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Flink: Document watermark generation feature #9179
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@@ -277,6 +277,75 @@ DataStream<Row> stream = env.fromSource(source, WatermarkStrategy.noWatermarks() | |
"Iceberg Source as Avro GenericRecord", new GenericRecordAvroTypeInfo(avroSchema)); | ||
``` | ||
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### 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-stable/docs/dev/datastream/event-time/generating_watermarks/#watermark-alignment), | ||
or prevent triggering [windows](https://nightlies.apache.org/flink/flink-docs-stable/docs/dev/datastream/operators/windows/) | ||
too early when reading multiple data files concurrently. | ||
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Enable watermark generation for an `IcebergSource` by setting the `watermarkColumn`. | ||
The supported column types are `timestamp`, `timestamptz` and `long`. | ||
Iceberg `timestamp` or `timestamptz` inherently contains the time precision. So there is no need | ||
to specify the time unit. But `long` type column doesn't contain time unit information. Use | ||
`watermarkTimeUnit` to configure the conversion for long columns. | ||
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The watermarks are generated based on column metrics stored for data files and emitted once per split. | ||
If multiple smaller files with different time ranges are combined into a single split, it can increase | ||
the out-of-orderliness and extra data buffering in the Flink state. The main purpose of watermark alignment | ||
is to reduce out-of-orderliness and excess data buffering in the Flink state. Hence it is recommended to | ||
set `read.split.open-file-cost` to a very large value to prevent combining multiple smaller files into a | ||
single split. The negative impact (of not combining small files into a single split) is on read throughput, | ||
especially if there are many small files. In typical stateful processing jobs, source read throughput is not | ||
the bottleneck. Hence this is probably a reasonable tradeoff. | ||
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This feature requires column-level min-max stats. Make sure stats are generated for the watermark column | ||
during write phase. By default, the column metrics are collected for the first 100 columns of the table. | ||
If watermark column doesn't have stats enabled by default, use | ||
[write properties](configuration.md#write-properties) starting with `write.metadata.metrics` when needed. | ||
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The following example could be useful if watermarks are used for windowing. The source reads Iceberg data files | ||
in order, using a timestamp column and emits watermarks: | ||
```java | ||
StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment(); | ||
TableLoader tableLoader = TableLoader.fromHadoopTable("hdfs://nn:8020/warehouse/path"); | ||
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DataStream<RowData> stream = | ||
env.fromSource( | ||
IcebergSource.forRowData() | ||
.tableLoader(tableLoader) | ||
// Watermark using timestamp column | ||
.watermarkColumn("timestamp_column") | ||
.build(), | ||
// Watermarks are generated by the source, no need to generate it manually | ||
WatermarkStrategy.<RowData>noWatermarks() | ||
// Extract event timestamp from records | ||
.withTimestampAssigner((record, eventTime) -> record.getTimestamp(pos, precision).getMillisecond()), | ||
SOURCE_NAME, | ||
TypeInformation.of(RowData.class)); | ||
``` | ||
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Example for reading Iceberg table using a long event column for watermark alignment: | ||
```java | ||
StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment(); | ||
TableLoader tableLoader = TableLoader.fromHadoopTable("hdfs://nn:8020/warehouse/path"); | ||
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DataStream<RowData> stream = | ||
env.fromSource( | ||
IcebergSource source = IcebergSource.forRowData() | ||
.tableLoader(tableLoader) | ||
// Disable combining multiple files to a single split | ||
.set(FlinkReadOptions.SPLIT_FILE_OPEN_COST, String.valueOf(TableProperties.SPLIT_SIZE_DEFAULT)) | ||
// Watermark using long column | ||
.watermarkColumn("long_column") | ||
.watermarkTimeUnit(TimeUnit.MILLI_SCALE) | ||
.build(), | ||
// Watermarks are generated by the source, no need to generate it manually | ||
WatermarkStrategy.<RowData>noWatermarks() | ||
.withWatermarkAlignment(watermarkGroup, maxAllowedWatermarkDrift), | ||
SOURCE_NAME, | ||
TypeInformation.of(RowData.class)); | ||
``` | ||
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## Options | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. we also need to update the read options section. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. There is no corresponding There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. oh. then we would need to add them. cc @mas-chen |
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### Read options | ||
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I'd include this in the previous example. I read this as a more advanced example as most users wouldn't need watermark alignment and so
withTimestampAssigner
could also be moved down here.There was a problem hiding this comment.
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I would keep this 2 as a separate example.
If I understand correctly @stevenzwu thinks that the watermark alignment is the most important feature of this change, and @mas-chen thinks that the ordering / windowing is more important.
Probably this is a good indication that both benefits are important 😄
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@mas-chen can you clarify your comment? I am not quite following.
@pvary it might be good to separate this into two code snippets. we can remove the two lines in the beginning.
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Oh I just think
should be advertised in the "basic" example. I think most people would just configure this, rather than the custom Timestamp assigner. This reduces code in the first example and keeps it simpler.
The 2nd example I consider as a more "advanced" example where we can show how to do the custom Timestamp assigner (and furthermore watermark alignment from the Flink perspective is an advanced feature--it requires lots of tuning and understanding of how it interacts with the watermark strategy--out of orderliness/idleness/etc).
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@mas-chen
.watermarkTimeUnit()
is only needed forlong
type column, which we don't know what's the precision. the first example is Icebergtimestamp
field which carries time unit inherently (currently only micro-second) and hence there is no need to ask user to set the time unit like the second example.timestamp assigner is for Flink
StreamRecord
timestamp, it is related to watermark generation / advancement at all.There was a problem hiding this comment.
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Thanks for the explantation, makes sense. Please disregard my comment!