### What changes were proposed in this pull request?
This PR fixes an issue that there is no way to redact sensitive information in Spark Thrift Server log.
For example, JDBC password can be exposed in the log.
```
21/08/25 18:52:37 INFO SparkExecuteStatementOperation: Submitting query 'CREATE TABLE mytbl2(a int) OPTIONS(url="jdbc:mysql//example.com:3306", driver="com.mysql.jdbc.Driver", dbtable="test_tbl", user="test_usr", password="abcde")' with ca14ae38-1aaf-4bf4-a099-06b8e5337613
```
### Why are the changes needed?
Bug fix.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Ran ThriftServer, connect to it and execute `CREATE TABLE mytbl2(a int) OPTIONS(url="jdbc:mysql//example.com:3306", driver="com.mysql.jdbc.Driver", dbtable="test_tbl", user="test_usr", password="abcde");` with `spark.sql.redaction.string.regex=((?i)(?<=password=))(".*")|('.*')`
Then, confirmed the log.
```
21/08/25 18:54:11 INFO SparkExecuteStatementOperation: Submitting query 'CREATE TABLE mytbl2(a int) OPTIONS(url="jdbc:mysql//example.com:3306", driver="com.mysql.jdbc.Driver", dbtable="test_tbl", user="test_usr", password=*********(redacted))' with ffc627e2-b1a8-4d83-ab6d-d819b3ccd909
```
Closes#33832 from sarutak/fix-SPARK-36398.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
In the PR, I propose to add new correctness rule `SpecialDatetimeValues` to the final analysis phase. It replaces casts of strings to date/timestamp_ltz/timestamp_ntz by literals of such types if the strings contain special datetime values like `today`, `yesterday` and `tomorrow`, and the input strings are foldable.
### Why are the changes needed?
1. To avoid a breaking change.
2. To improve user experience with Spark SQL. After the PR https://github.com/apache/spark/pull/32714, users have to use typed literals instead of implicit casts. For instance,
at Spark 3.1:
```sql
select ts_col > 'now';
```
but the query fails at the moment, and users have to use typed timestamp literal:
```sql
select ts_col > timestamp'now';
```
### Does this PR introduce _any_ user-facing change?
No. Previous release 3.1 has supported the feature already till it was removed by https://github.com/apache/spark/pull/32714.
### How was this patch tested?
1. Manually tested via the sql command line:
```sql
spark-sql> select cast('today' as date);
2021-08-24
spark-sql> select timestamp('today');
2021-08-24 00:00:00
spark-sql> select timestamp'tomorrow' > 'today';
true
```
2. By running new test suite:
```
$ build/sbt "sql/testOnly org.apache.spark.sql.catalyst.optimizer.SpecialDatetimeValuesSuite"
```
Closes#33816 from MaxGekk/foldable-datetime-special-values.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR modifies `sql-ref-syntax-ddl-create-function.md` to mention `ARCHIVE` as an acceptable resource type for `CREATE FUNCTION` statement.
`ARCHIVE` is acceptable as of SPARK-35236 (#32359).
### Why are the changes needed?
To maintain the document.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
`SKIP_API=1 bundle exec jekyll build`
Closes#33823 from sarutak/create-function-archive.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to move distributed-sequence index implementation to SQL plan to leverage optimizations such as column pruning.
```python
import pyspark.pandas as ps
ps.set_option('compute.default_index_type', 'distributed-sequence')
ps.range(10).id.value_counts().to_frame().spark.explain()
```
**Before:**
```bash
== Physical Plan ==
AdaptiveSparkPlan isFinalPlan=false
+- Sort [count#51L DESC NULLS LAST], true, 0
+- Exchange rangepartitioning(count#51L DESC NULLS LAST, 200), ENSURE_REQUIREMENTS, [id=#70]
+- HashAggregate(keys=[id#37L], functions=[count(1)], output=[__index_level_0__#48L, count#51L])
+- Exchange hashpartitioning(id#37L, 200), ENSURE_REQUIREMENTS, [id=#67]
+- HashAggregate(keys=[id#37L], functions=[partial_count(1)], output=[id#37L, count#63L])
+- Project [id#37L]
+- Filter atleastnnonnulls(1, id#37L)
+- Scan ExistingRDD[__index_level_0__#36L,id#37L]
# ^^^ Base DataFrame created by the output RDD from zipWithIndex (and checkpointed)
```
**After:**
```bash
== Physical Plan ==
AdaptiveSparkPlan isFinalPlan=false
+- Sort [count#275L DESC NULLS LAST], true, 0
+- Exchange rangepartitioning(count#275L DESC NULLS LAST, 200), ENSURE_REQUIREMENTS, [id=#174]
+- HashAggregate(keys=[id#258L], functions=[count(1)])
+- HashAggregate(keys=[id#258L], functions=[partial_count(1)])
+- Filter atleastnnonnulls(1, id#258L)
+- Range (0, 10, step=1, splits=16)
# ^^^ Removed the Spark job execution for `zipWithIndex`
```
### Why are the changes needed?
To leverage optimization of SQL engine and avoid unnecessary shuffle to create default index.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unittests were added. Also, this PR will test all unittests in pandas API on Spark after switching the default index implementation to `distributed-sequence`.
Closes#33807 from HyukjinKwon/SPARK-36559.
Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
When we refactor the query execution errors to use error classes in QueryExecutionErrors, we need define some exception that mix SparkThrowable into a base Exception type.
according the example [SparkArithmeticException](f90eb6a5db/core/src/main/scala/org/apache/spark/SparkException.scala (L75))
Add SparkXXXException as follows:
- `SparkClassNotFoundException`
- `SparkConcurrentModificationException`
- `SparkDateTimeException`
- `SparkFileAlreadyExistsException`
- `SparkFileNotFoundException`
- `SparkNoSuchMethodException`
- `SparkIndexOutOfBoundsException`
- `SparkIOException`
- `SparkSecurityException`
- `SparkSQLException`
- `SparkSQLFeatureNotSupportedException`
Refactor some exceptions in QueryExecutionErrors to use error classes and new exception for testing new exception
Some added by [PR](https://github.com/apache/spark/pull/33538) as follows:
- `SparkUnsupportedOperationException`
- `SparkIllegalStateException`
- `SparkNumberFormatException`
- `SparkIllegalArgumentException`
- `SparkArrayIndexOutOfBoundsException`
- `SparkNoSuchElementException`
### Why are the changes needed?
[SPARK-36336](https://issues.apache.org/jira/browse/SPARK-36336)
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
existed ut test
Closes#33573 from Peng-Lei/SPARK-36336.
Authored-by: PengLei <peng.8lei@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Revert 397b843890 and 5a48eb8d00
### Why are the changes needed?
As discussed in https://github.com/apache/spark/pull/33800#issuecomment-904140869, there is correctness issue in the current implementation. Let's revert the code changes from branch 3.2 and fix it on master branch later
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Ci tests
Closes#33819 from gengliangwang/revert-SPARK-34415.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR fixes `NullPointerException` in `LiveRDDDistribution.toApi`.
### Why are the changes needed?
Looking at the stack trace, the NPE is caused by the null `exec.hostPort`. I can't get the complete log to take a close look but only guess that it might be due to the event `SparkListenerBlockManagerAdded` is dropped or out of order.
```
21/08/23 12:26:29 ERROR AsyncEventQueue: Listener AppStatusListener threw an exception
java.lang.NullPointerException
at com.google.common.base.Preconditions.checkNotNull(Preconditions.java:192)
at com.google.common.collect.MapMakerInternalMap.putIfAbsent(MapMakerInternalMap.java:3507)
at com.google.common.collect.Interners$WeakInterner.intern(Interners.java:85)
at org.apache.spark.status.LiveEntityHelpers$.weakIntern(LiveEntity.scala:696)
at org.apache.spark.status.LiveRDDDistribution.toApi(LiveEntity.scala:563)
at org.apache.spark.status.LiveRDD.$anonfun$doUpdate$4(LiveEntity.scala:629)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:238)
at scala.collection.mutable.HashMap$$anon$2.$anonfun$foreach$3(HashMap.scala:158)
at scala.collection.mutable.HashTable.foreachEntry(HashTable.scala:237)
at scala.collection.mutable.HashTable.foreachEntry$(HashTable.scala:230)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:44)
at scala.collection.mutable.HashMap$$anon$2.foreach(HashMap.scala:158)
at scala.collection.TraversableLike.map(TraversableLike.scala:238)
at scala.collection.TraversableLike.map$(TraversableLike.scala:231)
at scala.collection.AbstractTraversable.map(Traversable.scala:108)
at org.apache.spark.status.LiveRDD.doUpdate(LiveEntity.scala:629)
at org.apache.spark.status.LiveEntity.write(LiveEntity.scala:51)
at org.apache.spark.status.AppStatusListener.update(AppStatusListener.scala:1206)
at org.apache.spark.status.AppStatusListener.maybeUpdate(AppStatusListener.scala:1212)
at org.apache.spark.status.AppStatusListener.$anonfun$onExecutorMetricsUpdate$6(AppStatusListener.scala:956)
...
```
### Does this PR introduce _any_ user-facing change?
Yes, users will see the expected RDD info in UI instead of the NPE error.
### How was this patch tested?
Pass existing tests.
Closes#33812 from Ngone51/fix-hostport-npe.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Currently, the procedure to run the Oracle Integration Suite is based on building the Oracle RDBMS image from the Dockerfiles provided by Oracle.
Recently, Oracle has started providing database images, see https://container-registry.oracle.com
Moreover an Oracle employee is maintaining Oracle XE images that are streamlined for testing at https://hub.docker.com/r/gvenzl/oracle-xe and https://github.com/gvenzl/oci-oracle-xe This solves the issue that official images are quite large and make testing resource-intensive and slow.
This proposes to document the available options and to introduce a default value for ORACLE_DOCKER_IMAGE
### Why are the changes needed?
This change will make it easier and faster to run the Oracle Integration Suite, removing the need to manually build an Oracle DB image.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manually tested:
```
export ENABLE_DOCKER_INTEGRATION_TESTS=1
./build/sbt -Pdocker-integration-tests "testOnly org.apache.spark.sql.jdbc.OracleIntegrationSuite"
./build/sbt -Pdocker-integration-tests "testOnly org.apache.spark.sql.jdbc.v2.OracleIntegrationSuite"
```
Closes#33821 from LucaCanali/oracleDockerIntegration.
Authored-by: Luca Canali <luca.canali@cern.ch>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Move final iteration of aggregation of RDD.treeAggregate to an executor with one partition and fetch that result to the driver
## Why are the changes needed?
1. RDD.fold pulls all shuffle partitions to the driver to merge the result
a. Driver becomes a single point of failure in the case that there are a lot of partitions to do the final aggregation on
2. Shuffle machinery at executors is much more robust/fault tolerant compared to fetching results to driver.
## Does this PR introduce any user-facing change?
The previous behavior always did the final aggregation in the driver. The user can now (optionally) provide a boolean config (default = false) ENABLE_EXECUTOR_TREE_AGGREGATE to do that final aggregation in a single partition executor before fetching the results to the driver. The only additional cost is that the user will see an extra stage in their job.
## How was this patch tested?
This patch was tested via unit tests, and also tested on a cluster.
The screenshots showing the extra stage on a cluster are attached below (before vs after).
Closes#33644 from akpatnam25/SPARK-36419.
Authored-by: Aravind Patnam <apatnam@linkedin.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Add back protected modifier of sparkConf to TPCBase according to https://github.com/apache/spark/pull/33736/files#r694054229
### Why are the changes needed?
Add back protected modifier of sparkConf to TPCBase
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Not need
Closes#33813 from AngersZhuuuu/SPARK-35991-FOLLOWUP.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Add `aggregate` package under `sql/catalyst/src/main/java/org/apache/spark/sql/connector/expressions` and move all the aggregates (e.g. `Count`, `Max`, `Min`, etc.) there.
### Why are the changes needed?
Right now these aggregates are under `sql/catalyst/src/main/java/org/apache/spark/sql/connector/expressions`. It looks OK now, but we plan to add a new `filter` package under `expressions` for all the DSV2 filters. It will look strange that filters have their own package, but aggregates don't.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing tests
Closes#33815 from huaxingao/agg_package.
Authored-by: Huaxin Gao <huaxin_gao@apple.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
### What changes were proposed in this pull request?
In the PR, I propose the update the SQL migration guide about the changes introduced by the PRs https://github.com/apache/spark/pull/33709 and https://github.com/apache/spark/pull/33769.
<img width="1011" alt="Screenshot 2021-08-23 at 11 40 35" src="https://user-images.githubusercontent.com/1580697/130419710-640f20b3-6a38-4eb1-a6d6-2e069dc5665c.png">
### Why are the changes needed?
To inform users about the upcoming changes in parsing datetime strings. This should help users to migrate on the new release.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
By generating the doc, and checking by eyes:
```
$ SKIP_API=1 SKIP_RDOC=1 SKIP_PYTHONDOC=1 SKIP_SCALADOC=1 bundle exec jekyll build
```
Closes#33809 from MaxGekk/datetime-cast-migr-guide.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
Mentioning Hadoop 3 in YARN introduction on cluster-overview.md.
### Why are the changes needed?
It only mentioned Hadoop 2 but Hadoop3 is currently the latest and I believe the most used version.
### Does this PR introduce _any_ user-facing change?
Yes, docs changed.
### How was this patch tested?
`SKIP_API=1 bundle exec jekyll build`
<img width="599" alt="minor_hadoop" src="https://user-images.githubusercontent.com/87687356/130002403-989f4290-d614-46f2-9823-1897fa39f370.png">
Closes#33783 from yutoacts/minor.
Authored-by: Yuto Akutsu <yuto.akutsu@nttdata.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
As Jacek Laskowski pointed out in the dev list, there is StackOverflowError if compiling Spark with the current MAVEN_OPTS in Spark documentation.
We should update it with `-Xss64m` to avoid it.
### Why are the changes needed?
Correct the documentation
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manual test. The MAVEN_OPTS is consistent with our github action build.
Closes#33804 from gengliangwang/updateBuildDoc.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Minor changes to change the config key name from `spark.shuffle.server.mergedShuffleFileManagerImpl` to `spark.shuffle.push.server.mergedShuffleFileManagerImpl`. This is missed out in https://github.com/apache/spark/pull/33615.
### Why are the changes needed?
To keep the config names consistent
### Does this PR introduce _any_ user-facing change?
Yes, this is a change in the config key name. But the new config name changes are yet to be released. Technically there is no user facing change because of this change.
### How was this patch tested?
Existing tests.
Closes#33799 from venkata91/SPARK-36374-follow-up.
Authored-by: Venkata krishnan Sowrirajan <vsowrirajan@linkedin.com>
Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>
### What changes were proposed in this pull request?
This patch fixes an error about streaming dedupliaction is Structured Streaming, and also updates an item about unsupported operation.
### Why are the changes needed?
Update the user document.
### Does this PR introduce _any_ user-facing change?
No. It's a doc only change.
### How was this patch tested?
Doc only change.
Closes#33801 from viirya/minor-ss-deduplication.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
### What changes were proposed in this pull request?
For the hive table, the actual write path and the schema handling are inconsistent when `spark.sql.legacy.charVarcharAsString` is true.
This causes problems like SPARK-36552 described.
In this PR we respect `spark.sql.legacy.charVarcharAsString` when generates hive table schema from spark data types.
### Why are the changes needed?
bugfix
### Does this PR introduce _any_ user-facing change?
yes, when `spark.sql.legacy.charVarcharAsString` is true, hive table with char/varchar will respect string behavior.
### How was this patch tested?
newly added test
Closes#33798 from yaooqinn/SPARK-36552.
Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This pr revert the change of SPARK-34309, includes:
- https://github.com/apache/spark/pull/31517
- https://github.com/apache/spark/pull/33772
### Why are the changes needed?
1. No really performance improvement in Spark
2. Added an additional dependency
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#33784 from LuciferYang/revert-caffeine.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
* improve docs in `docs/job-scheduling.md`
* add migration guide docs in `docs/core-migration-guide.md`
### Why are the changes needed?
Help user to migrate.
### Does this PR introduce _any_ user-facing change?
yes
### How was this patch tested?
Pass CI
Closes#33794 from ulysses-you/SPARK-35083-f.
Authored-by: ulysses-you <ulyssesyou18@gmail.com>
Signed-off-by: Kent Yao <yao@apache.org>
AuthEngineSuite was passing on some platforms (MacOS), but failing on others (Linux) with an InvalidKeyException stemming from this line. We should explicitly pass AES as the key format.
### What changes were proposed in this pull request?
Changes the AuthEngine SecretKeySpec from "RAW" to "AES".
### Why are the changes needed?
Unit tests were failing on some platforms with InvalidKeyExceptions when this key was used to instantiate a Cipher.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unit tests on a MacOS and Linux platform.
Closes#33790 from sweisdb/patch-1.
Authored-by: sweisdb <60895808+sweisdb@users.noreply.github.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Change all exceptions in NoSuchItemException.scala to case classes.
### Why are the changes needed?
Exceptions in NoSuchItemException.scala are not case classes. This is causing issues because in Analyzer's executeAndCheck method always calls the `copy` method on the exception. However, since these exceptions are not case classes, the `copy` method was always delegated to `AnalysisException::copy`, which is not the specialized version.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing UTs.
Closes#33673 from yeshengm/SPARK-36448.
Authored-by: Yesheng Ma <kimi.ysma@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
After https://github.com/apache/spark/pull/32726, Python doc build requires `sphinx-plotly-directive`.
This PR is to install it from `spark-rm/Dockerfile` to make sure `do-release-docker.sh` can run successfully.
Also, this PR mentions it in the README of docs.
### Why are the changes needed?
Fix release script and update README of docs
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manual test locally.
Closes#33797 from gengliangwang/fixReleaseDocker.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
When preparing Spark 3.2.0 RC1, I hit the same issue of https://github.com/apache/spark/pull/31031.
```
[INFO] Compiling 21 Scala sources and 3 Java sources to /opt/spark-rm/output/spark-3.1.0-bin-hadoop2.7/resource-managers/yarn/target/scala-2.12/test-classes ...
[ERROR] ## Exception when compiling 24 sources to /opt/spark-rm/output/spark-3.1.0-bin-hadoop2.7/resource-managers/yarn/target/scala-2.12/test-classes
java.lang.SecurityException: class "javax.servlet.SessionCookieConfig"'s signer information does not match signer information of other classes in the same package
java.lang.ClassLoader.checkCerts(ClassLoader.java:891)
java.lang.ClassLoader.preDefineClass(ClassLoader.java:661)
```
This PR is to apply the same fix again by downgrading scala-maven-plugin to 4.3.0
### Why are the changes needed?
To unblock the release process.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Build test
Closes#33791 from gengliangwang/downgrade.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
Add more documents and checking logic for the new options `minOffsetPerTrigger` and `maxTriggerDelay`.
### Why are the changes needed?
Have a clear description of the behavior introduced in SPARK-35312
### Does this PR introduce _any_ user-facing change?
Yes.
If the user set minOffsetsPerTrigger > maxOffsetsPerTrigger, the new code will throw an AnalysisException. The original behavior is to ignore the maxOffsetsPerTrigger silenctly.
### How was this patch tested?
Existing tests.
Closes#33792 from xuanyuanking/SPARK-35312-follow.
Authored-by: Yuanjian Li <yuanjian.li@databricks.com>
Signed-off-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
https://github.com/apache/spark/pull/33775 commits the debug code mistakely.
This PR revert the test path.
### Why are the changes needed?
Revoke debug code.
### Does this PR introduce _any_ user-facing change?
'No'.
Just adjust test.
### How was this patch tested?
Revert non-ansi test path.
Closes#33787 from beliefer/SPARK-36428-followup2.
Authored-by: gengjiaan <gengjiaan@360.cn>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
…mote scheduler pool files support"
This reverts commit e3902d1975. The feature is improvement instead of behavior change.
Closes#33789 from gengliangwang/revertDoc.
Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
Add remote scheduler pool files support to the migration guide.
### Why are the changes needed?
To highlight this useful support.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass exiting tests.
Closes#33785 from Ngone51/SPARK-35083-follow-up.
Lead-authored-by: yi.wu <yi.wu@databricks.com>
Co-authored-by: wuyi <yi.wu@databricks.com>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
RocksDB provides backward compatibility but it doesn't always provide forward compatibility. It's better to store the RocksDB format version in the checkpoint so that it would give us more information to provide the rollback guarantee when we upgrade the RocksDB version that may introduce incompatible change in a new Spark version.
A typical case is when a user upgrades their query to a new Spark version, and this new Spark version has a new RocksDB version which may use a new format. But the user hits some bug and decide to rollback. But in the old Spark version, the old RocksDB version cannot read the new format.
In order to handle this case, we will write the RocksDB format version to the checkpoint. When restarting from a checkpoint, we will force RocksDB to use the format version stored in the checkpoint. This will ensure the user can rollback their Spark version if needed.
We also provide a config `spark.sql.streaming.stateStore.rocksdb.formatVersion` for users who don't need to rollback their Spark versions to overwrite the format version specified in the checkpoint.
### Why are the changes needed?
Provide the Spark version rollback guarantee for streaming queries when a new RocksDB introduces an incompatible format change.
### Does this PR introduce _any_ user-facing change?
No. RocksDB state store is a new feature in Spark 3.2, which has not yet released.
### How was this patch tested?
The new unit tests.
Closes#33749 from zsxwing/SPARK-36519.
Authored-by: Shixiong Zhu <zsxwing@gmail.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
### What changes were proposed in this pull request?
In the PR, I propose to split the `dateFormat` and `timestampFormat` options in CSV/JSON datasources to:
- In write (`dateFormatInWrite`/`timestampFormatInWrite`). CSV/JSON datasource will use it in formatting of dates/timestamps. If an user doesn't initialise it, it will be set to a default value.
- In read (`dateFormatInRead`/`timestampFormatInRead`). The datasources will use it while parsing of input dates/timestamps strings. If an user doesn't set it, we will keep it as uninitialized (None), and use CAST to parse the input dates/timestamps strings.
### Why are the changes needed?
This should improve user experience with Spark SQL, and make the default parsing behavior more flexible.
### Does this PR introduce _any_ user-facing change?
Potentially, it can.
### How was this patch tested?
By existing test suites, and by new tests that are added to `JsonSuite` and to `CSVSuite`:
```
$ build/sbt "sql/test:testOnly *CSVLegacyTimeParserSuite"
$ build/sbt "sql/test:testOnly *JsonFunctionsSuite"
$ build/sbt "sql/test:testOnly *CSVv1Suite"
$ build/sbt "sql/test:testOnly *JsonV2Suite"
```
Closes#33769 from MaxGekk/split-datetime-ds-options.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>
### What changes were proposed in this pull request?
This PR fixes an issue that `UISeleniumSuite` in `sql/hive-thriftserver` doesn't work even though the ignored test is enabled due to the following two reasons.
(1) The suite waits for thriftserver starting up by reading a startup message from stdin but the expected message is never read.
(2) The URL and CSS selector for test are wrong.
To resolve (1), this PR adopt the way that `HiveThriftServer2Suite` does.
3f8ec0dae4/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala (L1222-L1248)
This PR also enables the ignored test. Let's disable it again in the following PR if it's still flaky.
### Why are the changes needed?
Bug fix.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
CIs.
Closes#33741 from sarutak/fix-thrift-uiseleniumsuite.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
Add PlanStability suite for TPCH
### Why are the changes needed?
Add PlanStability suite for TPCH
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added UT
Closes#33736 from AngersZhuuuu/SPARK-35991.
Lead-authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Co-authored-by: AngersZhuuuu <angers.zhu@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR proposes to support raw string literal which escape no character using `\`.
The raw string literal is the form of `r"..."` or `r'...'` like the syntax BigQuery and Python supports.
Actually, there is no standard way to represent raw string literals.
In PostgreSQL, any special character isn't escaped by \ unless a string literal starts with E prefix.
https://www.postgresql.org/docs/13/sql-syntax-lexical.html#SQL-SYNTAX-CONSTANTS
In MySQL, special characters in a string literal are not escaped if NO_BACKSLASH_ESCAPES is enabled.
https://dev.mysql.com/doc/refman/8.0/en/string-literals.html
In MsSQLServer, any special character isn't escaped by \ but STRING_ESCAPE function can escape such characters.
https://docs.microsoft.com/en-us/sql/t-sql/functions/string-escape-transact-sql?view=sql-server-ver15
But BigQuery supports `r"..."` and `r'...'` forms so this PR proposes this syntax for the purpose.
https://cloud.google.com/bigquery/docs/reference/standard-sql/lexical#literals
### Why are the changes needed?
In the current master, sometimes it's too confusable to represent JSON and regex in a string literal if they contain backslash.
For example, in JSON, `\` needs to be escaped like as follows.
```
{"a": "\\"}
```
But, if the JSON above is represented in a string literal, further two `\` are needed because string literal also requires `\` to be escaped.
```
SELECT from_json('{"a": "\\\\"}', 'a string')
{"a":"\"}
```
With the raw string literal, we can represent such JSON like as follows.
```
SELECT from_json(r'{"a": "\\"}', 'a string')
{"a":"\"}
```
### Does this PR introduce _any_ user-facing change?
No. This PR just extends the existing syntax.
### How was this patch tested?
Added new test.
I also confirmed that the modified document is successfully built with `SKIP_API=1 bundle exec jekyll build`.
Closes#33599 from sarutak/raw-string-literal.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This is a followup of https://github.com/apache/spark/pull/30648
ANALYZE TABLE and TABLES are essentially the same command, it's weird to put them in 2 different doc pages. This PR proposes to merge them into one doc page.
### Why are the changes needed?
simplify the doc
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
N/A
Closes#33781 from cloud-fan/doc.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This log should at least be WARN not INFO (in org/apache/spark/sql/execution/datasources/BasicWriteStatsTracker.scala )
"Expected $numSubmittedFiles files, but only saw $numFiles."
### Why are the changes needed?
INFO logs don't indicate possible issue but WARN logs should
### Does this PR introduce any user-facing change?
Yes, Log level changed.
### How was this patch tested?
manual, trivial change
Closes#33332 from tooptoop4/warn.
Authored-by: tooptoop4 <33283496+tooptoop4@users.noreply.github.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to fix the behavior of `astype` for `CategoricalDtype` to follow pandas 1.3.
**Before:**
```python
>>> pcat
0 a
1 b
2 c
dtype: category
Categories (3, object): ['a', 'b', 'c']
>>> pcat.astype(CategoricalDtype(["b", "c", "a"]))
0 a
1 b
2 c
dtype: category
Categories (3, object): ['b', 'c', 'a']
```
**After:**
```python
>>> pcat
0 a
1 b
2 c
dtype: category
Categories (3, object): ['a', 'b', 'c']
>>> pcat.astype(CategoricalDtype(["b", "c", "a"]))
0 a
1 b
2 c
dtype: category
Categories (3, object): ['a', 'b', 'c'] # CategoricalDtype is not updated if dtype is the same
```
`CategoricalDtype` is treated as a same `dtype` if the unique values are the same.
```python
>>> pcat1 = pser.astype(CategoricalDtype(["b", "c", "a"]))
>>> pcat2 = pser.astype(CategoricalDtype(["a", "b", "c"]))
>>> pcat1.dtype == pcat2.dtype
True
```
### Why are the changes needed?
We should follow the latest pandas as much as possible.
### Does this PR introduce _any_ user-facing change?
Yes, the behavior is changed as example in the PR description.
### How was this patch tested?
Unittest
Closes#33757 from itholic/SPARK-36368.
Authored-by: itholic <haejoon.lee@databricks.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
### What changes were proposed in this pull request?
This PR is followup for https://github.com/apache/spark/pull/33646 to add missing tests.
### Why are the changes needed?
Some tests are missing
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unittest
Closes#33776 from itholic/SPARK-36388-followup.
Authored-by: itholic <haejoon.lee@databricks.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
### What changes were proposed in this pull request?
The main change of this pr is converting an int literal to a long literal to avoid potential integer multiplications overflow risk.
For example:
**Before**
```java
void f(int i) {
long val = 65536 * i;
}
```
**After**
```java
void f(int i) {
long val = 65536L * i;
}
```
### Why are the changes needed?
Avoid potential integer multiplications overflow risk
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#33629 from LuciferYang/cast-to-long.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
The implement of https://github.com/apache/spark/pull/33665 make `make_timestamp` could accepts integer type as the seconds parameter.
This PR let `make_timestamp` accepts `decimal(16,6)` type as the seconds parameter and cast integer to `decimal(16,6)` is safe, so we can simplify the code.
### Why are the changes needed?
Simplify `make_timestamp`.
### Does this PR introduce _any_ user-facing change?
'No'.
### How was this patch tested?
New tests.
Closes#33775 from beliefer/SPARK-36428-followup.
Lead-authored-by: gengjiaan <gengjiaan@360.cn>
Co-authored-by: Jiaan Geng <beliefer@163.com>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
### What changes were proposed in this pull request?
Instead of exiting the executor within the RpcEnv's thread, exit the executor in a separate thread.
### Why are the changes needed?
The current exit way in `onDisconnected` can cause the deadlock, which has the exact same root cause with https://github.com/apache/spark/pull/12012:
* `onDisconnected` -> `System.exit` are called in sequence in the thread of `MessageLoop.threadpool`
* `System.exit` triggers shutdown hooks and `executor.stop` is one of the hooks.
* `executor.stop` stops the `Dispatcher`, which waits for the `MessageLoop.threadpool` to shutdown further.
* Thus, the thread which runs `System.exit` waits for hooks to be done, but the `MessageLoop.threadpool` in the hook waits that thread to finish. Finally, this mutual dependence results in the deadlock.
### Does this PR introduce _any_ user-facing change?
Yes, the executor shutdown won't hang.
### How was this patch tested?
Pass existing tests.
Closes#33759 from Ngone51/fix-executor-shutdown-hang.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Because SPARK-35863 Upgrade Ivy to 2.5.0, it supports skip searching the source and doc pom, but the remote repo will still be queried at present.
### Why are the changes needed?
Can improve the speed of some UT, such as `IsolatedClientLoader#downloadVersion`, no need to find source and doc pom
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
manual UT
Closes#33678 from cxzl25/SPARK-36451.
Authored-by: sychen <sychen@ctrip.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR upgrades Caffeine to `2.9.2`.
Caffeine was introduced in SPARK-34309 (#31517). At the time that PR was opened, the latest version of caffeine was `2.9.1` but now `2.9.2` is available.
### Why are the changes needed?
`2.9.2` have the following improvements (https://github.com/ben-manes/caffeine/releases/tag/v2.9.2).
* Fixed reading an intermittent null weak/soft value during a concurrent write
* Fixed extraneous eviction when concurrently removing a collected entry after a writer resurrects it with a new mapping
* Fixed excessive retries of discarding an expired entry when the fixed duration period is extended, thereby resurrecting it
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
CIs.
Closes#33772 from sarutak/upgrade-caffeine-2.9.2.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
This is a follow-up of #33687.
Use `LooseVersion` instead of `pkg_resources.parse_version`.
### Why are the changes needed?
In the previous PR, `pkg_resources.parse_version` was used, but we should use `LooseVersion` instead to be consistent in the code base.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing tests.
Closes#33768 from ueshin/issues/SPARK-36370/LooseVersion.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Refine the SQL reference doc:
- remove useless subitems in the sidebar
- remove useless sub-menu-pages (e.g. `sql-ref-syntax-aux.md`)
- avoid using `#####` in `sql-ref-literals.md`
### Why are the changes needed?
The subitems in the sidebar are quite useless, as the menu page serves the same functionalities:
<img width="1040" alt="WX20210817-2358402x" src="https://user-images.githubusercontent.com/3182036/129765924-d7e69bc1-e351-4581-a6de-f2468022f372.png">
It's also extra work to keep the manu page and sidebar subitems in sync (The ANSI compliance page is already out of sync).
The sub-menu-pages are only referenced by the sidebar, and duplicates the content of the menu page. As a result, the `sql-ref-syntax-aux.md` is already outdated compared to the menu page. It's easier to just look at the menu page.
The `#####` is not rendered properly:
<img width="776" alt="WX20210818-0001192x" src="https://user-images.githubusercontent.com/3182036/129766760-6f385443-e597-44aa-888d-14d128d45f84.png">
It's better to avoid using it.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
N/A
Closes#33767 from cloud-fan/doc.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Suggesting to refactor the way the _builtin_table is defined in the `python/pyspark/pandas/groupby.py` module.
Pandas has recently refactored the way we import the _builtin_table and is now part of the pandas.core.common module instead of being an attribute of the pandas.core.base.SelectionMixin class.
### Why are the changes needed?
This change is not fully needed but the current implementation redefines this table within pyspark, so any changes of this table from the pandas library would need to be updated in the pyspark repository as well.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Ran the following command successfully :
```sh
python/run-tests --testnames 'pyspark.pandas.tests.test_groupby'
```
Tests passed in 327 seconds
Closes#33687 from Cedric-Magnan/_builtin_table_from_pandas.
Authored-by: Cedric-Magnan <cedric.magnan@artefact.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
