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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2022/04/10 12:47:00 UTC
[jira] [Work logged] (BEAM-12256) PubsubIO.readAvroGenericRecord creates SchemaCoder that fails to decode some Avro logical types
[ https://issues.apache.org/jira/browse/BEAM-12256?focusedWorklogId=755014&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-755014 ]
ASF GitHub Bot logged work on BEAM-12256:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 10/Apr/22 12:46
Start Date: 10/Apr/22 12:46
Worklog Time Spent: 10m
Work Description: github-actions[bot] commented on PR #14686:
URL: https://github.com/apache/beam/pull/14686#issuecomment-1094265921
This pull request has been marked as stale due to 60 days of inactivity. It will be closed in 1 week if no further activity occurs. If you think that’s incorrect or this pull request requires a review, please simply write any comment. If closed, you can revive the PR at any time and @mention a reviewer or discuss it on the dev@beam.apache.org list. Thank you for your contributions.
Issue Time Tracking
-------------------
Worklog Id: (was: 755014)
Time Spent: 1h 10m (was: 1h)
> 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
> Affects Versions: 2.29.0
> Reporter: Brian Hulette
> Priority: P1
> Time Spent: 1h 10m
> Remaining Estimate: 0h
>
> 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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