[SPARK-39176] Pyspark failed to serialize dates before 1970 in windows - ASF JIRA

Details

Type: Improvement
Status: Resolved
Priority: Major
Resolution: Fixed
Affects Version/s: 3.0.1
Fix Version/s: 3.0.1
Component/s: PySpark, Tests, Windows
Labels:

Target Version/s:

3.0.1
Language:
- Python

Description

Fix problems with pyspark in Windows

Fixed datetime conversion to timestamp before 1970;
Fixed datetime conversion when timestamp is negative;
Adding a test script.

Pyspark has problems serializing pre-1970 times in Windows

An exception occurs when executing the following code under Windows:

rdd = sc.parallelize([('a', datetime(1957, 1, 9, 0, 0)),
                      ('b', datetime(2014, 1, 27, 0, 0))])
df = spark.createDataFrame(rdd, ["id", "date"])

df.show()
df.printSchema()

print(df.collect())

  File "...\spark\python\lib\pyspark.zip\pyspark\sql\types.py", line 195, in toInternal
    else time.mktime(dt.timetuple()))
OverflowError: mktime argument out of range

at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:503)
   at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:638)
   at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:621)
   at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:456)
   at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
   at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:489)
   at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
   at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
   at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
   at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
   at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
   at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340)
   at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872)
   at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872)
   at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
   at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
   at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
   at org.apache.spark.scheduler.Task.run(Task.scala:127)
   at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
   at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
   at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
   at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
   ... 1 more

and

File ...\spark\python\lib\pyspark.zip\pyspark\sql\types.py, in fromInternal:
Line 207:   return datetime.datetime.fromtimestamp(ts // 1000000).replace(microsecond=ts % 1000000)

OSError: [Errno 22] Invalid argument