes needed?
For `MariaDBKrbIntegrationSuite`, the version of `mariadb-plugin-gssapi-server` is currently set to `10.5.5` in `mariadb_docker_entrypoint.sh` but it's no longer available in the official apt repository and `MariaDBKrbIntegrationSuite` doesn't pass for now.
It seems that only the most recent three versions are available for each major version and they are `10.5.6`, `10.5.7` and `10.5.8` for now.
Further, the release cycle of MariaDB seems to be very rapid (1 ~ 2 months) so I don't think it's a good idea to set to an specific version for `mariadb-plugin-gssapi-server`.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Confirmed that `MariaDBKrbIntegrationSuite` passes with the following commands.
```
$ build/sbt -Pdocker-integration-tests -Phive -Phive-thriftserver package "testOnly org.apache.spark.sql.jdbc.MariaDBKrbIntegrationSuite"
```
In this case, we can see what version of `mariadb-plugin-gssapi-server` is going to be installed in the following container log message.
```
Installing mariadb-plugin-gssapi-server=1:10.5.8+maria~focal
```
Or, we can set MARIADB_CONTAINER_IMAGE_NAME for a specific version of MariaDB.
```
$ MARIADB_DOCKER_IMAGE_NAME=mariadb:10.5.6 build/sbt -Pdocker-integration-tests -Phive -Phive-thriftserver package "testOnly org.apache.spark.sql.jdbc.MariaDBKrbIntegrationSuite"
```
```
Installing mariadb-plugin-gssapi-server=1:10.5.6+maria~focal
```
Closes #30515 from sarutak/fix-MariaDBKrbIntegrationSuite.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
* [SPARK-33580][CORE] resolveDependencyPaths should use classifier attribute of artifact
### What changes were proposed in this pull request?
This patch proposes to use classifier attribute to construct artifact path instead of type.
### Why are the changes needed?
`resolveDependencyPaths` now takes artifact type to decide to add "-tests" postfix. However, the path pattern of ivy in `resolveMavenCoordinates` is `[organization]_[artifact][revision](-[classifier]).[ext]`. We should use classifier instead of type to construct file path.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit test. Manual test.
Closes #30524 from viirya/SPARK-33580.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [MINOR][SQL] Remove `getTables()` from `r.SQLUtils`
### What changes were proposed in this pull request?
Remove the unused method `getTables()` from `r.SQLUtils`. The method was used before the changes https://github.com/apache/spark/pull/17483 but R's `tables.default` was rewritten using `listTables()`: https://github.com/apache/spark/pull/17483/files#diff-2c01472a7bcb1d318244afcd621d726e00d36cd15dffe7e44fa96c54fce4cd9aR220-R223
### Why are the changes needed?
To improve code maintenance, and remove the dead code.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By R tests.
Closes #30527 from MaxGekk/remove-getTables-in-r-SQLUtils.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33581][SQL][TEST] Refactor HivePartitionFilteringSuite
### What changes were proposed in this pull request?
This pr refactor HivePartitionFilteringSuite.
### Why are the changes needed?
To make it easy to maintain.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
N/A
Closes #30525 from wangyum/SPARK-33581.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Yuming Wang <yumwang@ebay.com>
* [SPARK-33590][DOCS][SQL] Add missing sub-bullets in Spark SQL Guide
### What changes were proposed in this pull request?
Add the missing sub-bullets in the left side of `Spark SQL Guide`
### Why are the changes needed?
The three sub-bullets in the left side is not consistent with the contents (five bullets) in the right side.
### Does this PR introduce _any_ user-facing change?
Yes, you can see more lines in the left menu.
### How was this patch tested?
Manually build the doc as follows. This can be verified as attached:
```
cd docs
SKIP_API=1 jekyll build
firefox _site/sql-pyspark-pandas-with-arrow.html
```
Closes #30537 from kiszk/SPARK-33590.
Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33587][CORE] Kill the executor on nested fatal errors
### What changes were proposed in this pull request?
Currently we will kill the executor when hitting a fatal error. However, if the fatal error is wrapped by another exception, such as
- java.util.concurrent.ExecutionException, com.google.common.util.concurrent.UncheckedExecutionException, com.google.common.util.concurrent.ExecutionError when using Guava cache or Java thread pool.
- SparkException thrown from https://github.com/apache/spark/blob/cf98a761de677c733f3c33230e1c63ddb785d5c5/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala#L231 or https://github.com/apache/spark/blob/cf98a761de677c733f3c33230e1c63ddb785d5c5/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala#L296
We will still keep the executor running. Fatal errors are usually unrecoverable (such as OutOfMemoryError), some components may be in a broken state when hitting a fatal error and it's hard to predicate the behaviors of a broken component. Hence, it's better to detect the nested fatal error as well and kill the executor. Then we can rely on Spark's fault tolerance to recover.
### Why are the changes needed?
Fatal errors are usually unrecoverable (such as OutOfMemoryError), some components may be in a broken state when hitting a fatal error and it's hard to predicate the behaviors of a broken component. Hence, it's better to detect the nested fatal error as well and kill the executor. Then we can rely on Spark's fault tolerance to recover.
### Does this PR introduce _any_ user-facing change?
Yep. There is a slight internal behavior change on when to kill an executor. We will kill the executor when detecting a nested fatal error in the exception chain. `spark.executor.killOnFatalError.depth` is added to allow users to turn off this change if the slight behavior change impacts them.
### How was this patch tested?
The new method `Executor.isFatalError` is tested by `spark.executor.killOnNestedFatalError`.
Closes #30528 from zsxwing/SPARK-33587.
Authored-by: Shixiong Zhu <zsxwing@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33588][SQL] Respect the `spark.sql.caseSensitive` config while resolving partition spec in v1 `SHOW TABLE EXTENDED`
### What changes were proposed in this pull request?
Perform partition spec normalization in `ShowTablesCommand` according to the table schema before getting partitions from the catalog. The normalization via `PartitioningUtils.normalizePartitionSpec()` adjusts the column names in partition specification, w.r.t. the real partition column names and case sensitivity.
### Why are the changes needed?
Even when `spark.sql.caseSensitive` is `false` which is the default value, v1 `SHOW TABLE EXTENDED` is case sensitive:
```sql
spark-sql> CREATE TABLE tbl1 (price int, qty int, year int, month int)
> USING parquet
> partitioned by (year, month);
spark-sql> INSERT INTO tbl1 PARTITION(year = 2015, month = 1) SELECT 1, 1;
spark-sql> SHOW TABLE EXTENDED LIKE 'tbl1' PARTITION(YEAR = 2015, Month = 1);
Error in query: Partition spec is invalid. The spec (YEAR, Month) must match the partition spec (year, month) defined in table '`default`.`tbl1`';
```
### Does this PR introduce _any_ user-facing change?
Yes. After the changes, the `SHOW TABLE EXTENDED` command respects the SQL config. And for example above, it returns correct result:
```sql
spark-sql> SHOW TABLE EXTENDED LIKE 'tbl1' PARTITION(YEAR = 2015, Month = 1);
default tbl1 false Partition Values: [year=2015, month=1]
Location: file:/Users/maximgekk/spark-warehouse/tbl1/year=2015/month=1
Serde Library: org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe
InputFormat: org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat
OutputFormat: org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat
Storage Properties: [serialization.format=1, path=file:/Users/maximgekk/spark-warehouse/tbl1]
Partition Parameters: {transient_lastDdlTime=1606595118, totalSize=623, numFiles=1}
Created Time: Sat Nov 28 23:25:18 MSK 2020
Last Access: UNKNOWN
Partition Statistics: 623 bytes
```
### How was this patch tested?
By running the modified test suite `v1/ShowTablesSuite`
Closes #30529 from MaxGekk/show-table-case-sensitive-spec.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33585][SQL][DOCS] Fix the comment for `SQLContext.tables()` and mention the `database` column
### What changes were proposed in this pull request?
Change the comments for `SQLContext.tables()` to "The returned DataFrame has three columns, database, tableName and isTemporary".
### Why are the changes needed?
Currently, the comment mentions only 2 columns but `tables()` returns 3 columns actually:
```scala
scala> spark.range(10).createOrReplaceTempView("view1")
scala> val tables = spark.sqlContext.tables()
tables: org.apache.spark.sql.DataFrame = [database: string, tableName: string ... 1 more field]
scala> tables.printSchema
root
|-- database: string (nullable = false)
|-- tableName: string (nullable = false)
|-- isTemporary: boolean (nullable = false)
scala> tables.show
+--------+---------+-----------+
|database|tableName|isTemporary|
+--------+---------+-----------+
| default| t1| false|
| default| t2| false|
| default| ymd| false|
| | view1| true|
+--------+---------+-----------+
```
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running `./dev/scalastyle`
Closes #30526 from MaxGekk/sqlcontext-tables-doc.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
* [SPARK-33517][SQL][DOCS] Fix the correct menu items and page links in PySpark Usage Guide for Pandas with Apache Arrow
### What changes were proposed in this pull request?
Change "Apache Arrow in Spark" to "Apache Arrow in PySpark"
and the link to “/sql-pyspark-pandas-with-arrow.html#apache-arrow-in-pyspark”
### Why are the changes needed?
When I click on the menu item it doesn't point to the correct page, and from the parent menu I can infer that the correct menu item name and link should be "Apache Arrow in PySpark".
like this:
image
### Does this PR introduce any user-facing change?
Yes, clicking on the menu item will take you to the correct guide page
### How was this patch tested?
Manually build the doc. This can be verified as below:
cd docs
SKIP_API=1 jekyll build
open _site/sql-pyspark-pandas-with-arrow.html
Closes #30466 from liucht-inspur/master.
Authored-by: liucht <liucht@inspur.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33589][SQL] Close opened session if the initialization fails
### What changes were proposed in this pull request?
This pr add try catch when opening session.
### Why are the changes needed?
Close opened session if the initialization fails.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manual test.
Before this pr:
```
[rootspark-3267648 spark]# bin/beeline -u jdbc:hive2://localhost:10000/db_not_exist
NOTE: SPARK_PREPEND_CLASSES is set, placing locally compiled Spark classes ahead of assembly.
Connecting to jdbc:hive2://localhost:10000/db_not_exist
log4j:WARN No appenders could be found for logger (org.apache.hive.jdbc.Utils).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Error: Could not open client transport with JDBC Uri: jdbc:hive2://localhost:10000/db_not_exist: Database 'db_not_exist' not found; (state=08S01,code=0)
Beeline version 2.3.7 by Apache Hive
beeline>
```
After this pr:
```
[rootspark-3267648 spark]# bin/beeline -u jdbc:hive2://localhost:10000/db_not_exist
NOTE: SPARK_PREPEND_CLASSES is set, placing locally compiled Spark classes ahead of assembly.
log4j:WARN No appenders could be found for logger (org.apache.hadoop.util.Shell).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Connecting to jdbc:hive2://localhost:10000/db_not_exist
Error: Could not open client transport with JDBC Uri: jdbc:hive2://localhost:10000/db_not_exist: Failed to open new session: org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: Database 'db_not_exist' not found; (state=08S01,code=0)
Beeline version 2.3.7 by Apache Hive
beeline>
```
Closes #30536 from wangyum/SPARK-33589.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33582][SQL] Hive Metastore support filter by not-equals
### What changes were proposed in this pull request?
This pr make partition predicate pushdown into Hive metastore support not-equals operator.
Hive related changes:
https://github.com/apache/hive/blob/b8bd4594bef718b1eeac9fceb437d7df7b480ed1/itests/hive-unit/src/test/java/org/apache/hadoop/hive/metastore/TestHiveMetaStore.java#L2194-L2207
https://issues.apache.org/jira/browse/HIVE-2702
### Why are the changes needed?
Improve query performance.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unit test.
Closes #30534 from wangyum/SPARK-33582.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33567][SQL] DSv2: Use callback instead of passing Spark session and v2 relation for refreshing cache
### What changes were proposed in this pull request?
This replaces Spark session and `DataSourceV2Relation` in V2 write plans by replacing them with a callback `afterWrite`.
### Why are the changes needed?
Per discussion in #30429, it's better to not pass Spark session and `DataSourceV2Relation` through Spark plans. Instead we can use a callback which makes the interface cleaner.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
N/A
Closes #30491 from sunchao/SPARK-33492-followup.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [MINOR] Spelling bin core docs external mllib repl
### What changes were proposed in this pull request?
This PR intends to fix typos in the sub-modules:
* `bin`
* `core`
* `docs`
* `external`
* `mllib`
* `repl`
* `pom.xml`
Split per srowen https://github.com/apache/spark/pull/30323#issuecomment-728981618
NOTE: The misspellings have been reported at https://github.com/jsoref/spark/commit/706a726f87a0bbf5e31467fae9015218773db85b#commitcomment-44064356
### Why are the changes needed?
Misspelled words make it harder to read / understand content.
### Does this PR introduce _any_ user-facing change?
There are various fixes to documentation, etc...
### How was this patch tested?
No testing was performed
Closes #30530 from jsoref/spelling-bin-core-docs-external-mllib-repl.
Authored-by: Josh Soref <jsoref@users.noreply.github.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
* [SPARK-32976][SQL] Support column list in INSERT statement
### What changes were proposed in this pull request?
#### JIRA expectations
```
INSERT currently does not support named column lists.
INSERT INTO <table> (col1, col2,…) VALUES( 'val1', 'val2', … )
Note, we assume the column list contains all the column names. Issue an exception if the list is not complete. The column order could be different from the column order defined in the table definition.
```
#### implemetations
In this PR, we add a column list as an optional part to the `INSERT OVERWRITE/INTO` statements:
```
/**
* {{{
* INSERT OVERWRITE TABLE tableIdentifier [partitionSpec [IF NOT EXISTS]]? [identifierList] ...
* INSERT INTO [TABLE] tableIdentifier [partitionSpec] [identifierList] ...
* }}}
*/
```
The column list represents all expected columns with an explicit order that you want to insert to the target table. **Particularly**, we assume the column list contains all the column names in the current implementation, it will fail when the list is incomplete.
In **Analyzer**, we add a code path to resolve the column list in the `ResolveOutputRelation` rule before it is transformed to v1 or v2 command. It will fail here if the list has any field that not belongs to the target table.
Then, for v2 command, e.g. `AppendData`, we use the resolved column list and output of the target table to resolve the output of the source query `ResolveOutputRelation` rule. If the list has duplicated columns, we fail. If the list is not empty but the list size does not match the target table, we fail. If no other exceptions occur, we use the column list to map the output of the source query to the output of the target table. The column list will be set to Nil and it will not hit the rule again after it is resolved.
for v1 command, those all happen in the `PreprocessTableInsertion` rule
### Why are the changes needed?
new feature support
### Does this PR introduce _any_ user-facing change?
yes, insert into/overwrite table support specify column list
### How was this patch tested?
new tests
Closes #29893 from yaooqinn/SPARK-32976.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33448][SQL] Support CACHE/UNCACHE TABLE commands for v2 tables
### What changes were proposed in this pull request?
This PR proposes to support `CHACHE/UNCACHE TABLE` commands for v2 tables.
In addtion, this PR proposes to migrate `CACHE/UNCACHE TABLE` to use `UnresolvedTableOrView` to resolve the table identifier. This allows consistent resolution rules (temp view first, etc.) to be applied for both v1/v2 commands. More info about the consistent resolution rule proposal can be found in [JIRA](https://issues.apache.org/jira/browse/SPARK-29900) or [proposal doc](https://docs.google.com/document/d/1hvLjGA8y_W_hhilpngXVub1Ebv8RsMap986nENCFnrg/edit?usp=sharing).
### Why are the changes needed?
To support `CACHE/UNCACHE TABLE` commands for v2 tables.
Note that `CACHE/UNCACHE TABLE` for v1 tables/views go through `SparkSession.table` to resolve identifier, which resolves temp views first, so there is no change in the behavior by moving to the new framework.
### Does this PR introduce _any_ user-facing change?
Yes. Now the user can run `CACHE/UNCACHE TABLE` commands on v2 tables.
### How was this patch tested?
Added/updated existing tests.
Closes #30403 from imback82/cache_table.
Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
* [SPARK-33498][SQL][FOLLOW-UP] Deduplicate the unittest by using checkCastWithParseError
### What changes were proposed in this pull request?
Dup code removed in SPARK-33498 as follow-up.
### Why are the changes needed?
Nit.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Existing UT.
Closes #30540 from leanken/leanken-SPARK-33498.
Authored-by: xuewei.linxuewei <xuewei.linxuewei@alibaba-inc.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-28646][SQL] Fix bug of Count so as consistent with mainstream databases
### What changes were proposed in this pull request?
Currently, Spark allows calls to `count` even for non parameterless aggregate function. For example, the following query actually works:
`SELECT count() FROM tenk1;`
On the other hand, mainstream databases will throw an error.
**Oracle**
`> ORA-00909: invalid number of arguments`
**PgSQL**
`ERROR: count(*) must be used to call a parameterless aggregate function`
**MySQL**
`> 1064 - You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')`
### Why are the changes needed?
Fix a bug so that consistent with mainstream databases.
There is an example query output with/without this fix.
`SELECT count() FROM testData;`
The output before this fix:
`0`
The output after this fix:
```
org.apache.spark.sql.AnalysisException
cannot resolve 'count()' due to data type mismatch: count requires at least one argument.; line 1 pos 7
```
### Does this PR introduce _any_ user-facing change?
Yes.
If not specify parameter for `count`, will throw an error.
### How was this patch tested?
Jenkins test.
Closes #30541 from beliefer/SPARK-28646.
Lead-authored-by: gengjiaan <gengjiaan@360.cn>
Co-authored-by: beliefer <beliefer@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
* [SPARK-33480][SQL] Support char/varchar type
### What changes were proposed in this pull request?
This PR adds the char/varchar type which is kind of a variant of string type:
1. Char type is fixed-length string. When comparing char type values, we need to pad the shorter one to the longer length.
2. Varchar type is string with a length limitation.
To implement the char/varchar semantic, this PR:
1. Do string length check when writing to char/varchar type columns.
2. Do string padding when reading char type columns. We don't do it at the writing side to save storage space.
3. Do string padding when comparing char type column with string literal or another char type column. (string literal is fixed length so should be treated as char type as well)
To simplify the implementation, this PR doesn't propagate char/varchar type info through functions/operator…
dongjoon-hyun
pushed a commit
that referenced
this pull request
Jan 8, 2021
### What changes were proposed in this pull request? This changes `ReplaceTableExec`/`AtomicReplaceTableExec`, and uncaches the target table before it is dropped. In addition, this includes some refactoring by moving the `uncacheTable` method to `DataSourceV2Strategy` so that we don't need to pass a Spark session to the v2 exec. ### Why are the changes needed? Similar to SPARK-33492 (#30429). When a table is refreshed, the associated cache should be invalidated to avoid potential incorrect results. ### Does this PR introduce _any_ user-facing change? Yes. Now When a data source v2 is cached (either directly or indirectly), all the relevant caches will be refreshed or invalidated if the table is replaced. ### How was this patch tested? Added a new unit test. Closes #31081 from sunchao/SPARK-34039. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
sunchao
added a commit
to sunchao/spark
that referenced
this pull request
Jan 9, 2021
This changes `ReplaceTableExec`/`AtomicReplaceTableExec`, and uncaches the target table before it is dropped. In addition, this includes some refactoring by moving the `uncacheTable` method to `DataSourceV2Strategy` so that we don't need to pass a Spark session to the v2 exec. Similar to SPARK-33492 (apache#30429). When a table is refreshed, the associated cache should be invalidated to avoid potential incorrect results. Yes. Now When a data source v2 is cached (either directly or indirectly), all the relevant caches will be refreshed or invalidated if the table is replaced. Added a new unit test. Closes apache#31081 from sunchao/SPARK-34039. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
HyukjinKwon
pushed a commit
that referenced
this pull request
Jan 10, 2021
### What changes were proposed in this pull request? This is a backport of #31081 to branch-3.1. This changes `ReplaceTableExec`/`AtomicReplaceTableExec`, and uncaches the target table before it is dropped. In addition, this includes some refactoring by moving the `uncacheTable` method to `DataSourceV2Strategy` so that we don't need to pass a Spark session to the v2 exec. ### Why are the changes needed? Similar to SPARK-33492 (#30429). When a table is refreshed, the associated cache should be invalidated to avoid potential incorrect results. ### Does this PR introduce _any_ user-facing change? Yes. Now When a data source v2 is cached (either directly or indirectly), all the relevant caches will be refreshed or invalidated if the table is replaced. ### How was this patch tested? Added a new unit test. Closes #31100 from sunchao/SPARK-34039-branch-3.1. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
What changes were proposed in this pull request?
This adds changes in the following places:
AppendDataExec,OverwriteByExpressionExec,OverwritePartitionsDynamicExec, as well as their v1 fallbacksAppendDataExecV1andOverwriteByExpressionExecV1.ReplaceTableAsSelectExecand its atomic versionAtomicReplaceTableAsSelectExec. These are only supported in v2 at the moment though.In addition to the above, in order to test the v1 write fallback behavior, I extended
InMemoryTableWithV1Fallbackto also support batch reads.Why are the changes needed?
Currently in DataSource v2 we don't refresh or invalidate caches referencing the target table when the table content is changed by operations such as append, overwrite, or replace table. This is different from DataSource v1, and could potentially cause data correctness issue if the staled caches are queried later.
Does this PR introduce any user-facing change?
Yes. Now When a data source v2 is cached (either directly or indirectly), all the relevant caches will be refreshed or invalidated if the table is replaced.
How was this patch tested?
Added unit tests for the new code path.