[SPARK-9643] Error serializing datetimes with timezones using Dataframes and Parquet

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 1.4.1
• Fix Version/s: 1.6.0
• Component/s: PySpark
• Labels: upgrade
• Assignee: Alex Angelini
• Reporter: Alex Angelini
• Created: 05/Aug/15 17:07
• Updated: 19/Oct/15 17:56
• Resolved: 19/Oct/15 17:07

Description

Trying to serialize a DataFrame with a datetime column that includes a timezone fails with the following error.

net.razorvine.pickle.PickleException: invalid pickle data for datetime; expected 1 or 7 args, got 2
    at net.razorvine.pickle.objects.DateTimeConstructor.createDateTime(DateTimeConstructor.java:69)
    at net.razorvine.pickle.objects.DateTimeConstructor.construct(DateTimeConstructor.java:32)
    at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:701)
    at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:171)
    at net.razorvine.pickle.Unpickler.load(Unpickler.java:85)
    at net.razorvine.pickle.Unpickler.loads(Unpickler.java:98)
    at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:151)
    at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:150)
    at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
    at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.org$apache$spark$sql$execution$datasources$InsertIntoHadoopFsRelation$$writeRows$1(commands.scala:185)
    at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$insert$1.apply(commands.scala:163)
    at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$insert$1.apply(commands.scala:163)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:64)
    at org.apache.spark.scheduler.Task.run(Task.scala:86)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

According to davies timezone serialization is done directly in Spark and not dependent on Pyrolite, but I was not able to prove that.

Upgrading to Pyrolite 4.9 fixed this issue

https://github.com/apache/spark/pull/7950

Issue Links

• links to: [Github] Pull Request #7950 (angelini)