I assigned the issue to me. Because I wanted to that for a very long
time. I already did some prerequisite work for the documentation in
`org.apache.flink.api.common.typeinfo.Types`.
Thanks,
Timo
Am 20.11.18 um 11:44 schrieb Flavio Pompermaier:
Sure! The problem is that Dataset API does an implicit conversion to
Tuples during chaining and I didn't found any documentation about this
(actually I was pleasantly surprised by the fact that the Table API
were supporting aggregates on null values..).
Here it is: https://issues.apache.org/jira/browse/FLINK-10947
Thanks for the reply,
Flavio
On Tue, Nov 20, 2018 at 11:33 AM Fabian Hueske <fhue...@gmail.com
<mailto:fhue...@gmail.com>> wrote:
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 <mailto: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();
}