claudevdm commented on code in PR #38015:
URL: https://github.com/apache/beam/pull/38015#discussion_r3018596507
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sdks/python/apache_beam/io/gcp/bigquery_change_history.py:
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@@ -1170,16 +1315,46 @@ def expand(self, pbegin: beam.pvalue.PBegin) ->
beam.PCollection:
row_filter=self._row_filter))
| 'CommitQueryResults' >> beam.Reshuffle())
+ emit_raw = self._decompress_shards is not None
+
+ read_sdf = beam.ParDo(
+ _ReadStorageStreamsSDF(
+ batch_arrow_read=self._batch_arrow_read,
+ change_timestamp_column=self._change_timestamp_column,
+ max_split_rounds=self._max_split_rounds,
+ emit_raw_batches=emit_raw))
+ if emit_raw:
+ read_sdf = read_sdf.with_output_types(Tuple[bytes, bytes])
+ else:
+ read_sdf = read_sdf.with_output_types(Dict[str, Any])
+
read_outputs = (
query_results
- | 'ReadStorageStreams' >> beam.ParDo(
- _ReadStorageStreamsSDF(
- batch_arrow_read=self._batch_arrow_read,
- change_timestamp_column=self._change_timestamp_column)).
- with_outputs(_CLEANUP_TAG, main='rows'))
+ | 'ReadStorageStreams' >> read_sdf.with_outputs(
+ _CLEANUP_TAG, main='rows'))
_ = (
read_outputs[_CLEANUP_TAG]
| 'CleanupTempTables' >> beam.ParDo(_CleanupTempTablesFn()))
- return read_outputs['rows']
+ if emit_raw:
+ # Fan out raw Arrow batches across decompress_shards workers
+ # via GBK, then decompress and convert to timestamped row dicts.
+ # Uses a discarding trigger so GBK fires per-element without
+ # waiting for the GlobalWindow to close.
+ num_shards = self._decompress_shards
+ rows = (
+ read_outputs['rows']
+ | 'ShardBatches' >>
+ beam.WithKeys(lambda _, n=num_shards: random.randint(0, n - 1))
+ | 'WindowForGBK' >> beam.WindowInto(
+ GlobalWindows(),
+ trigger=beam_trigger.Repeatedly(beam_trigger.AfterCount(1)),
+ accumulation_mode=(beam_trigger.AccumulationMode.DISCARDING))
+ | 'GroupByShardKey' >> beam.GroupByKey()
Review Comment:
Also it is potentially easier to control the watermarks if a we need to add
the ability for a user to specify a non-standard column to use for event time.
Then if we decompress in the sdf we can advance watermark in the sdf to
max(observed event time) instead of the poll query range end
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