[SPARK-31710][SQL]Add compatibility flag to cast long to timestamp #6
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
As we know,long datatype is interpreted as milliseconds when conversion to timestamp in hive, while long is interpreted as seconds when conversion to timestamp in spark, we have many sqls runing in product, so we need a compatibility flag to make them migrating smoothly ,meanwhile do not change the user behavior in spark.
wxplovecc
pushed a commit
that referenced
this pull request
Aug 5, 2024
…to the `hive-thriftserver` module to fix the Maven daily test ### What changes were proposed in this pull request? This pr add bouncycastle-related test dependencies to the `hive-thrift` module to fix the Maven daily test. ### Why are the changes needed? `sql-on-files.sql` added the following statement in apache#47480, which caused the Maven daily test to fail https://github.com/apache/spark/blob/2363aec0c14ead24ade2bfa23478a4914f179c00/sql/core/src/test/resources/sql-tests/inputs/sql-on-files.sql#L10 - https://github.com/apache/spark/actions/runs/10094638521/job/27943309504 - https://github.com/apache/spark/actions/runs/10095571472/job/27943298802 ``` - sql-on-files.sql *** FAILED *** "" did not contain "Exception" Exception did not match for query #6 CREATE TABLE sql_on_files.test_orc USING ORC AS SELECT 1, expected: , but got: java.sql.SQLException org.apache.hive.service.cli.HiveSQLException: Error running query: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8542.0 failed 1 times, most recent failure: Lost task 0.0 in stage 8542.0 (TID 8594) (localhost executor driver): java.lang.NoClassDefFoundError: org/bouncycastle/jce/provider/BouncyCastleProvider at test.org.apache.spark.sql.execution.datasources.orc.FakeKeyProvider$Factory.createProvider(FakeKeyProvider.java:127) at org.apache.hadoop.crypto.key.KeyProviderFactory.get(KeyProviderFactory.java:96) at org.apache.hadoop.crypto.key.KeyProviderFactory.getProviders(KeyProviderFactory.java:68) at org.apache.orc.impl.HadoopShimsCurrent.createKeyProvider(HadoopShimsCurrent.java:97) at org.apache.orc.impl.HadoopShimsCurrent.getHadoopKeyProvider(HadoopShimsCurrent.java:131) at org.apache.orc.impl.CryptoUtils$HadoopKeyProviderFactory.create(CryptoUtils.java:158) at org.apache.orc.impl.CryptoUtils.getKeyProvider(CryptoUtils.java:141) at org.apache.orc.impl.WriterImpl.setupEncryption(WriterImpl.java:1015) at org.apache.orc.impl.WriterImpl.<init>(WriterImpl.java:164) at org.apache.orc.OrcFile.createWriter(OrcFile.java:1078) at org.apache.spark.sql.execution.datasources.orc.OrcOutputWriter.<init>(OrcOutputWriter.scala:49) at org.apache.spark.sql.execution.datasources.orc.OrcFileFormat$$anon$1.newInstance(OrcFileFormat.scala:89) at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:180) at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:165) at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:391) at org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:107) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:901) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:901) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:374) at org.apache.spark.rdd.RDD.iterator(RDD.scala:338) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93) at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:171) at org.apache.spark.scheduler.Task.run(Task.scala:146) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$5(Executor.scala:644) at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64) at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:647) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635) at java.base/java.lang.Thread.run(Thread.java:840) Caused by: java.lang.ClassNotFoundException: org.bouncycastle.jce.provider.BouncyCastleProvider at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641) at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188) at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:525) ... 32 more ``` Because we have configured `hadoop.security.key.provider.path` as `test:///` in the parent `pom.xml`, https://github.com/apache/spark/blob/5ccf9ba958f492c1eb4dde22a647ba75aba63d8e/pom.xml#L3165-L3166 `KeyProviderFactory#getProviders` will use `FakeKeyProvider$Factory` to create instances of `FakeKeyProvider`. https://github.com/apache/spark/blob/5ccf9ba958f492c1eb4dde22a647ba75aba63d8e/sql/core/src/test/resources/META-INF/services/org.apache.hadoop.crypto.key.KeyProviderFactory#L18 During the initialization of `FakeKeyProvider`, it first initializes its superclass `org.apache.hadoop.crypto.key.KeyProvider`, which leads to the loading of the `BouncyCastleProvider` class. Therefore, we need to add bouncycastle-related test dependencies in the `hive-thrift` module. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Manual Test with this pr. ``` build/mvn -Phive -Phive-thriftserver clean install -DskipTests build/mvn -Phive -Phive-thriftserver clean install -Dtest=none -DwildcardSuites=org.apache.spark.sql.hive.thriftserver.ThriftServerQueryTestSuite -pl sql/hive-thriftserver ``` ``` Run completed in 6 minutes, 52 seconds. Total number of tests run: 243 Suites: completed 2, aborted 0 Tests: succeeded 243, failed 0, canceled 0, ignored 20, pending 0 All tests passed. ``` ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#47496 from LuciferYang/thrift-bouncycastle. Authored-by: yangjie01 <yangjie01@baidu.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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?
As we know,long datatype is interpreted as milliseconds when conversion to timestamp in hive, while long is interpreted as seconds when conversion to timestamp in spark, we have been facing error data during migrating hive sql to spark sql. with compatibility flag we can fix this error,
Why are the changes needed?
we have many sqls runing in product, so we need a compatibility flag to make them migrating smoothly ,meanwhile do not change the user behavior in spark.
Does this PR introduce any user-facing change?
if user use this patch ,then user should set this paramter ,
if not, user do not need to do anything.
How was this patch tested?
unit test added