Update upstream by GulajavaMinistudio · Pull Request #2 · GulajavaMinistudio/spark

GulajavaMinistudio · 2017-03-30T02:00:59Z

What changes were proposed in this pull request?

(Please fill in changes proposed in this fix)

How was this patch tested?

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
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Please review http://spark.apache.org/contributing.html before opening a pull request.

…ver side metric updates ## What changes were proposed in this pull request? It is not super intuitive how to update SQLMetric on the driver side. This patch introduces a new SQLMetrics.postDriverMetricUpdates function to do that, and adds documentation to make it more obvious. ## How was this patch tested? Updated a test case to use this method. Author: Reynold Xin <rxin@databricks.com> Closes #17464 from rxin/SPARK-20134.

This change modifies the way block data is encrypted to make the more common cases faster, while penalizing an edge case. As a side effect of the change, all data that goes through the block manager is now encrypted only when needed, including the previous path (broadcast variables) where that did not happen. The way the change works is by not encrypting data that is stored in memory; so if a serialized block is in memory, it will only be encrypted once it is evicted to disk. The penalty comes when transferring that encrypted data from disk. If the data ends up in memory again, it is as efficient as before; but if the evicted block needs to be transferred directly to a remote executor, then there's now a performance penalty, since the code now uses a custom FileRegion implementation to decrypt the data before transferring. This also means that block data transferred between executors now is not encrypted (and thus relies on the network library encryption support for secrecy). Shuffle blocks are still transferred in encrypted form, since they're handled in a slightly different way by the code. This also keeps compatibility with existing external shuffle services, which transfer encrypted shuffle blocks, and avoids having to make the external service aware of encryption at all. The serialization and deserialization APIs in the SerializerManager now do not do encryption automatically; callers need to explicitly wrap their streams with an appropriate crypto stream before using those. As a result of these changes, some of the workarounds added in SPARK-19520 are removed here. Testing: a new trait ("EncryptionFunSuite") was added that provides an easy way to run a test twice, with encryption on and off; broadcast, block manager and caching tests were modified to use this new trait so that the existing tests exercise both encrypted and non-encrypted paths. I also ran some applications with encryption turned on to verify that they still work, including streaming tests that failed without the fix for SPARK-19520. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #17295 from vanzin/SPARK-19556.

…ovider ## What changes were proposed in this pull request? Currently we use system classloader to find HBase jars, if it is specified by `--jars`, then it will be failed with ClassNotFound issue. So here changing to use child classloader. Also putting added jars and main jar into classpath of submitted application in yarn cluster mode, otherwise HBase jars specified with `--jars` will never be honored in cluster mode, and fetching tokens in client side will always be failed. ## How was this patch tested? Unit test and local verification. Author: jerryshao <sshao@hortonworks.com> Closes #17388 from jerryshao/SPARK-20059.

## What changes were proposed in this pull request? Allow Jenkins Python tests to use the installed conda to test Python 2.7 support & test pip installability. ## How was this patch tested? Updated shell scripts, ran tests locally with installed conda, ran tests in Jenkins. Author: Holden Karau <holden@us.ibm.com> Closes #17355 from holdenk/SPARK-19955-support-python-tests-with-conda.

…n listeners ## What changes were proposed in this pull request? Bugfix from [SPARK-19540.](#16826) Cloning SessionState does not clone query execution listeners, so cloned session is unable to listen to events on queries. ## How was this patch tested? - Unit test Author: Kunal Khamar <kkhamar@outlook.com> Closes #17379 from kunalkhamar/clone-bugfix.

…ns.from_json ## What changes were proposed in this pull request? This pr added `StructType.fromDDL` to convert a DDL format string into `StructType` for defining schemas in `functions.from_json`. ## How was this patch tested? Added tests in `JsonFunctionsSuite`. Author: Takeshi Yamamuro <yamamuro@apache.org> Closes #17406 from maropu/SPARK-20009.

### What changes were proposed in this pull request? `FalseLiteral` and `TrueLiteral` should have been eliminated by optimizer rule `BooleanSimplification`, but null literals might be added by optimizer rule `NullPropagation`. For safety, our filter estimation should handle all the eligible literal cases. Our optimizer rule BooleanSimplification is unable to remove the null literal in many cases. For example, `a < 0 or null`. Thus, we need to handle null literal in filter estimation. `Not` can be pushed down below `And` and `Or`. Then, we could see two consecutive `Not`, which need to be collapsed into one. Because of the limited expression support for filter estimation, we just need to handle the case `Not(null)` for avoiding incorrect error due to the boolean operation on null. For details, see below matrix. ``` not NULL = NULL NULL or false = NULL NULL or true = true NULL or NULL = NULL NULL and false = false NULL and true = NULL NULL and NULL = NULL ``` ### How was this patch tested? Added the test cases. Author: Xiao Li <gatorsmile@gmail.com> Closes #17446 from gatorsmile/constantFilterEstimation.

## What changes were proposed in this pull request? It is similar to Hive silent mode, just show the query result. see: [Hive LanguageManual+Cli](https://cwiki.apache.org/confluence/display/Hive/LanguageManual+Cli) and [the implementation of Hive silent mode](https://github.com/apache/hive/blob/release-1.2.1/ql/src/java/org/apache/hadoop/hive/ql/session/SessionState.java#L948-L950). This PR set the Logger level to `WARN` to get similar result. ## How was this patch tested? manual tests ![manual test spark sql silent mode](https://cloud.githubusercontent.com/assets/5399861/24390165/989b7780-13b9-11e7-8496-6e68f55757e3.gif) Author: Yuming Wang <wgyumg@gmail.com> Closes #17449 from wangyum/SPARK-20120.

## What changes were proposed in this pull request? Commit 6c70a38 broke the build for scala 2.10. The commit uses some reflections which are not available in Scala 2.10. This PR fixes them. ## How was this patch tested? Existing tests. Author: Takuya UESHIN <ueshin@databricks.com> Closes #17473 from ueshin/issues/SPARK-19088.

## What changes were proposed in this pull request? The column comment was missing while constructing the Hive TableSchema. This fix will preserve the original comment. ## How was this patch tested? I have added a new test case to test the column with/without comment. Author: bomeng <bmeng@us.ibm.com> Closes #17470 from bomeng/SPARK-20146.

## What changes were proposed in this pull request? There were two related fixes regarding `from_json`, `get_json_object` and `json_tuple` ([Fix #1](apache@c8803c0), [Fix #2](apache@86174ea)), but they weren't comprehensive it seems. I wanted to extend those fixes to all the parsers, and add tests for each case. ## How was this patch tested? Regression tests Author: Burak Yavuz <brkyvz@gmail.com> Closes apache#20302 from brkyvz/json-invfix.

### What changes were proposed in this pull request? `org.apache.spark.sql.kafka010.KafkaDelegationTokenSuite` failed lately. After had a look at the logs it just shows the following fact without any details: ``` Caused by: sbt.ForkMain$ForkError: sun.security.krb5.KrbException: Server not found in Kerberos database (7) - Server not found in Kerberos database ``` Since the issue is intermittent and not able to reproduce it we should add more debug information and wait for reproduction with the extended logs. ### Why are the changes needed? Failing test doesn't give enough debug information. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? I've started the test manually and checked that such additional debug messages show up: ``` >>> KrbApReq: APOptions are 00000000 00000000 00000000 00000000 >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Looking for keys for: kafka/localhostEXAMPLE.COM Added key: 17version: 0 Added key: 23version: 0 Added key: 16version: 0 Found unsupported keytype (3) for kafka/localhostEXAMPLE.COM >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Using builtin default etypes for permitted_enctypes default etypes for permitted_enctypes: 17 16 23. >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType MemoryCache: add 1571936500/174770/16C565221B70AAB2BEFE31A83D13A2F4/client/localhostEXAMPLE.COM to client/localhostEXAMPLE.COM|kafka/localhostEXAMPLE.COM MemoryCache: Existing AuthList: #3: 1571936493/200803/8CD70D280B0862C5DA1FF901ECAD39FE/client/localhostEXAMPLE.COM #2: 1571936499/985009/BAD33290D079DD4E3579A8686EC326B7/client/localhostEXAMPLE.COM #1: 1571936499/995208/B76B9D78A9BE283AC78340157107FD40/client/localhostEXAMPLE.COM ``` Closes apache#26252 from gaborgsomogyi/SPARK-29580. Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>

### What changes were proposed in this pull request? fix the error caused by interval output in ExtractBenchmark ### Why are the changes needed? fix a bug in the test ```scala [info] Running case: cast to interval [error] Exception in thread "main" org.apache.spark.sql.AnalysisException: Cannot use interval type in the table schema.;; [error] OverwriteByExpression RelationV2[] noop-table, true, true [error] +- Project [(subtractdates(cast(cast(id#0L as timestamp) as date), -719162) + subtracttimestamps(cast(id#0L as timestamp), -30610249419876544)) AS ((CAST(CAST(id AS TIMESTAMP) AS DATE) - DATE '0001-01-01') + (CAST(id AS TIMESTAMP) - TIMESTAMP '1000-01-01 01:02:03.123456'))#2] [error] +- Range (1262304000, 1272304000, step=1, splits=Some(1)) [error] [error] at org.apache.spark.sql.catalyst.util.TypeUtils$.failWithIntervalType(TypeUtils.scala:106) [error] at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis$25(CheckAnalysis.scala:389) [error] at org.a ``` ### Does this PR introduce any user-facing change? no ### How was this patch tested? re-run benchmark Closes apache#27867 from yaooqinn/SPARK-31111. Authored-by: Kent Yao <yaooqinn@hotmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>

…chmarks ### What changes were proposed in this pull request? Replace `CAST(... AS TIMESTAMP` by `TIMESTAMP_SECONDS` in the following benchmarks: - ExtractBenchmark - DateTimeBenchmark - FilterPushdownBenchmark - InExpressionBenchmark ### Why are the changes needed? The benchmarks fail w/o the changes: ``` [info] Running benchmark: datetime +/- interval [info] Running case: date + interval(m) [error] Exception in thread "main" org.apache.spark.sql.AnalysisException: cannot resolve 'CAST(`id` AS TIMESTAMP)' due to data type mismatch: cannot cast bigint to timestamp,you can enable the casting by setting spark.sql.legacy.allowCastNumericToTimestamp to true,but we strongly recommend using function TIMESTAMP_SECONDS/TIMESTAMP_MILLIS/TIMESTAMP_MICROS instead.; line 1 pos 5; [error] 'Project [(cast(cast(id#0L as timestamp) as date) + 1 months) AS (CAST(CAST(id AS TIMESTAMP) AS DATE) + INTERVAL '1 months')#2] [error] +- Range (0, 10000000, step=1, splits=Some(1)) ``` ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running the affected benchmarks. Closes apache#28843 from MaxGekk/GuoPhilipse-31710-fix-compatibility-followup. Authored-by: Max Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>

…e are foldable boolean types ### What changes were proposed in this pull request? Improve `SimplifyConditionals`. Simplify `If(cond, TrueLiteral, FalseLiteral)` to `cond`. Simplify `If(cond, FalseLiteral, TrueLiteral)` to `Not(cond)`. The use case is: ```sql create table t1 using parquet as select id from range(10); select if (id > 2, false, true) from t1; ``` Before this pr: ``` == Physical Plan == *(1) Project [if ((id#1L > 2)) false else true AS (IF((id > CAST(2 AS BIGINT)), false, true))#2] +- *(1) ColumnarToRow +- FileScan parquet default.t1[id#1L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/opensource/spark/spark-warehouse/org.apache.spark.sql.DataF..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<id:bigint> ``` After this pr: ``` == Physical Plan == *(1) Project [(id#1L <= 2) AS (IF((id > CAST(2 AS BIGINT)), false, true))#2] +- *(1) ColumnarToRow +- FileScan parquet default.t1[id#1L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/opensource/spark/spark-warehouse/org.apache.spark.sql.DataF..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<id:bigint> ``` ### 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 apache#30849 from wangyum/SPARK-33798-2. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>

### What changes were proposed in this pull request? This PR intends to fix flaky GitHub Actions (GA) tests below in `transform.sql` (this flakiness does not seem to happen in the Jenkins tests): - https://github.com/apache/spark/runs/1592987501 - https://github.com/apache/spark/runs/1593196242 - https://github.com/apache/spark/runs/1595496305 - https://github.com/apache/spark/runs/1596309555 This is because the error message is different between test runs in GA (the error message seems to be truncated indeterministically) ,e.g., ``` # https://github.com/apache/spark/runs/1592987501 Expected "...h status 127. Error:[ /bin/bash: some_non_existent_command: command not found]", but got "...h status 127. Error:[]" Result did not match for query #2 # https://github.com/apache/spark/runs/1593196242 Expected "...istent_command: comm[and not found]", but got "...istent_command: comm[]" Result did not match for query #2 ``` The root cause of this indeterministic behaviour happening only in GA is not clear though, this test throws SparkException consistently even in GA. So, this PR proposes to make the test just check if it will be thrown when running it. This PR comes from the dongjoon-hyun comment: https://github.com/apache/spark/pull/29414/files#r547414513 ### Why are the changes needed? Bugfix. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Added tests. Closes apache#30896 from maropu/SPARK-32106-FOLLOWUP. Authored-by: Takeshi Yamamuro <yamamuro@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>

…pendently in Scala 2.13 ### What changes were proposed in this pull request? Similar to SPARK-35532, the main change of this pr is add `scala-2.13` profile to external/kafka-0-10-sql/pom.xml, external/avro/pom.xml and sql/hive-thriftserver/pom.xml, the `scala-2.13` profile include dependency on `scala-parallel-collections_2.13`, then all(34) spark modules can maven test independently. ### Why are the changes needed? Ensure alll(34) spark modules can be maven test independently in Scala 2.13 ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? - Pass the GitHub Action Scala 2.13 job - Manual test： 1. Execute ``` dev/change-scala-version.sh 2.13 mvn clean install -DskipTests -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13 ``` 2. maven test `external/kafka-0-10-sql` module ``` mvn test -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13 -pl external/kafka-0-10-sql ``` **before** ``` Discovery starting. Discovery completed in 857 milliseconds. Run starting. Expected test count is: 464 ... KafkaRelationSuiteV2: - explicit earliest to latest offsets - default starting and ending offsets - explicit offsets - default starting and ending offsets with headers - timestamp provided for starting and ending - timestamp provided for starting, offset provided for ending - timestamp provided for ending, offset provided for starting - timestamp provided for starting, ending not provided - timestamp provided for ending, starting not provided - global timestamp provided for starting and ending - no matched offset for timestamp - startingOffsets - preferences on offset related options - no matched offset for timestamp - endingOffsets *** RUN ABORTED *** java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.SparkContext.withScope(SparkContext.scala:788) at org.apache.spark.SparkContext.union(SparkContext.scala:1405) at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:182) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:220) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:217) ... Cause: java.lang.ClassNotFoundException: scala.collection.parallel.TaskSupport at java.net.URLClassLoader.findClass(URLClassLoader.java:382) at java.lang.ClassLoader.loadClass(ClassLoader.java:418) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352) at java.lang.ClassLoader.loadClass(ClassLoader.java:351) at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.SparkContext.withScope(SparkContext.scala:788) at org.apache.spark.SparkContext.union(SparkContext.scala:1405) at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697) ... ``` **After** ``` Run completed in 33 minutes, 51 seconds. Total number of tests run: 464 Suites: completed 31, aborted 0 Tests: succeeded 464, failed 0, canceled 0, ignored 0, pending 0 All tests passed. ``` 3. maven test `external/avro` module ``` mvn test -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13 -pl external/avro ``` **before** ``` Discovery starting. Discovery completed in 2 seconds, 765 milliseconds. Run starting. Expected test count is: 255 AvroReadSchemaSuite: - append column at the end - hide column at the end - append column into middle - hide column in the middle - add a nested column at the end of the leaf struct column - add a nested column in the middle of the leaf struct column - add a nested column at the end of the middle struct column - add a nested column in the middle of the middle struct column - hide a nested column at the end of the leaf struct column - hide a nested column in the middle of the leaf struct column - hide a nested column at the end of the middle struct column - hide a nested column in the middle of the middle struct column *** RUN ABORTED *** java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.SparkContext.withScope(SparkContext.scala:788) at org.apache.spark.SparkContext.union(SparkContext.scala:1405) at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:182) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:220) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:217) ... Cause: java.lang.ClassNotFoundException: scala.collection.parallel.TaskSupport at java.net.URLClassLoader.findClass(URLClassLoader.java:382) at java.lang.ClassLoader.loadClass(ClassLoader.java:418) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352) at java.lang.ClassLoader.loadClass(ClassLoader.java:351) at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.SparkContext.withScope(SparkContext.scala:788) at org.apache.spark.SparkContext.union(SparkContext.scala:1405) at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697) ... ``` **After** ``` Run completed in 1 minute, 42 seconds. Total number of tests run: 255 Suites: completed 12, aborted 0 Tests: succeeded 255, failed 0, canceled 0, ignored 2, pending 0 All tests passed. ``` 4. maven test `sql/hive-thriftserver` module ``` mvn test -Phadoop-3.2 -Phive-2.3 -Phadoop-cloud -Pmesos -Pyarn -Pkinesis-asl -Phive-thriftserver -Pspark-ganglia-lgpl -Pkubernetes -Phive -Pscala-2.13 -pl sql/hive-thriftserver ``` **before** ``` - union.sql *** FAILED *** "1 a 1 a 2 b 2 b" did not contain "Exception" Exception did not match for query #2 SELECT * FROM (SELECT * FROM t1 UNION ALL SELECT * FROM t1), expected: 1 a 1 a 2 b 2 b, but got: java.sql.SQLException org.apache.hive.service.cli.HiveSQLException: Error running query: java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport at org.apache.spark.sql.hive.thriftserver.HiveThriftServerErrors$.runningQueryError(HiveThriftServerErrors.scala:38) at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.org$apache$spark$sql$hive$thriftserver$SparkExecuteStatementOperation$$execute(SparkExecuteStatementOperation.scala:324) at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.$anonfun$run$2(SparkExecuteStatementOperation.scala:229) at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18) at org.apache.spark.sql.hive.thriftserver.SparkOperation.withLocalProperties(SparkOperation.scala:79) at org.apache.spark.sql.hive.thriftserver.SparkOperation.withLocalProperties$(SparkOperation.scala:63) at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.withLocalProperties(SparkExecuteStatementOperation.scala:43) at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.run(SparkExecuteStatementOperation.scala:229) at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.run(SparkExecuteStatementOperation.scala:224) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:422) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1878) at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2.run(SparkExecuteStatementOperation.scala:238) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Caused by: java.lang.NoClassDefFoundError: scala/collection/parallel/TaskSupport at org.apache.spark.SparkContext.$anonfun$union$1(SparkContext.scala:1411) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.SparkContext.withScope(SparkContext.scala:788) at org.apache.spark.SparkContext.union(SparkContext.scala:1405) at org.apache.spark.sql.execution.UnionExec.doExecute(basicPhysicalOperators.scala:697) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:182) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:220) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:217) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:178) at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:323) at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:389) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3719) at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2987) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3710) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:774) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3708) at org.apache.spark.sql.Dataset.collect(Dataset.scala:2987) at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.org$apache$spark$sql$hive$thriftserver$SparkExecuteStatementOperation$$execute(SparkExecuteStatementOperation.scala:299) ... 16 more Caused by: java.lang.ClassNotFoundException: scala.collection.parallel.TaskSupport at java.net.URLClassLoader.findClass(URLClassLoader.java:382) at java.lang.ClassLoader.loadClass(ClassLoader.java:418) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352) at java.lang.ClassLoader.loadClass(ClassLoader.java:351) ... 40 more (ThriftServerQueryTestSuite.scala:209) ``` **After** ``` Run completed in 29 minutes, 17 seconds. Total number of tests run: 535 Suites: completed 20, aborted 0 Tests: succeeded 535, failed 0, canceled 0, ignored 17, pending 0 All tests passed. ``` Closes apache#32994 from LuciferYang/SPARK-35838. Authored-by: YangJie <yangjie01@baidu.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>

…iEnabled in 'cast string to date #2' ### What changes were proposed in this pull request? This PR fixes the test to make `CastWithAnsiOffSuite` properly respect `ansiEnabled` in `cast string to date #2` test by using `CastWithAnsiOffSuite.cast` instead of `Cast` expression. ### Why are the changes needed? To make the tests pass. Currently it fails when ANSI mode is on: https://github.com/apache/spark/runs/6786744647 ### Does this PR introduce _any_ user-facing change? No, test-only. ### How was this patch tested? Manually tested in my IDE. Closes apache#36802 from HyukjinKwon/SPARK-39321-followup. Authored-by: Hyukjin Kwon <gurwls223@apache.org> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>

…ly equivalent children in `RewriteDistinctAggregates` ### What changes were proposed in this pull request? In `RewriteDistinctAggregates`, when grouping aggregate expressions by function children, treat children that are semantically equivalent as the same. ### Why are the changes needed? This PR will reduce the number of projections in the Expand operator when there are multiple distinct aggregations with superficially different children. In some cases, it will eliminate the need for an Expand operator. Example: In the following query, the Expand operator creates 3\*n rows (where n is the number of incoming rows) because it has a projection for each of function children `b + 1`, `1 + b` and `c`. ``` create or replace temp view v1 as select * from values (1, 2, 3.0), (1, 3, 4.0), (2, 4, 2.5), (2, 3, 1.0) v1(a, b, c); select a, count(distinct b + 1), avg(distinct 1 + b) filter (where c > 0), sum(c) from v1 group by a; ``` The Expand operator has three projections (each producing a row for each incoming row): ``` [a#87, null, null, 0, null, UnscaledValue(c#89)], <== projection #1 (for regular aggregation) [a#87, (b#88 + 1), null, 1, null, null], <== projection #2 (for distinct aggregation of b + 1) [a#87, null, (1 + b#88), 2, (c#89 > 0.0), null]], <== projection #3 (for distinct aggregation of 1 + b) ``` In reality, the Expand only needs one projection for `1 + b` and `b + 1`, because they are semantically equivalent. With the proposed change, the Expand operator's projections look like this: ``` [a#67, null, 0, null, UnscaledValue(c#69)], <== projection #1 (for regular aggregations) [a#67, (b#68 + 1), 1, (c#69 > 0.0), null]], <== projection #2 (for distinct aggregation on b + 1 and 1 + b) ``` With one less projection, Expand produces 2\*n rows instead of 3\*n rows, but still produces the correct result. In the case where all distinct aggregates have semantically equivalent children, the Expand operator is not needed at all. Benchmark code in the JIRA (SPARK-40382). Before the PR: ``` distinct aggregates: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------------------------------ all semantically equivalent 14721 14859 195 5.7 175.5 1.0X some semantically equivalent 14569 14572 5 5.8 173.7 1.0X none semantically equivalent 14408 14488 113 5.8 171.8 1.0X ``` After the PR: ``` distinct aggregates: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------------------------------ all semantically equivalent 3658 3692 49 22.9 43.6 1.0X some semantically equivalent 9124 9214 127 9.2 108.8 0.4X none semantically equivalent 14601 14777 250 5.7 174.1 0.3X ``` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? New unit tests. Closes apache#37825 from bersprockets/rewritedistinct_issue. Authored-by: Bruce Robbins <bersprockets@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>

### What changes were proposed in this pull request? This PR introduces sasl retry count in RetryingBlockTransferor. ### Why are the changes needed? Previously a boolean variable, saslTimeoutSeen, was used. However, the boolean variable wouldn't cover the following scenario: 1. SaslTimeoutException 2. IOException 3. SaslTimeoutException 4. IOException Even though IOException at #2 is retried (resulting in increment of retryCount), the retryCount would be cleared at step #4. Since the intention of saslTimeoutSeen is to undo the increment due to retrying SaslTimeoutException, we should keep a counter for SaslTimeoutException retries and subtract the value of this counter from retryCount. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? New test is added, courtesy of Mridul. Closes apache#39611 from tedyu/sasl-cnt. Authored-by: Ted Yu <yuzhihong@gmail.com> Signed-off-by: Mridul Muralidharan <mridul<at>gmail.com>

… throw internal error ### What changes were proposed in this pull request? This PR fixes the error messages and classes when Python UDFs are used in higher order functions. ### Why are the changes needed? To show the proper user-facing exceptions with error classes. ### Does this PR introduce _any_ user-facing change? Yes, previously it threw internal error such as: ```python from pyspark.sql.functions import transform, udf, col, array spark.range(1).select(transform(array("id"), lambda x: udf(lambda y: y)(x))).collect() ``` Before: ``` py4j.protocol.Py4JJavaError: An error occurred while calling o74.collectToPython. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 15 in stage 0.0 failed 1 times, most recent failure: Lost task 15.0 in stage 0.0 (TID 15) (ip-192-168-123-103.ap-northeast-2.compute.internal executor driver): org.apache.spark.SparkException: [INTERNAL_ERROR] Cannot evaluate expression: <lambda>(lambda x_0#3L)#2 SQLSTATE: XX000 at org.apache.spark.SparkException$.internalError(SparkException.scala:92) at org.apache.spark.SparkException$.internalError(SparkException.scala:96) ``` After: ``` pyspark.errors.exceptions.captured.AnalysisException: [INVALID_LAMBDA_FUNCTION_CALL.UNEVALUABLE] Invalid lambda function call. Python UDFs should be used in a lambda function at a higher order function. However, "<lambda>(lambda x_0#3L)" was a Python UDF. SQLSTATE: 42K0D; Project [transform(array(id#0L), lambdafunction(<lambda>(lambda x_0#3L)#2, lambda x_0#3L, false)) AS transform(array(id), lambdafunction(<lambda>(lambda x_0#3L), namedlambdavariable()))#4] +- Range (0, 1, step=1, splits=Some(16)) ``` ### How was this patch tested? Unittest was added ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#47079 from HyukjinKwon/SPARK-48706. Authored-by: Hyukjin Kwon <gurwls223@apache.org> Signed-off-by: Kent Yao <yao@apache.org>

### What changes were proposed in this pull request? Fix self-join after `applyInArrow`, the same issue of `applyInPandas` was fixed in apache#31429 ### Why are the changes needed? bug fix before: ``` In [1]: import pyarrow as pa In [2]: df = spark.createDataFrame([(1, 1)], ("k", "v")) In [3]: def arrow_func(key, table): ...: return pa.Table.from_pydict({"x": [2], "y": [2]}) ...: In [4]: df2 = df.groupby("k").applyInArrow(arrow_func, schema="x long, y long") In [5]: df2.show() 24/12/04 17:47:43 WARN CheckAllocator: More than one DefaultAllocationManager on classpath. Choosing first found +---+---+ | x| y| +---+---+ | 2| 2| +---+---+ In [6]: df2.join(df2) ... Failure when resolving conflicting references in Join: 'Join Inner :- FlatMapGroupsInArrow [k#0L], arrow_func(k#0L, v#1L)#2, [x#3L, y#4L] : +- Project [k#0L, k#0L, v#1L] : +- LogicalRDD [k#0L, v#1L], false +- FlatMapGroupsInArrow [k#12L], arrow_func(k#12L, v#13L)#2, [x#3L, y#4L] +- Project [k#12L, k#12L, v#13L] +- LogicalRDD [k#12L, v#13L], false Conflicting attributes: "x", "y". SQLSTATE: XX000 at org.apache.spark.SparkException$.internalError(SparkException.scala:92) at org.apache.spark.SparkException$.internalError(SparkException.scala:79) at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$2(CheckAnalysis.scala:798) ``` after: ``` In [6]: df2.join(df2) Out[6]: DataFrame[x: bigint, y: bigint, x: bigint, y: bigint] In [7]: df2.join(df2).show() +---+---+---+---+ | x| y| x| y| +---+---+---+---+ | 2| 2| 2| 2| +---+---+---+---+ ``` ### Does this PR introduce _any_ user-facing change? bug fix ### How was this patch tested? added tests ### Was this patch authored or co-authored using generative AI tooling? no Closes apache#49056 from zhengruifeng/fix_arrow_join. Authored-by: Ruifeng Zheng <ruifengz@apache.org> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>

rxin and others added 10 commits March 29, 2017 00:02

GulajavaMinistudio merged commit ca324ef into GulajavaMinistudio:master Mar 30, 2017

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GulajavaMinistudio commented Mar 30, 2017

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