Exception in thread "main" org.apache.kafka.streams.errors.TopologyBuilderException: Invalid topology building: KSTREAM-MAP-0000000001 and KTABLE-MAPVALUES-0000000004 are not joinable
 at org.apache.kafka.streams.kstream.internals.AbstractStream.ensureJoinableWith(AbstractStream.java:44)
 at org.apache.kafka.streams.kstream.internals.KStreamImpl.leftJoin(KStreamImpl.java:383)
 at io.confluent.examples.streams.PageViewRegionExample.main(PageViewRegionExample.java:102)
Schema schema = new Schema.Parser().parse(PageViewRegionExample.class.getResourceAsStream("/io/confluent/examples/streams/pageviewregion.avsc"));
Any reason why a KStream-KTable leftJoin would break topology rules?
You need to ensure, that both inputs are co-located.Âstream1 is not partitioned by the join key after the map. You need toÂtrigger re-partitioning using through()Â .
I don't see a call to through in the example following:
KStream<String, GenericRecord> viewsByUser = views.map((dummy, record) -> new KeyValue<>((String) record.get("user"), record));
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./bin/kafka-avro-console-producer --broker-list localhost:9092 --topic PageViews --property value.schema='{
"type": "record","name": "PageViews","fields": [{"name": "user", "type": "string"},{"name": "page", "type": "string"},{"name": "industry", "type": "string"}]}'
...
{"user":"Paul"},{"page":"www.kafka.org"},{"industry","non-profit"}
org.apache.kafka.common.errors.SerializationException: Error deserializing json {"user":"Paul"},{"page":"www.kafka.org"},{"industry","non-profit"} to Avro of schema {"type":"record","name":"PageViews","fields":[{"name":"user","type":"string"},{"name":"page","type":"string"},{"name":"industry","type":"string"}]}
Caused by: org.apache.avro.AvroTypeException: Expected string. Got END_OBJECT
at org.apache.avro.io.JsonDecoder.error(JsonDecoder.java:697)
at org.apache.avro.io.JsonDecoder.readString(JsonDecoder.java:227)
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I get a NullPointerDbException in PageViewRegionLambdaExample trying to write state to RocksDB and that's probably too hard for me to troubleshoot right now. See bottom of email for the stack.
Prior to this I had some cast exception to address with respect to deserialize Avro to String. This link with poster Aaron Kimball suggests we don't cast to String and use the toString method in here (I assume it's a required change for the examples):
There are several casts to String in this example, as well as for the non-Lambda one:
return new KeyValue<>((String) record.get("user"), record); // non-Lambda sample
return new KeyValue<>( record.get("user").toString(), record); // non-Lambda sample
KStream<String, GenericRecord> viewsByUser = views.map((dummy, record) -> new KeyValue<>( record.get("user").toString(), record))
.through("re-partitioning-topic");
KTable<String, String> userRegions = users.mapValues(record -> record.get("region").toString());
Stack trace:Exception in thread "StreamThread-1" java.lang.NullPointerException
at org.rocksdb.AbstractWriteBatch.put(AbstractWriteBatch.java:19)
at org.apache.kafka.streams.state.internals.RocksDBStore.putAllInternal(RocksDBStore.java:319)
at org.apache.kafka.streams.state.internals.RocksDBStore.flushCache(RocksDBStore.java:379)
at org.apache.kafka.streams.state.internals.RocksDBStore.flush(RocksDBStore.java:411)
at org.apache.kafka.streams.state.internals.MeteredKeyValueStore.flush(MeteredKeyValueStore.java:165)
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I wonder if anyone at Confluent has run this particular example recently and could confirm it normally works as it represents high pedagogical value.
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java -cp target/streams-examples-3.0.0-standalone.jar io.confluent.examples.streams.PageViewRegionLambdaExample
log4j:WARN No appenders could be found for logger (org.apache.kafka.streams.StreamsConfig).
log4j:WARN Please initialize the log4j system properly.
Exception in thread "StreamThread-1" java.lang.NullPointerException
at io.confluent.examples.streams.PageViewRegionLambdaExample.lambda$main$3(PageViewRegionLambdaExample.java:104)
at org.apache.kafka.streams.kstream.internals.KStreamMap$KStreamMapProcessor.process(KStreamMap.java:42)
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:68)
at org.apache.kafka.streams.processor.internals.StreamTask.forward(StreamTask.java:338)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:187)
at org.apache.kafka.streams.kstream.internals.KStreamKTableLeftJoin$KStreamKTableLeftJoinProcessor.process(KStreamKTableLeftJoin.java:61)
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:68)
at org.apache.kafka.streams.processor.internals.StreamTask.forward(StreamTask.java:338)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:187)
at org.apache.kafka.streams.processor.internals.SourceNode.process(SourceNode.java:64)
at org.apache.kafka.streams.processor.internals.StreamTask.process(StreamTask.java:174)
at org.apache.kafka.streams.processor.internals.StreamThread.runLoop(StreamThread.java:320)
at org.apache.kafka.streams.processor.internals.StreamThread.run(StreamThread.java:218)
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new KeyValue<>(record.get("user").toString(), record))
KTable<String, String> userRegions = users.mapValues(record -> record.get("region").toString());
whose key comes from users and that users is created just before as:
KTable<String, GenericRecord> users = builder.table("UserProfile");Object Users above gets "user" key from topic "UserProfile" and that comes from the new companion driver code that publishes on to the topic keysand values as follows with users being a normal Java String array that is initialized in the driver (with userProfilesTopic object below evaluating to "UserProfile":
for (String user : users) {
userProfileBuilder.set("experience", "some");userProfileBuilder.set("region", regions[random.nextInt(regions.length)]);producer.send(new ProducerRecord<>(userProfilesTopic, user, userProfileBuilder.build()));
Finally, we are in business to get the very impressive leftJoin, which is type safe (no messy "as" or String SQL stuff as in Spark 1.6/2.0 DataSets), no need to create an artificial class representing the resulting join, and concise thanks to JDK 8 Lambdas. The callback in braces that follow the selected rows/items view, regionis used to generate new data, the GenericRecord. Further transformations take place with that data and once all done, it's published to the topic and thus to Kafka. This Streams DSL looks quite elegant on first look!
.leftJoin(userRegions, (view, region) -> {
GenericRecord viewRegion = new GenericData.Record(schema);
viewRegion.put("user", view.get("user"));
viewRegion.put("page", view.get("page"));
viewRegion.put("region", region);
return viewRegion;
})
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Download Apache Kafka and Confluent Platform: www.confluent.io/download
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