Bug: NPE for bucketed write (ReadwriterTests.test_bucketed_write)
Status: Resolved | Priority: Major | Resolution: Fixed
Created: 12/Jan/23 02:37
Affects Version/s: 3.4.0



{code}
java.util.NoSuchElementException
	at java.util.AbstractList$Itr.next(AbstractList.java:364)
	at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:46)
	at scala.collection.IterableLike.head(IterableLike.scala:109)
	at scala.collection.IterableLike.head$(IterableLike.scala:108)
	at scala.collection.AbstractIterable.head(Iterable.scala:56)
	at org.apache.spark.sql.connect.planner.SparkConnectPlanner.handleWriteOperation(SparkConnectPlanner.scala:1411)
	at org.apache.spark.sql.connect.planner.SparkConnectPlanner.process(SparkConnectPlanner.scala:1297)
	at org.apache.spark.sql.connect.service.SparkConnectStreamHandler.handleCommand(SparkConnectStreamHandler.scala:182)
	at org.apache.spark.sql.connect.service.SparkConnectStreamHandler.handle(SparkConnectStreamHandler.scala:48)
	at org.apache.spark.sql.connect.service.SparkConnectService.executePlan(SparkConnectService.scala:135)
	at org.apache.spark.connect.proto.SparkConnectServiceGrpc$MethodHandlers.invoke(SparkConnectServiceGrpc.java:306)
	at org.sparkproject.connect.grpc.stub.ServerCalls$UnaryServerCallHandler$UnaryServerCallListener.onHalfClose(ServerCalls.java:182)
	at org.sparkproject.connect.grpc.internal.ServerCallImpl$ServerStreamListenerImpl.halfClosed(ServerCallImpl.java:352)
	at org.sparkproject.connect.grpc.internal.ServerImpl$JumpToApplicationThreadServerStreamListener$1HalfClosed.runInContext(ServerImpl.java:866)
	at org.sparkproject.connect.grpc.internal.ContextRunnable.run(ContextRunnable.java:37)
	at org.sparkproject.connect.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:133)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748)
23/01/12 11:27:45 ERROR SerializingExecutor: Exception while executing runnable org.sparkproject.connect.grpc.internal.ServerImpl$JumpToApplicationThreadServerStreamListener$1HalfClosed@6c9d5784
java.lang.NullPointerException
	at org.sparkproject.connect.google_protos.rpc.Status$Builder.setMessage(Status.java:783)
	at org.apache.spark.sql.connect.service.SparkConnectService$$anonfun$handleError$1.applyOrElse(SparkConnectService.scala:112)
	at org.apache.spark.sql.connect.service.SparkConnectService$$anonfun$handleError$1.applyOrElse(SparkConnectService.scala:85)
	at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
	at org.apache.spark.sql.connect.service.SparkConnectService.executePlan(SparkConnectService.scala:136)
	at org.apache.spark.connect.proto.SparkConnectServiceGrpc$MethodHandlers.invoke(SparkConnectServiceGrpc.java:306)
	at org.sparkproject.connect.grpc.stub.ServerCalls$UnaryServerCallHandler$UnaryServerCallListener.onHalfClose(ServerCalls.java:182)
	at org.sparkproject.connect.grpc.internal.ServerCallImpl$ServerStreamListenerImpl.halfClosed(ServerCallImpl.java:352)
	at org.sparkproject.connect.grpc.internal.ServerImpl$JumpToApplicationThreadServerStreamListener$1HalfClosed.runInContext(ServerImpl.java:866)
	at org.sparkproject.connect.grpc.internal.ContextRunnable.run(ContextRunnable.java:37)
	at org.sparkproject.connect.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:133)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748)

pyspark/sql/tests/test_readwriter.py:102 (ReadwriterParityTests.test_bucketed_write)
self = <pyspark.sql.tests.connect.test_parity_readwriter.ReadwriterParityTests testMethod=test_bucketed_write>

    def test_bucketed_write(self):
        data = [
            (1, "foo", 3.0),
            (2, "foo", 5.0),
            (3, "bar", -1.0),
            (4, "bar", 6.0),
        ]
        df = self.spark.createDataFrame(data, ["x", "y", "z"])
    
        def count_bucketed_cols(names, table="pyspark_bucket"):
            """Given a sequence of column names and a table name
            query the catalog and return number o columns which are
            used for bucketing
            """
            cols = self.spark.catalog.listColumns(table)
            num = len([c for c in cols if c.name in names and c.isBucket])
            return num
    
        with self.table("pyspark_bucket"):
            # Test write with one bucketing column
>           df.write.bucketBy(3, "x").mode("overwrite").saveAsTable("pyspark_bucket")

../test_readwriter.py:123: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../../connect/readwriter.py:381: in saveAsTable
    self._spark.client.execute_command(self._write.command(self._spark.client))
../../connect/client.py:478: in execute_command
    self._execute(req)
../../connect/client.py:562: in _execute
    self._handle_error(rpc_error)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <pyspark.sql.connect.client.SparkConnectClient object at 0x7fe0d069b5b0>
rpc_error = <_MultiThreadedRendezvous of RPC that terminated with:
	status = StatusCode.UNKNOWN
	details = ""
	debug_error_string ...ved from peer ipv6:%5B::1%5D:15002 {created_time:"2023-01-12T11:27:45.816172+09:00", grpc_status:2, grpc_message:""}"
>

    def _handle_error(self, rpc_error: grpc.RpcError) -> NoReturn:
        """
        Error handling helper for dealing with GRPC Errors. On the server side, certain
        exceptions are enriched with additional RPC Status information. These are
        unpacked in this function and put into the exception.
    
        To avoid overloading the user with GRPC errors, this message explicitly
        swallows the error context from the call. This GRPC Error is logged however,
        and can be enabled.
    
        Parameters
        ----------
        rpc_error : grpc.RpcError
           RPC Error containing the details of the exception.
    
        Returns
        -------
        Throws the appropriate internal Python exception.
        """
        logger.exception("GRPC Error received")
        # We have to cast the value here because, a RpcError is a Call as well.
        # https://grpc.github.io/grpc/python/grpc.html#grpc.UnaryUnaryMultiCallable.__call__
        status = rpc_status.from_call(cast(grpc.Call, rpc_error))
        if status:
            for d in status.details:
                if d.Is(error_details_pb2.ErrorInfo.DESCRIPTOR):
                    info = error_details_pb2.ErrorInfo()
                    d.Unpack(info)
                    if info.reason == "org.apache.spark.sql.AnalysisException":
                        raise SparkConnectAnalysisException(
                            info.reason, info.metadata["message"], info.metadata["plan"]
                        ) from None
                    else:
                        raise SparkConnectException(status.message, info.reason) from None
    
            raise SparkConnectException(status.message) from None
        else:
>           raise SparkConnectException(str(rpc_error)) from None
E           pyspark.sql.connect.client.SparkConnectException: <_MultiThreadedRendezvous of RPC that terminated with:
E           	status = StatusCode.UNKNOWN
E           	details = ""
E           	debug_error_string = "UNKNOWN:Error received from peer ipv6:%5B::1%5D:15002 {created_time:"2023-01-12T11:27:45.816172+09:00", grpc_status:2, grpc_message:""}"
E           >

../../connect/client.py:640: SparkConnectException

{code}