Hi Flavio, Whether groupBy with null values works or not depends on the type of the key, or more specifically on the TypeComparator and TypeSerializer that are used to serialize, compare, and hash the key type. The processing engine supports null values If the comparator and serializer can handle null input values.
Flink SQL wraps keys in the Row type and the corresponding serializer / comparator can handle null fields. If you use Row in DataSet / DataStream programs, null values are supported as well. I think it would be good to discuss the handling of null keys on the documentation about data types [1] and link to that from operators that require keys. Would you mind creating a Jira issue for that? Thank you, Fabian [1] https://ci.apache.org/projects/flink/flink-docs-release-1.6/dev/types_serialization.html Am Mo., 19. Nov. 2018 um 12:31 Uhr schrieb Flavio Pompermaier < pomperma...@okkam.it>: > Hi to all, > we wanted to do a group by on elements that can contains null values and > we discovered that Table API support this while Dataset API does not. > Is this documented somehwere on the Flink site? > > Best, > Flavio > > ------------------------------------------------------- > > PS: you can test this with the following main: > > public static void main(String[] args) throws Exception { > final ExecutionEnvironment env = > ExecutionEnvironment.getExecutionEnvironment(); > final BatchTableEnvironment btEnv = > TableEnvironment.getTableEnvironment(env); > final DataSet<String> testDs = env > .fromElements("test", "test", "test2", "null", "null", "test3") > .map(x -> "null".equals(x) ? null : x); > > boolean testDatasetApi = true; > if (testDatasetApi) { > testDs.groupBy(x -> x).reduceGroup(new GroupReduceFunction<String, > Integer>() { > > @Override > public void reduce(Iterable<String> values, Collector<Integer> > out) throws Exception { > int cnt = 0; > for (String value : values) { > cnt++; > } > out.collect(cnt); > } > }).print(); > } > > btEnv.registerDataSet("TEST", testDs, "field1"); > Table res = btEnv.sqlQuery("SELECT field1, count(*) as cnt FROM TEST > GROUP BY field1"); > DataSet<Row> result = btEnv.toDataSet(res, > new RowTypeInfo(BasicTypeInfo.STRING_TYPE_INFO, > BasicTypeInfo.LONG_TYPE_INFO)); > result.print(); > } >
