In a pyspark SS job, trying to use sql instead of sql functions in foreachBatch sink throws AttributeError: 'JavaMember' object has no attribute 'format' exception. However, the same thing works in Scala API.
Please note, I tested in spark 2.4.5/2.4.6 and 3.0.0 and got the same exception. Is it a bug or known issue with Pyspark implementation? I noticed that I could perform other operations except the write method. Please, let me know how to fix this issue. See below code examples # Spark Scala method def processData(batchDF: DataFrame, batchId: Long) { batchDF.createOrReplaceTempView("tbl") val outdf=batchDF.sparkSession.sql("select action, count(*) as count from tbl where date='2020-06-20' group by 1") outdf.printSchema() outdf.show outdf.coalesce(1).write.format("csv").save("/tmp/agg") } ## pyspark python method def process_data(bdf, bid): lspark = bdf._jdf.sparkSession() bdf.createOrReplaceTempView("tbl") outdf=lspark.sql("select action, count(*) as count from tbl where date='2020-06-20' group by 1") outdf.printSchema() # it works outdf.show() # throws AttributeError: 'JavaMember' object has no attribute 'format' exception outdf.coalesce(1).write.format("csv").save("/tmp/agg1") Here is the full exception 20/07/24 16:31:24 ERROR streaming.MicroBatchExecution: Query [id = 854a39d0-b944-4b52-bf05-cacf998e2cbd, runId = e3d4dc7d-80e1-4164-8310-805d7713fc96] terminated with error py4j.Py4JException: An exception was raised by the Python Proxy. Return Message: Traceback (most recent call last): File "/Users/muru/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 2381, in _call_proxy return_value = getattr(self.pool[obj_id], method)(*params) File "/Users/muru/spark/python/pyspark/sql/utils.py", line 191, in call raise e AttributeError: 'JavaMember' object has no attribute 'format' at py4j.Protocol.getReturnValue(Protocol.java:473) at py4j.reflection.PythonProxyHandler.invoke(PythonProxyHandler.java:108) at com.sun.proxy.$Proxy20.call(Unknown Source) at org.apache.spark.sql.execution.streaming.sources.PythonForeachBatchHelper$$anonfun$callForeachBatch$1.apply(ForeachBatchSink.scala:55) at org.apache.spark.sql.execution.streaming.sources.PythonForeachBatchHelper$$anonfun$callForeachBatch$1.apply(ForeachBatchSink.scala:55) at org.apache.spark.sql.execution.streaming.sources.ForeachBatchSink.addBatch(ForeachBatchSink.scala:35) at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5$$anonfun$apply$17.apply(MicroBatchExecution.scala:537) at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75) at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5.apply(MicroBatchExecution.scala:535) at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351) at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58) at org.apache.spark.sql.execution.streaming.MicroBatchExecution.org $apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:534) at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:198) at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166) at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166) at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351) at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58) at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:166) at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56) at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160) at org.apache.spark.sql.execution.streaming.StreamExecution.org $apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:281) at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:193)