kafka streams DSL: add an option parameter to disable repartition when using `map` `selectByKey` `groupBy`
0
According to the documents, streams will be marked for repartition when applied map selectKey groupBy even though the new key has been partitioned appropriately. Is it possible to add an option parameter to disable repartition ?
Here is my user case:
there is a topic has been partitioned by user_id.
# topic 'user', format '%key,%value'
partition-1:
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device2'
partition-2:
user2,'user_id':'user2', 'device_id':'device3'
user2,'user_id':'user2', 'device_id':'device4'
I want to count user_id-device_id pairs using DSL as follow:
stream
.groupBy((user_id, value) ->
JSONObject event = new JSONObject(value);
String userId = event.getString('user_id');
String deviceId = event.getString('device_id');
return String.format("%s&%s", userId,deviceId);
)
.count();
Actually the new key has been partitioned indirectly. There is no need to do it again.
apache-kafka-streams
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
add a comment |
0
According to the documents, streams will be marked for repartition when applied map selectKey groupBy even though the new key has been partitioned appropriately. Is it possible to add an option parameter to disable repartition ?
Here is my user case:
there is a topic has been partitioned by user_id.
# topic 'user', format '%key,%value'
partition-1:
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device2'
partition-2:
user2,'user_id':'user2', 'device_id':'device3'
user2,'user_id':'user2', 'device_id':'device4'
I want to count user_id-device_id pairs using DSL as follow:
stream
.groupBy((user_id, value) ->
JSONObject event = new JSONObject(value);
String userId = event.getString('user_id');
String deviceId = event.getString('device_id');
return String.format("%s&%s", userId,deviceId);
)
.count();
Actually the new key has been partitioned indirectly. There is no need to do it again.
apache-kafka-streams
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
add a comment |
0
0
0
According to the documents, streams will be marked for repartition when applied map selectKey groupBy even though the new key has been partitioned appropriately. Is it possible to add an option parameter to disable repartition ?
Here is my user case:
there is a topic has been partitioned by user_id.
# topic 'user', format '%key,%value'
partition-1:
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device2'
partition-2:
user2,'user_id':'user2', 'device_id':'device3'
user2,'user_id':'user2', 'device_id':'device4'
I want to count user_id-device_id pairs using DSL as follow:
stream
.groupBy((user_id, value) ->
JSONObject event = new JSONObject(value);
String userId = event.getString('user_id');
String deviceId = event.getString('device_id');
return String.format("%s&%s", userId,deviceId);
)
.count();
Actually the new key has been partitioned indirectly. There is no need to do it again.
apache-kafka-streams
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
According to the documents, streams will be marked for repartition when applied map selectKey groupBy even though the new key has been partitioned appropriately. Is it possible to add an option parameter to disable repartition ?
Here is my user case:
there is a topic has been partitioned by user_id.
# topic 'user', format '%key,%value'
partition-1:
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device1'
user1,'user_id':'user1', 'device_id':'device2'
partition-2:
user2,'user_id':'user2', 'device_id':'device3'
user2,'user_id':'user2', 'device_id':'device4'
I want to count user_id-device_id pairs using DSL as follow:
stream
.groupBy((user_id, value) ->
JSONObject event = new JSONObject(value);
String userId = event.getString('user_id');
String deviceId = event.getString('device_id');
return String.format("%s&%s", userId,deviceId);
)
.count();
Actually the new key has been partitioned indirectly. There is no need to do it again.
apache-kafka-streams
apache-kafka-streams
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
edited Nov 15 '18 at 2:17
Lifei Chen
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
asked Nov 13 '18 at 4:47
Lifei ChenLifei Chen
609
609
add a comment |
add a comment |
1 Answer
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0
If you use .groupBy(), it always causes data re-partitioning. If possible use groupByKey instead, which will re-partition data only if required.
In your case, you are changing the keys anyways, so that will create a re-partition topic.
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
In fact, the data has been partitioned indirectly (data is repartitioned by user_id, but user_id_device_id also be partitioned too), so repartition is not needed. Besides, I do not want to change the key of kafka record, I just want the key I used for aggregation in kafka streams is user_id_device_id but not user_id
– Lifei Chen
Nov 15 '18 at 2:14
GroupByKey/Aggregation won't change the key of the source topic. Instead, it creates a repartition topic as internal topic. That belongs to application.id
– Nishu Tayal
Nov 15 '18 at 8:36
Yes, my suggestion is whether it is possilbe that developer of kafka streams could add an option parameter to disable repartition (because it will generate repartition topics) and the key for aggregation not using the key of record directly but also key generated by value of record
– Lifei Chen
Nov 15 '18 at 9:33
No, it is not possible at the moment in Streams DSL directly. You can low level Processor API to implement custom logic to avoid the repartitioning
– Nishu Tayal
Nov 15 '18 at 10:00
Thanks, I will approve the answer, if there are features about it, please mention it in later comments. :)
– Lifei Chen
Nov 15 '18 at 10:06
add a comment |
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1 Answer
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0
If you use .groupBy(), it always causes data re-partitioning. If possible use groupByKey instead, which will re-partition data only if required.
In your case, you are changing the keys anyways, so that will create a re-partition topic.
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
In fact, the data has been partitioned indirectly (data is repartitioned by user_id, but user_id_device_id also be partitioned too), so repartition is not needed. Besides, I do not want to change the key of kafka record, I just want the key I used for aggregation in kafka streams is user_id_device_id but not user_id
– Lifei Chen
Nov 15 '18 at 2:14
GroupByKey/Aggregation won't change the key of the source topic. Instead, it creates a repartition topic as internal topic. That belongs to application.id
– Nishu Tayal
Nov 15 '18 at 8:36
Yes, my suggestion is whether it is possilbe that developer of kafka streams could add an option parameter to disable repartition (because it will generate repartition topics) and the key for aggregation not using the key of record directly but also key generated by value of record
– Lifei Chen
Nov 15 '18 at 9:33
No, it is not possible at the moment in Streams DSL directly. You can low level Processor API to implement custom logic to avoid the repartitioning
– Nishu Tayal
Nov 15 '18 at 10:00
Thanks, I will approve the answer, if there are features about it, please mention it in later comments. :)
– Lifei Chen
Nov 15 '18 at 10:06
add a comment |
0
If you use .groupBy(), it always causes data re-partitioning. If possible use groupByKey instead, which will re-partition data only if required.
In your case, you are changing the keys anyways, so that will create a re-partition topic.
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
In fact, the data has been partitioned indirectly (data is repartitioned by user_id, but user_id_device_id also be partitioned too), so repartition is not needed. Besides, I do not want to change the key of kafka record, I just want the key I used for aggregation in kafka streams is user_id_device_id but not user_id
– Lifei Chen
Nov 15 '18 at 2:14
GroupByKey/Aggregation won't change the key of the source topic. Instead, it creates a repartition topic as internal topic. That belongs to application.id
– Nishu Tayal
Nov 15 '18 at 8:36
Yes, my suggestion is whether it is possilbe that developer of kafka streams could add an option parameter to disable repartition (because it will generate repartition topics) and the key for aggregation not using the key of record directly but also key generated by value of record
– Lifei Chen
Nov 15 '18 at 9:33
No, it is not possible at the moment in Streams DSL directly. You can low level Processor API to implement custom logic to avoid the repartitioning
– Nishu Tayal
Nov 15 '18 at 10:00
Thanks, I will approve the answer, if there are features about it, please mention it in later comments. :)
– Lifei Chen
Nov 15 '18 at 10:06
add a comment |
0
0
0
If you use .groupBy(), it always causes data re-partitioning. If possible use groupByKey instead, which will re-partition data only if required.
In your case, you are changing the keys anyways, so that will create a re-partition topic.
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
If you use .groupBy(), it always causes data re-partitioning. If possible use groupByKey instead, which will re-partition data only if required.
In your case, you are changing the keys anyways, so that will create a re-partition topic.
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
answered Nov 14 '18 at 18:51
Nishu TayalNishu Tayal
11.8k73481
11.8k73481
In fact, the data has been partitioned indirectly (data is repartitioned by user_id, but user_id_device_id also be partitioned too), so repartition is not needed. Besides, I do not want to change the key of kafka record, I just want the key I used for aggregation in kafka streams is user_id_device_id but not user_id
– Lifei Chen
Nov 15 '18 at 2:14
GroupByKey/Aggregation won't change the key of the source topic. Instead, it creates a repartition topic as internal topic. That belongs to application.id
– Nishu Tayal
Nov 15 '18 at 8:36
Yes, my suggestion is whether it is possilbe that developer of kafka streams could add an option parameter to disable repartition (because it will generate repartition topics) and the key for aggregation not using the key of record directly but also key generated by value of record
– Lifei Chen
Nov 15 '18 at 9:33
No, it is not possible at the moment in Streams DSL directly. You can low level Processor API to implement custom logic to avoid the repartitioning
– Nishu Tayal
Nov 15 '18 at 10:00
Thanks, I will approve the answer, if there are features about it, please mention it in later comments. :)
– Lifei Chen
Nov 15 '18 at 10:06
add a comment |
In fact, the data has been partitioned indirectly (data is repartitioned by user_id, but user_id_device_id also be partitioned too), so repartition is not needed. Besides, I do not want to change the key of kafka record, I just want the key I used for aggregation in kafka streams is user_id_device_id but not user_id
– Lifei Chen
Nov 15 '18 at 2:14
GroupByKey/Aggregation won't change the key of the source topic. Instead, it creates a repartition topic as internal topic. That belongs to application.id
– Nishu Tayal
Nov 15 '18 at 8:36
Yes, my suggestion is whether it is possilbe that developer of kafka streams could add an option parameter to disable repartition (because it will generate repartition topics) and the key for aggregation not using the key of record directly but also key generated by value of record
– Lifei Chen
Nov 15 '18 at 9:33
No, it is not possible at the moment in Streams DSL directly. You can low level Processor API to implement custom logic to avoid the repartitioning
– Nishu Tayal
Nov 15 '18 at 10:00
Thanks, I will approve the answer, if there are features about it, please mention it in later comments. :)
– Lifei Chen
Nov 15 '18 at 10:06
In fact, the data has been partitioned indirectly (data is repartitioned by user_id, but user_id_device_id also be partitioned too), so repartition is not needed. Besides, I do not want to change the key of kafka record, I just want the key I used for aggregation in kafka streams is user_id_device_id but not user_id
– Lifei Chen
Nov 15 '18 at 2:14
In fact, the data has been partitioned indirectly (data is repartitioned by user_id, but user_id_device_id also be partitioned too), so repartition is not needed. Besides, I do not want to change the key of kafka record, I just want the key I used for aggregation in kafka streams is user_id_device_id but not user_id
– Lifei Chen
Nov 15 '18 at 2:14
GroupByKey/Aggregation won't change the key of the source topic. Instead, it creates a repartition topic as internal topic. That belongs to application.id
– Nishu Tayal
Nov 15 '18 at 8:36
GroupByKey/Aggregation won't change the key of the source topic. Instead, it creates a repartition topic as internal topic. That belongs to application.id
– Nishu Tayal
Nov 15 '18 at 8:36
Yes, my suggestion is whether it is possilbe that developer of kafka streams could add an option parameter to disable repartition (because it will generate repartition topics) and the key for aggregation not using the key of record directly but also key generated by value of record
– Lifei Chen
Nov 15 '18 at 9:33
Yes, my suggestion is whether it is possilbe that developer of kafka streams could add an option parameter to disable repartition (because it will generate repartition topics) and the key for aggregation not using the key of record directly but also key generated by value of record
– Lifei Chen
Nov 15 '18 at 9:33
No, it is not possible at the moment in Streams DSL directly. You can low level Processor API to implement custom logic to avoid the repartitioning
– Nishu Tayal
Nov 15 '18 at 10:00
No, it is not possible at the moment in Streams DSL directly. You can low level Processor API to implement custom logic to avoid the repartitioning
– Nishu Tayal
Nov 15 '18 at 10:00
Thanks, I will approve the answer, if there are features about it, please mention it in later comments. :)
– Lifei Chen
Nov 15 '18 at 10:06
Thanks, I will approve the answer, if there are features about it, please mention it in later comments. :)
– Lifei Chen
Nov 15 '18 at 10:06
add a comment |
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