Proper way to assign watermark with DateStreamSource<List> using Flink
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I have a continuing JSONArray data produced to Kafka topic,and I wanna process records with EventTime characteristic.In order to reach this goal,I have to assign watermark to each record which contained in the JSONArray.
I didn't find a convenience way to achieve this goal.My solution is consuming data from DataStreamSource> ,then iterate List and collect Object to downstream with an anonymous ProcessFunction,finally assign watermark to the this downstream.
The major code shows below:
DataStreamSource<List<MockData>> listDataStreamSource = KafkaSource.genStream(env);
SingleOutputStreamOperator<MockData> convertToPojo = listDataStreamSource
.process(new ProcessFunction<List<MockData>, MockData>() {
@Override
public void processElement(List<MockData> value, Context ctx, Collector<MockData> out)
throws Exception {
value.forEach(mockData -> out.collect(mockData));
}
});
convertToPojo.assignTimestampsAndWatermarks(
new BoundedOutOfOrdernessTimestampExtractor<MockData>(Time.seconds(5)) {
@Override
public long extractTimestamp(MockData element) {
return element.getTimestamp();
}
});
SingleOutputStreamOperator<Tuple2<String, Long>> countStream = convertToPojo
.keyBy("country").window(
SlidingEventTimeWindows.of(Time.seconds(10), Time.seconds(10)))
.process(
new FlinkEventTimeCountFunction()).name("count elements");
The code seems all right without doubt,running without error as well.But ProcessWindowFunction never triggered.I tracked the Flink source code,find EventTimeTrigger never returns TriggerResult.FIRE,causing by TriggerContext.getCurrentWatermark returns Long.MIN_VALUE all the time.
What's the proper way to process List in eventtime?Any suggestion will be appreciated.
apache-flink flink-streaming
add a comment |
I have a continuing JSONArray data produced to Kafka topic,and I wanna process records with EventTime characteristic.In order to reach this goal,I have to assign watermark to each record which contained in the JSONArray.
I didn't find a convenience way to achieve this goal.My solution is consuming data from DataStreamSource> ,then iterate List and collect Object to downstream with an anonymous ProcessFunction,finally assign watermark to the this downstream.
The major code shows below:
DataStreamSource<List<MockData>> listDataStreamSource = KafkaSource.genStream(env);
SingleOutputStreamOperator<MockData> convertToPojo = listDataStreamSource
.process(new ProcessFunction<List<MockData>, MockData>() {
@Override
public void processElement(List<MockData> value, Context ctx, Collector<MockData> out)
throws Exception {
value.forEach(mockData -> out.collect(mockData));
}
});
convertToPojo.assignTimestampsAndWatermarks(
new BoundedOutOfOrdernessTimestampExtractor<MockData>(Time.seconds(5)) {
@Override
public long extractTimestamp(MockData element) {
return element.getTimestamp();
}
});
SingleOutputStreamOperator<Tuple2<String, Long>> countStream = convertToPojo
.keyBy("country").window(
SlidingEventTimeWindows.of(Time.seconds(10), Time.seconds(10)))
.process(
new FlinkEventTimeCountFunction()).name("count elements");
The code seems all right without doubt,running without error as well.But ProcessWindowFunction never triggered.I tracked the Flink source code,find EventTimeTrigger never returns TriggerResult.FIRE,causing by TriggerContext.getCurrentWatermark returns Long.MIN_VALUE all the time.
What's the proper way to process List in eventtime?Any suggestion will be appreciated.
apache-flink flink-streaming
add a comment |
I have a continuing JSONArray data produced to Kafka topic,and I wanna process records with EventTime characteristic.In order to reach this goal,I have to assign watermark to each record which contained in the JSONArray.
I didn't find a convenience way to achieve this goal.My solution is consuming data from DataStreamSource> ,then iterate List and collect Object to downstream with an anonymous ProcessFunction,finally assign watermark to the this downstream.
The major code shows below:
DataStreamSource<List<MockData>> listDataStreamSource = KafkaSource.genStream(env);
SingleOutputStreamOperator<MockData> convertToPojo = listDataStreamSource
.process(new ProcessFunction<List<MockData>, MockData>() {
@Override
public void processElement(List<MockData> value, Context ctx, Collector<MockData> out)
throws Exception {
value.forEach(mockData -> out.collect(mockData));
}
});
convertToPojo.assignTimestampsAndWatermarks(
new BoundedOutOfOrdernessTimestampExtractor<MockData>(Time.seconds(5)) {
@Override
public long extractTimestamp(MockData element) {
return element.getTimestamp();
}
});
SingleOutputStreamOperator<Tuple2<String, Long>> countStream = convertToPojo
.keyBy("country").window(
SlidingEventTimeWindows.of(Time.seconds(10), Time.seconds(10)))
.process(
new FlinkEventTimeCountFunction()).name("count elements");
The code seems all right without doubt,running without error as well.But ProcessWindowFunction never triggered.I tracked the Flink source code,find EventTimeTrigger never returns TriggerResult.FIRE,causing by TriggerContext.getCurrentWatermark returns Long.MIN_VALUE all the time.
What's the proper way to process List in eventtime?Any suggestion will be appreciated.
apache-flink flink-streaming
I have a continuing JSONArray data produced to Kafka topic,and I wanna process records with EventTime characteristic.In order to reach this goal,I have to assign watermark to each record which contained in the JSONArray.
I didn't find a convenience way to achieve this goal.My solution is consuming data from DataStreamSource> ,then iterate List and collect Object to downstream with an anonymous ProcessFunction,finally assign watermark to the this downstream.
The major code shows below:
DataStreamSource<List<MockData>> listDataStreamSource = KafkaSource.genStream(env);
SingleOutputStreamOperator<MockData> convertToPojo = listDataStreamSource
.process(new ProcessFunction<List<MockData>, MockData>() {
@Override
public void processElement(List<MockData> value, Context ctx, Collector<MockData> out)
throws Exception {
value.forEach(mockData -> out.collect(mockData));
}
});
convertToPojo.assignTimestampsAndWatermarks(
new BoundedOutOfOrdernessTimestampExtractor<MockData>(Time.seconds(5)) {
@Override
public long extractTimestamp(MockData element) {
return element.getTimestamp();
}
});
SingleOutputStreamOperator<Tuple2<String, Long>> countStream = convertToPojo
.keyBy("country").window(
SlidingEventTimeWindows.of(Time.seconds(10), Time.seconds(10)))
.process(
new FlinkEventTimeCountFunction()).name("count elements");
The code seems all right without doubt,running without error as well.But ProcessWindowFunction never triggered.I tracked the Flink source code,find EventTimeTrigger never returns TriggerResult.FIRE,causing by TriggerContext.getCurrentWatermark returns Long.MIN_VALUE all the time.
What's the proper way to process List in eventtime?Any suggestion will be appreciated.
apache-flink flink-streaming
apache-flink flink-streaming
asked Nov 22 '18 at 6:32
![](https://i.stack.imgur.com/ndcFU.jpg?s=32&g=1)
![](https://i.stack.imgur.com/ndcFU.jpg?s=32&g=1)
moyigukemoyiguke
255
255
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add a comment |
1 Answer
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The problem is that you are applying the keyBy and window operations to the convertToPojo stream, rather than the stream with timestamps and watermarks (which you didn't assign to a variable).
If you write the code more or less like this, it should work:
listDataStreamSource = KafkaSource ...
convertToPojo = listDataStreamSource.process ...
pojoPlusWatermarks = convertToPojo.assignTimestampsAndWatermarks ...
countStream = pojoPlusWatermarks.keyBy ...
Calling assignTimestampsAndWatermarks on the convertToPojo stream does not modify that stream, but rather creates a new datastream object that includes timestamps and watermarks. You need to apply your windowing to that new datastream.
Very glad to see you,and thanks for you prompt reply .I don't quite understand that,is it means user can not assign watermark to down stream other than source stream.As I find SourceFunction has collectWithTimestamp but none in Collector.
– moyiguke
Nov 23 '18 at 9:51
I've expanded my answer to hopefully be more clear.
– David Anderson
Nov 23 '18 at 10:03
Thank you so much !!! Your precise explanation enlightened me,following your guide and pseudocode,it works well now.
– moyiguke
Nov 24 '18 at 14:24
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
The problem is that you are applying the keyBy and window operations to the convertToPojo stream, rather than the stream with timestamps and watermarks (which you didn't assign to a variable).
If you write the code more or less like this, it should work:
listDataStreamSource = KafkaSource ...
convertToPojo = listDataStreamSource.process ...
pojoPlusWatermarks = convertToPojo.assignTimestampsAndWatermarks ...
countStream = pojoPlusWatermarks.keyBy ...
Calling assignTimestampsAndWatermarks on the convertToPojo stream does not modify that stream, but rather creates a new datastream object that includes timestamps and watermarks. You need to apply your windowing to that new datastream.
Very glad to see you,and thanks for you prompt reply .I don't quite understand that,is it means user can not assign watermark to down stream other than source stream.As I find SourceFunction has collectWithTimestamp but none in Collector.
– moyiguke
Nov 23 '18 at 9:51
I've expanded my answer to hopefully be more clear.
– David Anderson
Nov 23 '18 at 10:03
Thank you so much !!! Your precise explanation enlightened me,following your guide and pseudocode,it works well now.
– moyiguke
Nov 24 '18 at 14:24
add a comment |
The problem is that you are applying the keyBy and window operations to the convertToPojo stream, rather than the stream with timestamps and watermarks (which you didn't assign to a variable).
If you write the code more or less like this, it should work:
listDataStreamSource = KafkaSource ...
convertToPojo = listDataStreamSource.process ...
pojoPlusWatermarks = convertToPojo.assignTimestampsAndWatermarks ...
countStream = pojoPlusWatermarks.keyBy ...
Calling assignTimestampsAndWatermarks on the convertToPojo stream does not modify that stream, but rather creates a new datastream object that includes timestamps and watermarks. You need to apply your windowing to that new datastream.
Very glad to see you,and thanks for you prompt reply .I don't quite understand that,is it means user can not assign watermark to down stream other than source stream.As I find SourceFunction has collectWithTimestamp but none in Collector.
– moyiguke
Nov 23 '18 at 9:51
I've expanded my answer to hopefully be more clear.
– David Anderson
Nov 23 '18 at 10:03
Thank you so much !!! Your precise explanation enlightened me,following your guide and pseudocode,it works well now.
– moyiguke
Nov 24 '18 at 14:24
add a comment |
The problem is that you are applying the keyBy and window operations to the convertToPojo stream, rather than the stream with timestamps and watermarks (which you didn't assign to a variable).
If you write the code more or less like this, it should work:
listDataStreamSource = KafkaSource ...
convertToPojo = listDataStreamSource.process ...
pojoPlusWatermarks = convertToPojo.assignTimestampsAndWatermarks ...
countStream = pojoPlusWatermarks.keyBy ...
Calling assignTimestampsAndWatermarks on the convertToPojo stream does not modify that stream, but rather creates a new datastream object that includes timestamps and watermarks. You need to apply your windowing to that new datastream.
The problem is that you are applying the keyBy and window operations to the convertToPojo stream, rather than the stream with timestamps and watermarks (which you didn't assign to a variable).
If you write the code more or less like this, it should work:
listDataStreamSource = KafkaSource ...
convertToPojo = listDataStreamSource.process ...
pojoPlusWatermarks = convertToPojo.assignTimestampsAndWatermarks ...
countStream = pojoPlusWatermarks.keyBy ...
Calling assignTimestampsAndWatermarks on the convertToPojo stream does not modify that stream, but rather creates a new datastream object that includes timestamps and watermarks. You need to apply your windowing to that new datastream.
edited Nov 23 '18 at 10:03
answered Nov 22 '18 at 8:35
![](https://i.stack.imgur.com/ILyg6.jpg?s=32&g=1)
![](https://i.stack.imgur.com/ILyg6.jpg?s=32&g=1)
David AndersonDavid Anderson
6,77821424
6,77821424
Very glad to see you,and thanks for you prompt reply .I don't quite understand that,is it means user can not assign watermark to down stream other than source stream.As I find SourceFunction has collectWithTimestamp but none in Collector.
– moyiguke
Nov 23 '18 at 9:51
I've expanded my answer to hopefully be more clear.
– David Anderson
Nov 23 '18 at 10:03
Thank you so much !!! Your precise explanation enlightened me,following your guide and pseudocode,it works well now.
– moyiguke
Nov 24 '18 at 14:24
add a comment |
Very glad to see you,and thanks for you prompt reply .I don't quite understand that,is it means user can not assign watermark to down stream other than source stream.As I find SourceFunction has collectWithTimestamp but none in Collector.
– moyiguke
Nov 23 '18 at 9:51
I've expanded my answer to hopefully be more clear.
– David Anderson
Nov 23 '18 at 10:03
Thank you so much !!! Your precise explanation enlightened me,following your guide and pseudocode,it works well now.
– moyiguke
Nov 24 '18 at 14:24
Very glad to see you,and thanks for you prompt reply .I don't quite understand that,is it means user can not assign watermark to down stream other than source stream.As I find SourceFunction has collectWithTimestamp but none in Collector.
– moyiguke
Nov 23 '18 at 9:51
Very glad to see you,and thanks for you prompt reply .I don't quite understand that,is it means user can not assign watermark to down stream other than source stream.As I find SourceFunction has collectWithTimestamp but none in Collector.
– moyiguke
Nov 23 '18 at 9:51
I've expanded my answer to hopefully be more clear.
– David Anderson
Nov 23 '18 at 10:03
I've expanded my answer to hopefully be more clear.
– David Anderson
Nov 23 '18 at 10:03
Thank you so much !!! Your precise explanation enlightened me,following your guide and pseudocode,it works well now.
– moyiguke
Nov 24 '18 at 14:24
Thank you so much !!! Your precise explanation enlightened me,following your guide and pseudocode,it works well now.
– moyiguke
Nov 24 '18 at 14:24
add a comment |
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