Hi Lorenzo, I didn't mean to dismiss the issue, but it's not a matter of incompatibility, it's a matter of unsound generated code. It will break independently of Flink, since it apparently is a bug in the Avro compiler 1.8.2, so our options to fix it are limited. What we should do is to bump the Avro version to fix the underlying issue. You can vote for it on the respective ticket, which also explains why it's not that easy [1] (also you can vote on that respective hive ticket).
I remember that I also encountered an issue with nullable logical types back in my user days, but didn't dare to fix it, since the Avro project was really inactive at that time (e.g., it looked dead). Possible workarounds: * Stick with non-logical types (what I ended up with). You need to convert manually in your first step, which sounds like a PITA, but that's what you would do on non-JVM projects anyways (logical types are not really established after 5+ years). * Use default values instead of union with null. So instead of using null to tag missing values, use 0 = 01.01.1970 to identify missing values. Deep copies are used whenever the same record has to be used multiple times (state, broadcast). That's why I thought your idea of switching to POJOs asap should help. Where do you see issues? [1] https://issues.apache.org/jira/browse/FLINK-12532 On Tue, Jun 16, 2020 at 9:59 PM Lorenzo Nicora <lorenzo.nic...@gmail.com> wrote: > Hi Arvid, > > Sorry but saying the AVRO compiler setup is "broken" sounds like an easy > way for dismissing a problem ;) > I am using the official AVRO 1.8.2 Maven plugin with no customisation to > generate the code. > There might be some legit AVRO configurations that are incompatible with > Flink or something in the schema not fully supported. > > In particular, I noticed the user.avsc schema in Flink testing has *no > optional logical type fields* while my schema has multiple optional > timestamps. > Can AVRO-1891 <https://issues.apache.org/jira/browse/AVRO-1891> (fixed in > AVRO 1.9.1) be related? > > I tried changing user.avsc making one of the timestamp fields a union with > null, and flink-avro tests start failing with a lot of "Unknown datum type > org.joda.time.DateTime" > > This would explain why using records generated with AVRO 1.9.2 and > dateTimeLogicalType=Joda and enableObjectReuse() behaves better. > The workaround only partially solves my problem. > It looks like deepCopies happen in many places not controlled by > enableObjectReuse, like when adding to some Collectors. Am I right? > > Cheers > Lorenzo > > > On Mon, 15 Jun 2020 at 19:30, Arvid Heise <ar...@ververica.com> wrote: > >> Hi Lorenzo, >> >> Thank you for confirming my suspicion. It really means something is >> broken in your Avro compiler setup and there is not much that we can do on >> our end. >> >> Just for reference, we are having a user.avsc [1] being compiled [2] with >> <avro.version>1.8.2</avro.version> into this snippet [3] for our tests. >> Look especially on how the conversions look like; they have a different >> template style than yours. >> >> The expectation is that you have 1 conversion for each logical type that >> is compiled to joda type. If you have conversions on other places, you can >> trace back to which field they belong by using the IndexedRecord methods. >> >> [1] >> https://github.com/apache/flink/blob/master/flink-formats/flink-avro/src/test/resources/avro/user.avsc >> [2] >> https://github.com/apache/flink/blob/master/flink-formats/flink-avro/pom.xml >> [3] https://gist.github.com/AHeise/041ff5ccf76087975ed157c3d3276875 >> >> On Thu, Jun 11, 2020 at 3:22 PM Lorenzo Nicora <lorenzo.nic...@gmail.com> >> wrote: >> >>> >>> Hi Arvit, >>> >>> I followed your instructions for the breakpoint in >>> SpecificDatumReader.readField *with AVRO 1.8.2*, >>> >>> For all timestamp-millis fields (I have many): >>> >>> Conversion<?> conversion = ((SpecificRecordBase) >>> r).getConversion(f.pos()); >>> >>> >>> returns null for all timestamp-millis fields (I have many), so... >>> >>> datum = readWithoutConversion(oldDatum, f.schema(), in); >>> >>> >>> is used instead and returns a *Long* >>> >>> >>> >>> Not sure it's relevant, but in this version I have the explicit >>> dependency org.apache.avro:avro:1.8.2 and I am using the >>> avro-maven-plugin (1.8.2) to generate the record from .avsc with this >>> configuration: >>> >>> <configuration> >>> <stringType>String</stringType> >>> <createSetters>true</createSetters> >>> <fieldVisibility>private</fieldVisibility> >>> <enableDecimalLogicalType>true</enableDecimalLogicalType> >>> </configuration> >>> >>> >>> Cheers >>> Lorenzo >>> >>> >>> On Thu, 11 Jun 2020 at 13:11, Arvid Heise <ar...@ververica.com> wrote: >>> >>>> Sorry forget my last mail, that was half-finished. >>>> >>>> Here is the real one: >>>> >>>> Hi Lorenzo, >>>> >>>> if you still have time to investigate. >>>> >>>> Your stack trace shows that all expected code paths have been taken. >>>> Conversions are there; although they look different than here, but that can >>>> be attributed to the avro upgrade. >>>> >>>> Could you put a breakpoint on SpecificDatumReader.readField, so that >>>> you can inspect the conversion for the timestamp field? You probably want >>>> to make it a conditional for f.name() == <your field name>. >>>> The expected flow is that it should have a conversion that returns the >>>> joda time instead of the long. Then datum should be the converted joda >>>> time. >>>> >>>> @Override >>>> protected void readField(Object r, Schema.Field f, Object oldDatum, >>>> ResolvingDecoder in, Object state) >>>> throws IOException { >>>> if (r instanceof SpecificRecordBase) { >>>> Conversion<?> conversion = ((SpecificRecordBase) >>>> r).getConversion(f.pos()); >>>> >>>> Object datum; >>>> if (conversion != null) { >>>> datum = readWithConversion( >>>> oldDatum, f.schema(), f.schema().getLogicalType(), conversion, >>>> in); >>>> } else { >>>> datum = readWithoutConversion(oldDatum, f.schema(), in); >>>> } >>>> >>>> getData().setField(r, f.name(), f.pos(), datum); >>>> >>>> } else { >>>> super.readField(r, f, oldDatum, in, state); >>>> } >>>> } >>>> >>>> >>>> On Thu, Jun 11, 2020 at 2:06 PM Arvid Heise <ar...@ververica.com> >>>> wrote: >>>> >>>>> Hi Lorenzo, >>>>> >>>>> if you still have time to investigate. >>>>> >>>>> Your stack trace shows that all expected code paths have been taken. >>>>> Conversions are there although they look different than here, but that can >>>>> be attributed to the avro upgrade. >>>>> >>>>> @Override >>>>> protected void readField(Object r, Schema.Field f, Object oldDatum, >>>>> ResolvingDecoder in, Object state) >>>>> throws IOException { >>>>> if (r instanceof SpecificRecordBase) { >>>>> Conversion<?> conversion = ((SpecificRecordBase) >>>>> r).getConversion(f.pos()); >>>>> >>>>> Object datum; >>>>> if (conversion != null) { >>>>> datum = readWithConversion( >>>>> oldDatum, f.schema(), f.schema().getLogicalType(), conversion, >>>>> in); >>>>> } else { >>>>> datum = readWithoutConversion(oldDatum, f.schema(), in); >>>>> } >>>>> >>>>> getData().setField(r, f.name(), f.pos(), datum); >>>>> >>>>> } else { >>>>> super.readField(r, f, oldDatum, in, state); >>>>> } >>>>> } >>>>> >>>>> >>>>> On Thu, Jun 11, 2020 at 1:27 PM Lorenzo Nicora < >>>>> lorenzo.nic...@gmail.com> wrote: >>>>> >>>>>> >>>>>> Thanks Gouwei, >>>>>> >>>>>> setting format.setReuseAvroValue(false) with 1.8.2-generated records >>>>>> does not solve the problem. >>>>>> >>>>>> 12:02:59,314 INFO >>>>>> org.apache.flink.runtime.checkpoint.CheckpointCoordinator - >>>>>> Discarding >>>>>> checkpoint 1 of job 46ea458aff2a496c4617a6b57e4de937. >>>>>> java.lang.ClassCastException: java.lang.Long cannot be cast to >>>>>> org.joda.time.DateTime >>>>>> at com.tenx.client.generalledger.event.GlHeader.put(GlHeader.java:125) >>>>>> at org.apache.avro.generic.GenericData.setField(GenericData.java:690) >>>>>> at >>>>>> org.apache.avro.specific.SpecificDatumReader.readField(SpecificDatumReader.java:119) >>>>>> at >>>>>> org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:222) >>>>>> at >>>>>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:175) >>>>>> at >>>>>> org.apache.avro.specific.SpecificDatumReader.readField(SpecificDatumReader.java:116) >>>>>> at >>>>>> org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:222) >>>>>> at >>>>>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:175) >>>>>> at >>>>>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153) >>>>>> at >>>>>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:145) >>>>>> at org.apache.avro.file.DataFileStream.next(DataFileStream.java:233) >>>>>> at >>>>>> org.apache.flink.formats.avro.AvroInputFormat.nextRecord(AvroInputFormat.java:170) >>>>>> at >>>>>> org.apache.flink.streaming.api.functions.source.ContinuousFileReaderOperator$SplitReader.run(ContinuousFileReaderOperator.java:323) >>>>>> >>>>>> >>>>>> ---------------------------- >>>>>> >>>>>> Summarising, the only working combination seems to be: >>>>>> >>>>>> - Use AVRO 1.9.2 code generation, setting >>>>>> dateTimeLogicalTypeImplementation >>>>>> = joda >>>>>> - Enabling Object Reuse (being careful for the implications) >>>>>> >>>>>> Using AVRO 1.8.2 code generation does not work, with any of the other >>>>>> workarounds. >>>>>> Using Generic objects does not work for a bug in AvroSerializer >>>>>> <https://issues.apache.org/jira/browse/FLINK-18223> but >>>>>> GenericRecords also brings a number of other problems. >>>>>> >>>>>> I am not very comfortable with using AVRO objects generated with a >>>>>> different AVRO version than the one supported by Flink. >>>>>> I am going to map AVRO records into hand-written POJOs immediately >>>>>> after the ingestion to reduce chances of further issues. I reckon this is >>>>>> very empirical, but that's what the workaround looks to me :) >>>>>> >>>>>> Lorenzo >>>>>> >>>>>> P.S, I want to give a massive thank to this community. So far it has >>>>>> been one of the most reactive and helpful I ever interacted with. >>>>>> >>>>>> On Thu, 11 Jun 2020 at 10:25, Guowei Ma <guowei....@gmail.com> wrote: >>>>>> >>>>>>> Hi, >>>>>>> for the 1.8.2(case 1) you could try the format.setReuseAvroValue( >>>>>>> false); >>>>>>> >>>>>>> Best, >>>>>>> Guowei >>>>>>> >>>>>>> >>>>>>> Lorenzo Nicora <lorenzo.nic...@gmail.com> 于2020年6月11日周四 下午5:02写道： >>>>>>> >>>>>>>> Hi Arvid, >>>>>>>> >>>>>>>> thanks for the point about catching records. Gotcha! >>>>>>>> >>>>>>>> Sorry I cannot share the full schema or generated code. It's a 3rd >>>>>>>> party IP and we signed a meter-think NDA... I think I can post >>>>>>>> snippets. >>>>>>>> The schema is heavily nested, including arrays of other record types >>>>>>>> Types are primitives, or logical decimal and timestamp-millis. No >>>>>>>> union. >>>>>>>> >>>>>>>> #conversion is in AccountEntries only (one of the nested records) >>>>>>>> and looks like this: >>>>>>>> >>>>>>>> private static final org.apache.avro.Conversion<?>[] conversions = >>>>>>>> new org.apache.avro.Conversion<?>[] { >>>>>>>> null, >>>>>>>> null, >>>>>>>> null, >>>>>>>> new org.apache.avro.data.JodaTimeConversions.TimestampConversion(), >>>>>>>> new org.apache.avro.data.JodaTimeConversions.TimestampConversion(), >>>>>>>> new org.apache.avro.data.JodaTimeConversions.TimestampConversion(), >>>>>>>> null, >>>>>>>> null, >>>>>>>> null, >>>>>>>> null, >>>>>>>> null, >>>>>>>> null, >>>>>>>> null >>>>>>>> }; >>>>>>>> >>>>>>>> >>>>>>>> Note that I have to generate the specific object with AVRO 1.9.2 >>>>>>>> Maven Plugin. >>>>>>>> With 1.8.2 generated code it fails with the following exception, >>>>>>>> regardless setting enableObjectReuse() >>>>>>>> >>>>>>>> java.lang.ClassCastException: java.lang.Long cannot be cast to >>>>>>>> org.joda.time.DateTime >>>>>>>> at >>>>>>>> com.tenx.client.generalledger.event.GlHeader.put(GlHeader.java:125) >>>>>>>> at >>>>>>>> org.apache.avro.generic.GenericData.setField(GenericData.java:690) >>>>>>>> at >>>>>>>> org.apache.avro.specific.SpecificDatumReader.readField(SpecificDatumReader.java:119) >>>>>>>> at >>>>>>>> org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:222) >>>>>>>> at >>>>>>>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:175) >>>>>>>> at >>>>>>>> org.apache.avro.specific.SpecificDatumReader.readField(SpecificDatumReader.java:116) >>>>>>>> at >>>>>>>> org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:222) >>>>>>>> at >>>>>>>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:175) >>>>>>>> at >>>>>>>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153) >>>>>>>> at >>>>>>>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:145) >>>>>>>> at org.apache.avro.file.DataFileStream.next(DataFileStream.java:233) >>>>>>>> at >>>>>>>> org.apache.flink.formats.avro.AvroInputFormat.nextRecord(AvroInputFormat.java:165) >>>>>>>> at >>>>>>>> org.apache.flink.streaming.api.functions.source.ContinuousFileReaderOperator$SplitReader.run(ContinuousFileReaderOperator.java:323) >>>>>>>> >>>>>>>> >>>>>>>> Thanks for the help >>>>>>>> Lorenzo >>>>>>>> >>>>>>>> >>>>>>>> On Thu, 11 Jun 2020 at 08:58, Arvid Heise <ar...@ververica.com> >>>>>>>> wrote: >>>>>>>> >>>>>>>>> Hi Lorenzo, >>>>>>>>> >>>>>>>>> I'm glad that it worked out somehow, but I'd still like to >>>>>>>>> understand what went wrong, so it will work more smoothly for future >>>>>>>>> users. >>>>>>>>> I double checked and we even test AvroSerializer with logical types, >>>>>>>>> so I'm >>>>>>>>> a bit puzzled. >>>>>>>>> >>>>>>>>> Could you attach GlHeader or at least show us how GlHeader#conversions >>>>>>>>> look like? I want to exclude the possibility that the source >>>>>>>>> generator screwed up. >>>>>>>>> >>>>>>>>> Concerning object reuse is that you need to treat all POJO as >>>>>>>>> immutable (I'm assuming that that's what your meant from your >>>>>>>>> description), >>>>>>>>> but you should also never cache values like >>>>>>>>> class ShiftElements extends MapFunction { >>>>>>>>> Object lastElement; >>>>>>>>> >>>>>>>>> Object map(Object newElement, Collector out) { >>>>>>>>> out.collect(lastElement); >>>>>>>>> lastElement = newElement; // <- never cache with >>>>>>>>> enableObjectReuse >>>>>>>>> } >>>>>>>>> } >>>>>>>>> >>>>>>>>> (excuse my ugly code) >>>>>>>>> >>>>>>>>> On Thu, Jun 11, 2020 at 9:25 AM Lorenzo Nicora < >>>>>>>>> lorenzo.nic...@gmail.com> wrote: >>>>>>>>> >>>>>>>>>> Hi Arvid, >>>>>>>>>> >>>>>>>>>> answering to your other questions >>>>>>>>>> >>>>>>>>>> Here is the stacktrace of the case (1), when I try to read using >>>>>>>>>> specific records generated by the AVRO 1.8.2 plugin >>>>>>>>>> >>>>>>>>>> java.lang.ClassCastException: java.lang.Long cannot be cast to >>>>>>>>>> org.joda.time.DateTime >>>>>>>>>> at >>>>>>>>>> com.tenx.client.generalledger.event.GlHeader.put(GlHeader.java:125) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.setField(GenericData.java:690) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.specific.SpecificDatumReader.readField(SpecificDatumReader.java:119) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:222) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:175) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.specific.SpecificDatumReader.readField(SpecificDatumReader.java:116) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:222) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:175) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:145) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.file.DataFileStream.next(DataFileStream.java:233) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.formats.avro.AvroInputFormat.nextRecord(AvroInputFormat.java:165) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.api.functions.source.ContinuousFileReaderOperator$SplitReader.run(ContinuousFileReaderOperator.java:323) >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> I also tried generating the specific object with avro 1.9.2 (2) >>>>>>>>>> but forcing it to use Joda time but still didn't work >>>>>>>>>> >>>>>>>>>> org.apache.flink.streaming.runtime.tasks.ExceptionInChainedOperatorException: >>>>>>>>>> Could not forward element to next operator >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:596) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:554) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:534) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.api.operators.StreamSourceContexts$ManualWatermarkContext.processAndCollect(StreamSourceContexts.java:305) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.api.operators.StreamSourceContexts$WatermarkContext.collect(StreamSourceContexts.java:394) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.api.functions.source.ContinuousFileReaderOperator$SplitReader.run(ContinuousFileReaderOperator.java:325) >>>>>>>>>> Caused by: org.apache.avro.AvroRuntimeException: Unknown datum >>>>>>>>>> type org.joda.time.DateTime: 2020-06-01T02:00:42.326Z >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.getSchemaName(GenericData.java:909) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.specific.SpecificData.getSchemaName(SpecificData.java:420) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.resolveUnion(GenericData.java:871) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.deepCopyRaw(GenericData.java:1302) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.deepCopy(GenericData.java:1221) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.deepCopyRaw(GenericData.java:1283) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.deepCopy(GenericData.java:1221) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.deepCopyRaw(GenericData.java:1283) >>>>>>>>>> at >>>>>>>>>> org.apache.avro.generic.GenericData.deepCopy(GenericData.java:1221) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.formats.avro.typeutils.AvroSerializer.copy(AvroSerializer.java:242) >>>>>>>>>> at >>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:577) >>>>>>>>>> ... 7 more >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> But in the second case, it seems the failure happens when Flink >>>>>>>>>> tries to make a copy of the record. >>>>>>>>>> So I followed your suggestion of enableObjectReuse() and* IT >>>>>>>>>> WORKS!* >>>>>>>>>> >>>>>>>>>> I am not sure I understand all implications of object reuse >>>>>>>>>> in Flink, specifically. >>>>>>>>>> I am familiar with the general risk of mutable messages, and I >>>>>>>>>> always handle them as mutable even when they are POJO. Never >>>>>>>>>> mutating and >>>>>>>>>> forwarding the same record. >>>>>>>>>> Not sure whether there are other implications in Flink. >>>>>>>>>> >>>>>>>>>> Many thanks >>>>>>>>>> Lorenzo >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On Wed, 10 Jun 2020 at 17:52, Arvid Heise <ar...@ververica.com> >>>>>>>>>> wrote: >>>>>>>>>> >>>>>>>>>>> Hi Lorenzo, >>>>>>>>>>> >>>>>>>>>>> 1) I'm surprised that this doesn't work. I'd like to see that >>>>>>>>>>> stacktrace. >>>>>>>>>>> >>>>>>>>>>> 2) cannot work like this, because we bundle Avro 1.8.2. You >>>>>>>>>>> could retest with dateTimeLogicalType='Joda' set, but then you >>>>>>>>>>> will probably see the same issue as 1) >>>>>>>>>>> >>>>>>>>>>> 3) I'm surprised that this doesn't work either. There is a >>>>>>>>>>> codepath since 2016 for GenericRecord and it's covered in a test. >>>>>>>>>>> From the >>>>>>>>>>> error description and the ticket, it looks like the issue is not the >>>>>>>>>>> AvroInputFormat, but the serializer. So it would probably work >>>>>>>>>>> with a different serializer (but that would cause back and forth >>>>>>>>>>> type >>>>>>>>>>> transformation). >>>>>>>>>>> >>>>>>>>>>> On Wed, Jun 10, 2020 at 4:31 PM Lorenzo Nicora < >>>>>>>>>>> lorenzo.nic...@gmail.com> wrote: >>>>>>>>>>> >>>>>>>>>>>> Thanks Timo, >>>>>>>>>>>> >>>>>>>>>>>> the stacktrace with 1.9.2-generated specific file is the >>>>>>>>>>>> following >>>>>>>>>>>> >>>>>>>>>>>> org.apache.flink.streaming.runtime.tasks.ExceptionInChainedOperatorException: >>>>>>>>>>>> Could not forward element to next operator >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:596) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:554) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:534) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.api.operators.StreamSourceContexts$ManualWatermarkContext.processAndCollect(StreamSourceContexts.java:305) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.api.operators.StreamSourceContexts$WatermarkContext.collect(StreamSourceContexts.java:394) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.api.functions.source.ContinuousFileReaderOperator$SplitReader.run(ContinuousFileReaderOperator.java:325) >>>>>>>>>>>> Caused by: org.apache.avro.AvroRuntimeException: Unknown datum >>>>>>>>>>>> type java.time.Instant: 2020-06-01T02:00:42.105Z >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.getSchemaName(GenericData.java:909) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.specific.SpecificData.getSchemaName(SpecificData.java:420) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.resolveUnion(GenericData.java:871) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.deepCopyRaw(GenericData.java:1302) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.deepCopy(GenericData.java:1221) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.deepCopyRaw(GenericData.java:1283) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.deepCopy(GenericData.java:1221) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.deepCopyRaw(GenericData.java:1283) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.avro.generic.GenericData.deepCopy(GenericData.java:1221) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.formats.avro.typeutils.AvroSerializer.copy(AvroSerializer.java:242) >>>>>>>>>>>> at >>>>>>>>>>>> org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:577) >>>>>>>>>>>> ... 7 more >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> I reckon logical types might have been considered somehow >>>>>>>>>>>> experimental since...ever. But, honestly, I've been using them in >>>>>>>>>>>> the >>>>>>>>>>>> Kafka/Java ecosystem as well as in Spark without too many problems. >>>>>>>>>>>> >>>>>>>>>>>> For my specific use case, the schema is given. Messages are >>>>>>>>>>>> produced by a 3rd party and we cannot change the schema >>>>>>>>>>>> (especially because >>>>>>>>>>>> it's a legit schema). >>>>>>>>>>>> I am desperately looking for a workaround. >>>>>>>>>>>> >>>>>>>>>>>> I had a similar issue with a Kafka Source, and AVRO records >>>>>>>>>>>> containing decimals and timestamps. Timestamps worked but not >>>>>>>>>>>> decimals. >>>>>>>>>>>> I was able to work around the problem using GenericRecords. >>>>>>>>>>>> But Kafka source relies on AvroDeserializationSchema rather >>>>>>>>>>>> than AvroSerializer, and has no problem handling >>>>>>>>>>>> GenericRecords. >>>>>>>>>>>> >>>>>>>>>>>> I'm honestly finding very confusing having different ways of >>>>>>>>>>>> handling AVRO deserialization inside Flink core components. >>>>>>>>>>>> >>>>>>>>>>>> Cheers >>>>>>>>>>>> Lorenzo >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On Wed, 10 Jun 2020 at 15:02, Timo Walther <twal...@apache.org> >>>>>>>>>>>> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> Hi Lorenzo, >>>>>>>>>>>>> >>>>>>>>>>>>> as far as I know we don't support Avro's logical times in >>>>>>>>>>>>> Flink's >>>>>>>>>>>>> AvroInputFormat yet. E.g. AvroRowDeserializationSchema [1] >>>>>>>>>>>>> supports the >>>>>>>>>>>>> 1.8.2 version of logical types but might be incompatible with >>>>>>>>>>>>> 1.9.2. >>>>>>>>>>>>> >>>>>>>>>>>>> Reg 2) Specific record generated with AVRO 1.9.2 plugin: >>>>>>>>>>>>> >>>>>>>>>>>>> Could you send us the full stack trace? I think this should >>>>>>>>>>>>> actually >>>>>>>>>>>>> work, because specific records are handled as POJOs and those >>>>>>>>>>>>> should be >>>>>>>>>>>>> able to also deal with logical type's classes through Kryo. >>>>>>>>>>>>> >>>>>>>>>>>>> Reg 3) Generic record >>>>>>>>>>>>> >>>>>>>>>>>>> It would be great if we can make this option possible. We >>>>>>>>>>>>> could include >>>>>>>>>>>>> it in the next minor release fix. >>>>>>>>>>>>> >>>>>>>>>>>>> Sorry, for the bad user experience. But IMHO logical type are >>>>>>>>>>>>> still >>>>>>>>>>>>> experiemental in Avro. Maybe 1.9.2 has finally fixed the >>>>>>>>>>>>> biggest >>>>>>>>>>>>> shortcomings such that Flink can properly support them as well. >>>>>>>>>>>>> >>>>>>>>>>>>> Regards, >>>>>>>>>>>>> Timo >>>>>>>>>>>>> >>>>>>>>>>>>> [1] >>>>>>>>>>>>> >>>>>>>>>>>>> https://github.com/apache/flink/blob/master/flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/AvroRowDeserializationSchema.java >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On 10.06.20 15:08, Lorenzo Nicora wrote: >>>>>>>>>>>>> > Hi, >>>>>>>>>>>>> > >>>>>>>>>>>>> > I need to continuously ingest AVRO files as they arrive. >>>>>>>>>>>>> > Files are written by an S3 Sink Kafka Connect but S3 is not >>>>>>>>>>>>> the point >>>>>>>>>>>>> > here. I started trying to ingest a static bunch of files >>>>>>>>>>>>> from local fs >>>>>>>>>>>>> > first and I am having weird issues with AVRO deserialization. >>>>>>>>>>>>> > >>>>>>>>>>>>> > I have to say, the records contain logical types, >>>>>>>>>>>>> timestamps-ms and decimals >>>>>>>>>>>>> > >>>>>>>>>>>>> > To keep it simple, I extracted the AVRO schema from the data >>>>>>>>>>>>> files and >>>>>>>>>>>>> > used avro-maven-plugin to generate POJOs >>>>>>>>>>>>> > I tried multiple combinations, all with no luck >>>>>>>>>>>>> > >>>>>>>>>>>>> > 1) Specific record generated with AVRO 1.8.2 plugin >>>>>>>>>>>>> > >>>>>>>>>>>>> > Path in = new Path(sourceBasePath); >>>>>>>>>>>>> > AvroInputFormat<AccountEntries> inputFormat = new >>>>>>>>>>>>> AvroInputFormat<>(in, >>>>>>>>>>>>> > AccountEntries.class); >>>>>>>>>>>>> > DataStream<AccountEntries> accountEntries = env >>>>>>>>>>>>> > .readFile(inputFormat, sourceBasePath, >>>>>>>>>>>>> > FileProcessingMode.PROCESS_CONTINUOUSLY, >>>>>>>>>>>>> FILE_SCAN_INTERVAL_MS); >>>>>>>>>>>>> > >>>>>>>>>>>>> > *Result* >>>>>>>>>>>>> > java.lang.ClassCastException: java.lang.Long cannot be cast >>>>>>>>>>>>> to >>>>>>>>>>>>> > org.joda.time.DateTime >>>>>>>>>>>>> > (IIRC this is a known AVRO 1.8.2 issue) >>>>>>>>>>>>> > >>>>>>>>>>>>> > >>>>>>>>>>>>> > 2) Specific record generated with AVRO 1.9.2 plugin >>>>>>>>>>>>> > Same code as above but AVRO POJOs are generated with AVRO >>>>>>>>>>>>> 1.9.2 >>>>>>>>>>>>> > >>>>>>>>>>>>> > *Result* >>>>>>>>>>>>> > org.apache.avro.AvroRuntimeException: Unknown datum type >>>>>>>>>>>>> java.time.Instant >>>>>>>>>>>>> > >>>>>>>>>>>>> > >>>>>>>>>>>>> > 3) Generic record >>>>>>>>>>>>> > I am getting the Schema from the generated specific record, >>>>>>>>>>>>> for >>>>>>>>>>>>> > convenience, but I am not using the generated POJO as record. >>>>>>>>>>>>> > I also followed the suggestions in this Flink blog post >>>>>>>>>>>>> > < >>>>>>>>>>>>> https://flink.apache.org/news/2020/04/15/flink-serialization-tuning-vol-1.html#avro-generic>, >>>>>>>>>>>>> >>>>>>>>>>>>> > to explicitly specify the TypeInfo with returns(...) >>>>>>>>>>>>> > >>>>>>>>>>>>> > Path in = new Path(config.sourceFileSystemPath); >>>>>>>>>>>>> > Schema schema = AccountEntries.getClassSchema(); >>>>>>>>>>>>> > AvroInputFormat<GenericRecord> inputFormat = new >>>>>>>>>>>>> AvroInputFormat<>(in, >>>>>>>>>>>>> > GenericRecord.class); >>>>>>>>>>>>> > DataStream<GenericRecord> accountEntries = env >>>>>>>>>>>>> > .readFile(inputFormat, config.sourceFileSystemPath, >>>>>>>>>>>>> > FileProcessingMode.PROCESS_CONTINUOUSLY, >>>>>>>>>>>>> FILE_SCAN_INTERVAL_MS) >>>>>>>>>>>>> > .returns(new GenericRecordAvroTypeInfo(schema)); >>>>>>>>>>>>> > >>>>>>>>>>>>> > >>>>>>>>>>>>> > *Result* >>>>>>>>>>>>> > The class 'org.apache.avro.generic.GenericRecord' is not >>>>>>>>>>>>> instantiable: >>>>>>>>>>>>> > The class is not a proper class. It is either abstract, an >>>>>>>>>>>>> interface, or >>>>>>>>>>>>> > a primitive type. >>>>>>>>>>>>> > >>>>>>>>>>>>> > This looks like a bug. >>>>>>>>>>>>> > I raised the ticket < >>>>>>>>>>>>> https://issues.apache.org/jira/browse/FLINK-18223> >>>>>>>>>>>>> > and I will try to submit a fix, but still do not solve my >>>>>>>>>>>>> problem as I >>>>>>>>>>>>> > am using a managed Flink I cannot update. >>>>>>>>>>>>> > I cannot believe there is no workaround. I do not think I'm >>>>>>>>>>>>> trying to do >>>>>>>>>>>>> > anything bizarre. Am I? >>>>>>>>>>>>> > >>>>>>>>>>>>> > Any ideas? >>>>>>>>>>>>> > Am I missing something obvious? >>>>>>>>>>>>> > >>>>>>>>>>>>> > Cheers >>>>>>>>>>>>> > Lorenzo >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> >>>>>>>>>>> Arvid Heise | Senior Java Developer >>>>>>>>>>> >>>>>>>>>>> <https://www.ververica.com/> >>>>>>>>>>> >>>>>>>>>>> Follow us @VervericaData >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> >>>>>>>>>>> Join Flink Forward <https://flink-forward.org/> - The Apache >>>>>>>>>>> Flink Conference >>>>>>>>>>> >>>>>>>>>>> Stream Processing | Event Driven | Real Time >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> >>>>>>>>>>> Ververica GmbH | Invalidenstrasse 115, 10115 Berlin, Germany >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> Ververica GmbH >>>>>>>>>>> Registered at Amtsgericht Charlottenburg: HRB 158244 B >>>>>>>>>>> Managing Directors: Timothy Alexander Steinert, Yip Park Tung >>>>>>>>>>> Jason, Ji (Toni) Cheng >>>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>>> -- >>>>>>>>> >>>>>>>>> Arvid Heise | Senior Java Developer >>>>>>>>> >>>>>>>>> <https://www.ververica.com/> >>>>>>>>> >>>>>>>>> Follow us @VervericaData >>>>>>>>> >>>>>>>>> -- >>>>>>>>> >>>>>>>>> Join Flink Forward <https://flink-forward.org/> - The Apache Flink >>>>>>>>> Conference >>>>>>>>> >>>>>>>>> Stream Processing | Event Driven | Real Time >>>>>>>>> >>>>>>>>> -- >>>>>>>>> >>>>>>>>> Ververica GmbH | Invalidenstrasse 115, 10115 Berlin, Germany >>>>>>>>> >>>>>>>>> -- >>>>>>>>> Ververica GmbH >>>>>>>>> Registered at Amtsgericht Charlottenburg: HRB 158244 B >>>>>>>>> Managing Directors: Timothy Alexander Steinert, Yip Park Tung >>>>>>>>> Jason, Ji (Toni) Cheng >>>>>>>>> >>>>>>>> >>>>> >>>>> -- >>>>> >>>>> Arvid Heise | Senior Java Developer >>>>> >>>>> <https://www.ververica.com/> >>>>> >>>>> Follow us @VervericaData >>>>> >>>>> -- >>>>> >>>>> Join Flink Forward <https://flink-forward.org/> - The Apache Flink >>>>> Conference >>>>> >>>>> Stream Processing | Event Driven | Real Time >>>>> >>>>> -- >>>>> >>>>> Ververica GmbH | Invalidenstrasse 115, 10115 Berlin, Germany >>>>> >>>>> -- >>>>> Ververica GmbH >>>>> Registered at Amtsgericht Charlottenburg: HRB 158244 B >>>>> Managing Directors: Timothy Alexander Steinert, Yip Park Tung Jason, >>>>> Ji (Toni) Cheng >>>>> >>>> >>>> >>>> -- >>>> >>>> Arvid Heise | Senior Java Developer >>>> >>>> <https://www.ververica.com/> >>>> >>>> Follow us @VervericaData >>>> >>>> -- >>>> >>>> Join Flink Forward <https://flink-forward.org/> - The Apache Flink >>>> Conference >>>> >>>> Stream Processing | Event Driven | Real Time >>>> >>>> -- >>>> >>>> Ververica GmbH | Invalidenstrasse 115, 10115 Berlin, Germany >>>> >>>> -- >>>> Ververica GmbH >>>> Registered at Amtsgericht Charlottenburg: HRB 158244 B >>>> Managing Directors: Timothy Alexander Steinert, Yip Park Tung Jason, Ji >>>> (Toni) Cheng >>>> >>> >> >> -- >> >> Arvid Heise | Senior Java Developer >> >> <https://www.ververica.com/> >> >> Follow us @VervericaData >> >> -- >> >> Join Flink Forward <https://flink-forward.org/> - The Apache Flink >> Conference >> >> Stream Processing | Event Driven | Real Time >> >> -- >> >> Ververica GmbH | Invalidenstrasse 115, 10115 Berlin, Germany >> >> -- >> Ververica GmbH >> Registered at Amtsgericht Charlottenburg: HRB 158244 B >> Managing Directors: Timothy Alexander Steinert, Yip Park Tung Jason, Ji >> (Toni) Cheng >> > -- Arvid Heise | Senior Java Developer <https://www.ververica.com/> Follow us @VervericaData -- Join Flink Forward <https://flink-forward.org/> - The Apache Flink Conference Stream Processing | Event Driven | Real Time -- Ververica GmbH | Invalidenstrasse 115, 10115 Berlin, Germany -- Ververica GmbH Registered at Amtsgericht Charlottenburg: HRB 158244 B Managing Directors: Timothy Alexander Steinert, Yip Park Tung Jason, Ji (Toni) Cheng
