echauchot commented on a change in pull request #11055: [BEAM-9436] Improve GBK
in spark structured streaming runner
URL: https://github.com/apache/beam/pull/11055#discussion_r397207312
##########
File path:
runners/spark/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/functions/GroupAlsoByWindowViaOutputBufferFn.java
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@@ -65,9 +65,15 @@ public GroupAlsoByWindowViaOutputBufferFn(
@Override
public Iterator<WindowedValue<KV<K, Iterable<InputT>>>> call(
- KV<K, Iterable<WindowedValue<InputT>>> kv) throws Exception {
- K key = kv.getKey();
- Iterable<WindowedValue<InputT>> values = kv.getValue();
+ K key, Iterator<WindowedValue<KV<K, InputT>>> iterator) throws Exception
{
+
+ // we have to meterialize the Iterator because
ReduceFnRunner.processElements expects
+ // ArrayList<WindowedValue<InputT>> and not Iterator<WindowedValue<KV<K,
InputT>>>
+ ArrayList<WindowedValue<InputT>> values = new ArrayList<>();
+ while (iterator.hasNext()) {
+ WindowedValue<KV<K, InputT>> wv = iterator.next();
+ values.add(wv.withValue(wv.getValue().getValue()));
Review comment:
in previous impl materialization to list was already there
I know about the javadoc but as stated in my comment in the code, it is
unavoidable due to the reduceFnRunner needing a list as input.
Anyway I measured during the load test (see results above) in a tiny JVM and
I got no OOM, I only got spill to disc of GB of data
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