Hi Fred,
You probably need to cast the configs to Map<String, Object> before adding
the specific.avro.reader config.
Thanks,
Liquan
On Tue, May 17, 2016 at 5:29 PM, Guozhang Wang <wangg...@gmail.com> wrote:
> Hello Fred,
>
> Thanks for reporting this. I looked through your code and found this is due
> to a bug in io.confluent.examples.streams.utils.SpecificAvroDeserializer.
>
> I will fix this bug in Confluent's repo, as for you to work around it, you
> can create your own SpecificAvroDeserializer with the correct logic by
> copy-past Confluent class with the following one-line change:
>
> In configure(Map<String, ?> configs, boolean isKey) function, add the
> following key-value pair to the configs before calling inner.configure:
>
> configs.put("specific.avro.reader", "true");
>
>
> Guozhang
>
> On Tue, May 17, 2016 at 11:35 AM, Fred Patton <thoughtp...@gmail.com>
> wrote:
>
> > Before, switching the example from to() to through() things seemed to
> work
> > fine. Afterward, I get ClassCastExceptions from GenericRecord to
> > SpecificRecord. Hopefully, someone can point out something quick and dumb
> > so I can get my demo wrapped up. I never get past the through() method. I
> > am using the Kafka Streams tech preview, and using Avro compiled from
> > AvroTools. Additionally, initially I had a second parallel application
> > taking the output of this to() invocation and continuing with the same
> > logic, there was no crash, but no code ever ran such as initializing the
> > context. Any illumination is most appreciated.
> >
> > Here's the stack trace followed by the offending bit code...
> >
> > [info] CdcProcessorSupplier::get
> > [info] CdcProcessor::init - ctx:
> > org.apache.kafka.streams.processor.internals.ProcessorContextImpl@c5ff552
> > [info] CdcProcessor::close
> > [error] Exception in thread "StreamThread-1"
> java.lang.ClassCastException:
> > org.apache.avro.generic.GenericData$Record cannot be cast to
> > org.apache.avro.specific.SpecificRecord
> > [error] at
> >
> >
> io.confluent.examples.streams.utils.SpecificAvroDeserializer.deserialize(SpecificAvroDeserializer.java:51)
> > [error] at
> >
> >
> io.confluent.examples.streams.utils.SpecificAvroDeserializer.deserialize(SpecificAvroDeserializer.java:24)
> > [error] at
> >
> >
> org.apache.kafka.streams.processor.internals.SourceNode.deserializeValue(SourceNode.java:41)
> > [error] at
> >
> >
> org.apache.kafka.streams.processor.internals.RecordQueue.addRawRecords(RecordQueue.java:77)
> > [error] at
> >
> >
> org.apache.kafka.streams.processor.internals.PartitionGroup.addRawRecords(PartitionGroup.java:113)
> > [error] at
> >
> >
> org.apache.kafka.streams.processor.internals.StreamTask.addRecords(StreamTask.java:134)
> > [error] at
> >
> >
> org.apache.kafka.streams.processor.internals.StreamThread.runLoop(StreamThread.java:334)
> > [error] at
> >
> >
> org.apache.kafka.streams.processor.internals.StreamThread.run(StreamThread.java:248)
> >
> > def main(args: Array[String]) {
> > val schemaRegistry = new CachedSchemaRegistryClient("
> > http://localhost:8081";,
> > AbstractKafkaAvroSerDeConfig.MAX_SCHEMAS_PER_SUBJECT_DEFAULT)
> > val builder: KStreamBuilder = new KStreamBuilder
> > val streamingConfig = {
> > val settings = new Properties
> > settings.put(StreamsConfig.JOB_ID_CONFIG, "kstreams")
> > settings.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG,
> > "localhost:9092")
> > settings.put(StreamsConfig.ZOOKEEPER_CONNECT_CONFIG,
> > "localhost:2181")
> > settings.put(StreamsConfig.KEY_SERIALIZER_CLASS_CONFIG,
> > "io.confluent.kafka.serializers.KafkaAvroSerializer")
> > settings.put(StreamsConfig.KEY_DESERIALIZER_CLASS_CONFIG,
> > "io.confluent.kafka.serializers.KafkaAvroDeserializer")
> > settings.put(StreamsConfig.VALUE_SERIALIZER_CLASS_CONFIG,
> > "io.confluent.kafka.serializers.KafkaAvroSerializer")
> > settings.put(StreamsConfig.VALUE_DESERIALIZER_CLASS_CONFIG,
> > "io.confluent.kafka.serializers.KafkaAvroDeserializer")
> > settings
> > }
> >
> > import KeyValueImplicits._
> >
> > val stringSerializer = new StringSerializer
> > val stringDeserializer = new StringDeserializer
> > val bcAccessLogSerializer = new
> > SpecificAvroSerializer[BcAccessLog](schemaRegistry)
> > val bcAccessLogDeserializer = new
> > SpecificAvroDeserializer[BcAccessLog](schemaRegistry)
> >
> > val rawSourceStream: KStream[String, String] =
> > builder.stream(stringDeserializer,
> > stringDeserializer,
> > "raw-accesslog-" + testRun)
> >
> > val filteredStream: KStream[String, BcAccessLog] =
> > rawSourceStream.mapValues(parseAsJson)
> > .filter(isCdcEvent)
> > .map((key, value) => (getAccessLogKey(value),
> toBcAccessLog(value)))
> >
> > filteredStream
> > .through("accesslog-" + testRun,
> > stringSerializer,
> > bcAccessLogSerializer,
> > stringDeserializer,
> > bcAccessLogDeserializer)
> > .mapValues(value => {
> > println("filteredSourceStream value: " + value)
> > value
> > })
> > .process(new CdcProcessorSupplier)
> >
> > val stream: KafkaStreams = new KafkaStreams(builder, streamingConfig)
> > println("\nstart filtering BcAccessLog test run: " + testRun + "\n")
> > stream.start()
> > }
> >
> > Regards,
> > Fred Patton
> >
>
>
>
> --
> -- Guozhang
>
--
Liquan Pei
Software Engineer, Confluent Inc
