mas-chen commented on code in PR #9179:
URL: https://github.com/apache/iceberg/pull/9179#discussion_r1409722185
##########
docs/flink-queries.md:
##########
@@ -277,6 +277,58 @@ DataStream<Row> stream = env.fromSource(source,
WatermarkStrategy.noWatermarks()
"Iceberg Source as Avro GenericRecord", new
GenericRecordAvroTypeInfo(avroSchema));
```
+### Emitting watermarks
+Emitting watermarks from the source itself could be beneficial for several
purposes, like harnessing the
+[Flink Watermark
Alignment](https://nightlies.apache.org/flink/flink-docs-release-1.18/docs/dev/datastream/event-time/generating_watermarks/#watermark-alignment)
+feature to prevent runaway readers, or providing triggers for [Flink
windowing](https://nightlies.apache.org/flink/flink-docs-release-1.18/docs/dev/datastream/operators/windows/).
+
+Enable watermark generation for an `IcebergSource` by setting the
`watermarkColumn`.
+The supported column types are `timestamp`, `timestamptz` and `long`.
+Timestamp columns are automatically converted to milliseconds since the Java
epoch of
+1970-01-01T00:00:00Z. Use `watermarkTimeUnit` to configure the conversion for
long columns.
+
+The watermarks are generated based on column metrics stored for data files and
emitted once per split.
+When using watermarks for Flink watermark alignment set
`read.split.open-file-cost` to prevent
+combining multiple files to a single split.
Review Comment:
Is there a tradeoff for increasing `read.split.open-file-cost`? Would a user
need to also tune the split throttling parameter to avoid memory issues?
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