Hi,
You can “skip” the corrupted message by returning `null` from the deserialize
method on the user-provided DeserializationSchema.
This lets the Kafka connector consider the record as processed, advances the
offset, but doesn’t emit anything downstream for it.
Hope this helps!
Cheers,
Gordon
On 20 June 2018 at 3:59:47 PM, Kien Truong (duckientru...@gmail.com) wrote:
Hi,
You can use FlatMap instead of Map, and only collect valid elements.
Regards,
Kien
On 6/20/2018 7:57 AM, chrisr123 wrote:
> First time I'm trying to get this to work so bear with me. I'm trying to
> learn checkpointing with Kafka and handling "bad" messages, restarting
> without losing state.
>
> Use Case:
> Use checkpointing.
> Read a stream of integers from Kafka, keep a running sum.
> If a "bad" Kafka message read, restart app, skip the "bad" message, keep
> state.
> My stream would something look like this:
>
> set1,5
> set1,7
> set1,foobar
> set1,6
>
> I want my app to keep a running sum of the integers it has seen, and restart
> if it crashes without losing state. so my running sum would be:
> 5,
> 12,
> app crashes and restarts
> 18
>
> However, I'm finding when my app restarts, it keeps reading the bad "foobar"
> message and doesnt get past it. Source code below. The mapper bombs when I
> try to parse "foobar" as an Integer.
> How can I modify app to get past "poison" message?
>
> env.enableCheckpointing(1000L);
> env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
>
> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
> env.getCheckpointConfig().setMinPauseBetweenCheckpoints(500L);
> env.getCheckpointConfig().setCheckpointTimeout(10000);
> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
> env.setStateBackend(new
> FsStateBackend("hdfs://mymachine:9000/flink/checkpoints"));
>
> Properties properties = new Properties();
> properties.setProperty("bootstrap.servers", BROKERS);
> properties.setProperty("zookeeper.connect", ZOOKEEPER_HOST);
> properties.setProperty("group.id", "consumerGroup1");
>
> FlinkKafkaConsumer08 kafkaConsumer = new FlinkKafkaConsumer08<>(topicName,
> new SimpleStringSchema(), properties);
> DataStream<String> messageStream = env.addSource(kafkaConsumer);
>
> DataStream<Tuple2<String,Integer>> sums = messageStream
> .map(new NumberMapper())
> .keyBy(0)
> .sum(1);
> sums.print();
>
>
> private static class NumberMapper implements
> MapFunction<String,Tuple2<String,Integer>> {
> public Tuple2<String,Integer> map(String input) throws Exception {
> return parseData(input);
> }
>
> private Tuple2<String,Integer> parseData(String record) {
>
> String[] tokens = record.toLowerCase().split(",");
>
> // Get Key
> String key = tokens[0];
>
> // Get Integer Value
> String integerValue = tokens[1];
> System.out.println("Trying to Parse=" + integerValue);
> Integer value = Integer.parseInt(integerValue);
>
> // Build TupleBoundedOutOfOrdernessGenerator
> return new Tuple2<String,Integer>(key, value);
> }
>
> }
>
>
>
>
> --
> Sent from:
> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/
