Thanks. It might be something good to document in case other users run into this as well. Can you file a JIRA with the details ?
On Fri, Jan 29, 2021 at 10:47 AM Tao Li <[email protected]> wrote: > OK I think this issue is due to incompatibility between the parquet files > (created with spark 2.4) and parquet version as a dependency of ParquetIO > 2.25. It seems working after I switch to spark runner (from direct runner) > and run the beam app in a spark cluster. I assume by doing this I am > basically using parquet jars from spark distributable directly and now > everything is compatible. > > > > *From: *Tao Li <[email protected]> > *Reply-To: *"[email protected]" <[email protected]> > *Date: *Friday, January 29, 2021 at 7:45 AM > *To: *"[email protected]" <[email protected]> > *Subject: *Re: Potential bug with ParquetIO.read when reading arrays > > > > Hi community, > > > > Can someone take a look at this issue? It is kind of a blocker to me right > now. Really appreciate your help! > > > > *From: *Tao Li <[email protected]> > *Reply-To: *"[email protected]" <[email protected]> > *Date: *Thursday, January 28, 2021 at 6:13 PM > *To: *"[email protected]" <[email protected]> > *Subject: *Re: Potential bug with ParquetIO.read when reading arrays > > > > BTW I tried avro 1.8 and 1.9 and both have the same error. So we can > probably rule out any avro issue. > > > > *From: *Tao Li <[email protected]> > *Reply-To: *"[email protected]" <[email protected]> > *Date: *Thursday, January 28, 2021 at 9:07 AM > *To: *"[email protected]" <[email protected]> > *Subject: *Potential bug with ParquetIO.read when reading arrays > > > > Hi Beam community, > > > > I am seeing an error when reading an array field using ParquetIO. I was > using beam 2.25 and the direct runner for testing. Is this a bug or a known > issue? Am I missing anything here? Please help me root cause this issue. > Thanks so much! > > > > Attached are the avro schema and the parquet file. Below is the schema > tree as a quick visualization. The array field name is “list” and the > element type is int. You can see this schema defined in the avsc file as > well. > > > > root > > |-- list: array (nullable = true) > > | |-- element: integer (containsNull = true) > > > > The beam code is very simple: > pipeline.apply(ParquetIO.read(avroSchema).from(parquetPath)); > > > > Here is the error when running that code: > > > > [direct-runner-worker] INFO > shaded.org.apache.parquet.hadoop.InternalParquetRecordReader - block read > in memory in 130 ms. row count = 1 > > Exception in thread "main" > org.apache.beam.sdk.Pipeline$PipelineExecutionException: > java.lang.ClassCastException: org.apache.avro.generic.GenericData$Record > cannot be cast to java.lang.Number > > at > org.apache.beam.runners.direct.DirectRunner$DirectPipelineResult.waitUntilFinish(DirectRunner.java:353) > > at > org.apache.beam.runners.direct.DirectRunner$DirectPipelineResult.waitUntilFinish(DirectRunner.java:321) > > at > org.apache.beam.runners.direct.DirectRunner.run(DirectRunner.java:216) > > at > org.apache.beam.runners.direct.DirectRunner.run(DirectRunner.java:67) > > at org.apache.beam.sdk.Pipeline.run(Pipeline.java:317) > > at org.apache.beam.sdk.Pipeline.run(Pipeline.java:303) > > Caused by: java.lang.ClassCastException: > org.apache.avro.generic.GenericData$Record cannot be cast to > java.lang.Number > > at > org.apache.avro.generic.GenericDatumWriter.writeWithoutConversion(GenericDatumWriter.java:156) > > at > org.apache.avro.generic.GenericDatumWriter.write(GenericDatumWriter.java:82) > > at > org.apache.avro.generic.GenericDatumWriter.writeArray(GenericDatumWriter.java:234) > > at > org.apache.avro.generic.GenericDatumWriter.writeWithoutConversion(GenericDatumWriter.java:136) > > at > org.apache.avro.generic.GenericDatumWriter.write(GenericDatumWriter.java:82) > > at > org.apache.avro.generic.GenericDatumWriter.writeField(GenericDatumWriter.java:206) > > at > org.apache.avro.generic.GenericDatumWriter.writeRecord(GenericDatumWriter.java:195) > > at > org.apache.avro.generic.GenericDatumWriter.writeWithoutConversion(GenericDatumWriter.java:130) > > at > org.apache.avro.generic.GenericDatumWriter.write(GenericDatumWriter.java:82) > > at > org.apache.avro.generic.GenericDatumWriter.write(GenericDatumWriter.java:72) > > at > org.apache.beam.sdk.coders.AvroCoder.encode(AvroCoder.java:317) > > at org.apache.beam.sdk.coders.Coder.encode(Coder.java:136) > > at > org.apache.beam.sdk.util.CoderUtils.encodeToSafeStream(CoderUtils.java:82) > > at > org.apache.beam.sdk.util.CoderUtils.encodeToByteArray(CoderUtils.java:66) > > at > org.apache.beam.sdk.util.CoderUtils.encodeToByteArray(CoderUtils.java:51) > > at > org.apache.beam.sdk.util.CoderUtils.clone(CoderUtils.java:141) > > at > org.apache.beam.sdk.util.MutationDetectors$CodedValueMutationDetector.<init>(MutationDetectors.java:115) > > at > org.apache.beam.sdk.util.MutationDetectors.forValueWithCoder(MutationDetectors.java:46) > > at > org.apache.beam.runners.direct.ImmutabilityCheckingBundleFactory$ImmutabilityEnforcingBundle.add(ImmutabilityCheckingBundleFactory.java:112) > > at > org.apache.beam.runners.direct.ParDoEvaluator$BundleOutputManager.output(ParDoEvaluator.java:301) > > at > org.apache.beam.repackaged.direct_java.runners.core.SimpleDoFnRunner.outputWindowedValue(SimpleDoFnRunner.java:267) > > at > org.apache.beam.repackaged.direct_java.runners.core.SimpleDoFnRunner.access$900(SimpleDoFnRunner.java:79) > > at > org.apache.beam.repackaged.direct_java.runners.core.SimpleDoFnRunner$DoFnProcessContext.output(SimpleDoFnRunner.java:413) > > at > org.apache.beam.repackaged.direct_java.runners.core.SimpleDoFnRunner$DoFnProcessContext.output(SimpleDoFnRunner.java:401) > > at > org.apache.beam.sdk.io.parquet.ParquetIO$ReadFiles$ReadFn.processElement(ParquetIO.java:646) > > > > >
