[jira] [Created] (BEAM-12256) PubsubIO.readAvroGenericRecord creates SchemaCoder that fails to decode some Avro logical types

["Brian Hulette (Jira)" <ji...@apache.org>]

Brian Hulette created BEAM-12256:
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             Summary: PubsubIO.readAvroGenericRecord creates SchemaCoder that fails to decode some Avro logical types
                 Key: BEAM-12256
                 URL: https://issues.apache.org/jira/browse/BEAM-12256
             Project: Beam
          Issue Type: Bug
          Components: io-java-gcp, sdk-java-core
            Reporter: Brian Hulette
            Assignee: Brian Hulette


For example, when PubsubIO.readAvroGenericRecord is used with an avro schema that includes a decimal type with a non-zero scale, it can encounter the following exception when decoding:


{code:java}
org.apache.avro.AvroTypeException: Cannot encode decimal with scale 17 as scale 0
	at org.apache.avro.Conversions$DecimalConversion.toBytes(Conversions.java:92)
	at org.apache.beam.sdk.schemas.utils.AvroUtils.genericFromBeamField(AvroUtils.java:975)
	at org.apache.beam.sdk.schemas.utils.AvroUtils.toGenericRecord(AvroUtils.java:397)
	at org.apache.beam.sdk.schemas.utils.AvroUtils$RowToGenericRecordFn.apply(AvroUtils.java:547)
	at org.apache.beam.sdk.schemas.utils.AvroUtils$RowToGenericRecordFn.apply(AvroUtils.java:538)
	at org.apache.beam.sdk.schemas.SchemaCoder.decode(SchemaCoder.java:123)
	at org.apache.beam.sdk.io.gcp.bigquery.TableRowInfoCoder.decode(TableRowInfoCoder.java:64)
	at org.apache.beam.sdk.io.gcp.bigquery.TableRowInfoCoder.decode(TableRowInfoCoder.java:30)
	at org.apache.beam.runners.dataflow.worker.WindmillKeyedWorkItem.lambda$elementsIterable$2(WindmillKeyedWorkItem.java:112)
	at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators$6.transform(Iterators.java:785)
	at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.TransformedIterator.next(TransformedIterator.java:47)
	at org.apache.beam.runners.dataflow.worker.StreamingGroupAlsoByWindowReshuffleFn.processElement(StreamingGroupAlsoByWindowReshuffleFn.java:56)
	at org.apache.beam.runners.dataflow.worker.StreamingGroupAlsoByWindowReshuffleFn.processElement(StreamingGroupAlsoByWindowReshuffleFn.java:39)
	at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowFnRunner.invokeProcessElement(GroupAlsoByWindowFnRunner.java:121)
	at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowFnRunner.processElement(GroupAlsoByWindowFnRunner.java:73)
	at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowsParDoFn.processElement(GroupAlsoByWindowsParDoFn.java:137)
	at org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:44)
	at org.apache.beam.runners.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:49)
	at org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation.runReadLoop(ReadOperation.java:212)
	at org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation.start(ReadOperation.java:163)
	at org.apache.beam.runners.dataflow.worker.util.common.worker.MapTaskExecutor.execute(MapTaskExecutor.java:92)
	at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker.process(StreamingDataflowWorker.java:1426)
	at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker.access$1100(StreamingDataflowWorker.java:163)
	at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker$7.run(StreamingDataflowWorker.java:1105)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748) {code}



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