Andreas, I agree that it might be a bug, but it's unclear what is happening -- it would be helpful to understand the scenario better to file a descriptive JIRA that helps to fix the issue.
Btw: Kafka 0.10.2.1 got release yesterday -- maybe you can try the new release and report if it works there on not (there are a couple of bug fixes for Streams) If you receive a random number of output records, are this records from consecutive offsets in the input topic? Or record with random offsets? Also, when your application does not write all record to the output topic, what is the committed offsets for the input topic? I ask this as I would like to understand if Stream get stuck at some point, of if the input got get consumed but message get lost in the middle. Did you check the logs? Maybe increasing the log level to DEBUG (or even TRACE) might revile some insight. Did you register and UncaughtExceptionHandler (cf. http://docs.confluent.io/current/streams/developer-guide.html#using-kafka-streams-within-your-application-code). This might help to see if a thread dies or not. Do you run single thread on both Stream instances? Do you change any other default StreamsConfig setting? -Matthias On 4/25/17 12:56 AM, Andreas Voss wrote: > Hi Matthias, > > thank you for your response. Here are some more details: > > - my input and output topics have 6 partitions each. > - my application instances run from docker images so the is no state left > over from a previous run > - I have a single docker container running kafka + zookeeper (spotify/kafka). > - when the second consumer is in place, I receive a random number of records > in the target topic (e.g. I send 1000 records and receive 439 on first run > and 543 on second run) > - the problem only occurs if two instances of the application are running. If > I only start one instance then it's slow but when I send 1000 records I also > receive 1000 records. I think this is also an indicator for a bug, because a > streaming app should behave the same, independent of whether one or two > instances are running. > - I added the properties you suggested, but behavior did not change. > > I think this is a bug, consumers of different groups should not interact with > each other. Should I submit a bug report and if so, any suggestions on how to > do that? > > Andreas > > > -----Ursprüngliche Nachricht----- > Von: Matthias J. Sax [mailto:matth...@confluent.io] > Gesendet: Montag, 24. April 2017 19:18 > An: users@kafka.apache.org > Betreff: Re: Consumer with another group.id conflicts with streams() > > Hi, > > hard to diagnose. The new consumer should not affect the Streams app though > -- even if I am wondering why you need it. > >> KafkaConsumer (with a UUID as group.id) that reads some historical >> data from input topic > > Maybe using GlobalKTable instead might be a better solution? > >> (i.e. I feed 1000 records into source topic and receive around 200 on >> the target topic) > > Are this the first 200 records? Or are those 200 record "random ones" > from your input topic? How many partitions do you have for input/output topic? > >> looks like a lot of rebalancing happens. > > We recommend to change StreamsConfig values as follows to improve in > rebalance behavior: > >> props.put(ProducerConfig.RETRIES_CONFIG, 10); <---- increase to 10 >> from default of 0 >> props.put(ConsumerConfig.MAX_POLL_INTERVAL_MS_CONFIG, >> Integer.toString(Integer.MAX_VALUE)); <--------- increase to infinity >> from default of 300 s > > We will change the default values accordingly in future release but for now > you should set this manually. > > > Hope this helps. > > > -Matthias > > On 4/24/17 10:01 AM, Andreas Voss wrote: >> Hi, I have a simple streaming app that copies data from one topic to >> another, so when I feed 1000 records into source topic I receive 1000 >> records in the target topic. Also the app contains a transform() step which >> does nothing, except instantiating a KafkaConsumer (with a UUID as group.id) >> that reads some historical data from input topic. As soon as this consumer >> is in place, the streaming app does not work anymore, records get lost (i.e. >> I feed 1000 records into source topic and receive around 200 on the target >> topic) and it's terribly slow - looks like a lot of rebalancing happens. >> >> To me this looks like a bug, because the KStreamBuilder uses the application >> id as group.id ("kafka-smurfing" in this case), and the transformer uses a >> different one (uuid). >> >> Full source code: >> >> public class Main { >> >> public static final String BOOTSTRAP_SERVERS = "192.168.99.100:9092"; >> public static final String SOURCE_TOPIC = "transactions"; >> public static final String TARGET_TOPIC = "alerts"; >> >> public static void main(String[] args) throws Exception { >> >> KStreamBuilder builder = new KStreamBuilder(); >> builder.stream(Serdes.String(), Serdes.String(), SOURCE_TOPIC) >> .transform(() -> new DebugTransformer()) >> .to(Serdes.String(), Serdes.String(), TARGET_TOPIC); >> >> Properties props = new Properties(); >> props.put(StreamsConfig.APPLICATION_ID_CONFIG, "kafka-smurfing"); >> props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, >> Main.BOOTSTRAP_SERVERS); >> props.put(StreamsConfig.KEY_SERDE_CLASS_CONFIG, >> Serdes.String().getClass().getName()); >> props.put(StreamsConfig.VALUE_SERDE_CLASS_CONFIG, >> Serdes.String().getClass().getName()); >> props.put(StreamsConfig.NUM_STREAM_THREADS_CONFIG, 2); >> props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest"); >> >> KafkaStreams streams = new KafkaStreams(builder, props); >> streams.start(); >> Runtime.getRuntime().addShutdownHook(new Thread(streams::close)); >> >> } >> >> } >> >> public class DebugTransformer implements Transformer<String, String, >> KeyValue<String, String>> { >> >> private KafkaConsumer<String, String> consumer; >> private ProcessorContext context; >> >> @Override >> public void init(ProcessorContext context) { >> this.context = context; >> Properties props = new Properties(); >> props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, >> Main.BOOTSTRAP_SERVERS); >> props.put(ConsumerConfig.GROUP_ID_CONFIG, UUID.randomUUID().toString()); >> props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "none"); >> props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "false"); >> props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, >> StringDeserializer.class.getName()); >> props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, >> StringDeserializer.class.getName()); >> consumer = new KafkaConsumer<>(props); >> } >> >> @Override >> public KeyValue<String, String> transform(String key, String value) { >> TopicPartition partition = new TopicPartition(Main.SOURCE_TOPIC, >> context.partition()); >> consumer.assign(Arrays.asList(partition)); >> consumer.seek(partition, 0); >> consumer.poll(100); >> return KeyValue.pair(key, value); >> } >> >> @Override >> public void close() { >> consumer.close(); >> } >> >> @Override >> public KeyValue<String, String> punctuate(long timestamp) { >> return null; >> } >> >> } >> >> Thanks for any hints, >> Andreas >> >> This email and any files transmitted with it are confidential, proprietary >> and intended solely for the individual or entity to whom they are addressed. >> If you have received this email in error please delete it immediately. >> > > This email and any files transmitted with it are confidential, proprietary > and intended solely for the individual or entity to whom they are addressed. > If you have received this email in error please delete it immediately. >
signature.asc
Description: OpenPGP digital signature
