Hi, As a simple test, you can put your key extraction logic into a MapFunction, i.e. MapFunction<T extends SignalSet<?>, Tuple2<String, T>> and then simply use that field as the key:
input .map(new MyKeyExtractorMapper()) .keyBy(0) If that solves your problem it means that the key extraction is not deterministic. This is a problem because getKey() is called at different points in time and when the result is not always the same you will get that error. Best, Aljoscha > On 12. Jun 2017, at 22:04, Meera <mvengadasu...@ebay.com> wrote: > > Did this problem get resolved > > - I am running into this problem when I parallelize the tasks > Unexpected key group index. This indicates a bug. > > - it runs fine on 1 parallelism. This suggests there is some key grouping > issue - I checked my Watermark and KeySelector - they look okay. > > The snippet of my KeySelector and Watermark attached to the KeyedStream. > public class DimensionKeySelector<T extends SignalSet<?>> implements > KeySelector<T, String> { > > private static final long serialVersionUID = 7666263008141606451L; > private final String[] dimKeys; > > public DimensionKeySelector(Map<String, String> conf) { > if (conf.containsKey("dimKeys") == false) { > throw new RuntimeException("Required 'dimKeys' > missing."); > } > this.dimKeys = conf.get("dimKeys").split(","); > } > > @Override > public String getKey(T signalSet) throws Exception { > StringBuffer group = new StringBuffer(signalSet.namespace()); > if (signalSet.size() != 0) { > for (String dim : dimKeys) { > if (signalSet.dimensions().containsKey(dim)) { > > group.append(signalSet.dimensions().get(dim)); > } > } > } > return group.toString(); > } > } > > and Watermark > public class WaterMarks extends > BoundedOutOfOrdernessTimestampExtractor<MetricSignalSet> { > > public WaterMarks(Time maxOutOfOrderness) { > super(maxOutOfOrderness); > } > > private static final long serialVersionUID = 1L; > > @Override > public long extractTimestamp(MetricSignalSet element) { > return element.get(0).timestamp().getTime(); > } > } > > Any thoughts? > > > > > -- > View this message in context: > http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Window-Function-on-AllWindowed-Stream-Combining-Kafka-Topics-tp12941p13663.html > Sent from the Apache Flink User Mailing List archive. mailing list archive at > Nabble.com.