问题
I want to do a KStream to KTable Join. using KTable as just a lookup table. below steps shows the sequence in which code is executed
Construct KTable
ReKey KTable
Construct KStream
ReKey KStream
Join KStream - KTable
Lets say there are 8000 records in KStream, 14 records in KTable and Assuming that for each key in KStreams there is a record in KTable. So the expected output would be 8000 records.
Every time i do a join for first time or when i start the application. Expected output is 8000 records but i see only 6200 records sometimes, sometimes 8000 complete set of records(twice), some times no record, etc.
Question 1: why is there inconsistency in records every single time i run the application?
Before the KTable gets constructed(construct + Rekey), KStreams gets Constructed and data is available for join from KStream side then join starts with out KTable so there wont be data seen in final join until KTable is constructed. after once KTable is constructed then we can see join happening for the remaining records.
Question 2: How to resolve the inconsistency join in records?
I tried with Test case using Embedded Kafka for KStream and Ktable join. There was 10 records from KStreams and 3 records from KTable which were used process. when i ran the test case for the first time There was no Join and i didn’t see any data after join. When ran the same second time it ran perfectly. If i clear the state store then back to zero.
Question 3: Why is this behaviour happening?
I tried with KSQL and the join was working perfectly and i got 8000 records, then i went into KSQL source code, i noticed KSQL is also doing same Join function.
Question 4: How is KSQL resolving the issue?
I saw few example suggested answers
- Use GlobalKTable which didn’t work. i got same inconsistent join.
- use Custom joiner https://github.com/confluentinc/kafka-streams-examples/blob/5.2.1-post/src/test/java/io/confluent/examples/streams/CustomStreamTableJoinIntegrationTest.java which didn’t work
I am using spring cloud streams as dependency.
Also i saw there was a open issue regarding this somewhere on JIRA.
回答1:
below steps shows the sequence in which code is executed
Note that building a topology is just providing a logical description of data flow program and there is no "order of execution" of different operator. The program will be translated and all operator will be execute at the same time. Hence, data from all topics will be read in parallel.
This parallel processing is the root cause of your observation, i.e., the table is not loaded first before processing begins (at least there is no guarantee by default) and thus streams-side data may be processed even if the table is not fully loaded.
The order of processing between different topic depend on the record timestamps: records with smaller timestamps are processed first. Hence, if you want to ensure that the KTable data is processed first, you must ensure that the record timestamps are smaller than the stream-side record timestamps. This can either be ensured when you produce the input data into the input topic, or by using a custom timestamp extractor.
Second, fetching data from topics is non-deterministic and thus, if data for only the stream side is returned (but not table side data) a timestamp comparison cannot be done and thus the stream-side data would be processed before the table side data. To tackle this issue, you can increase configuration parameter max.task.idle.ms (default is 0ms). If you increase this config (and I believe that is what KSQL also does by default) if there is no data for one input the task will block and try to fetch data for the empty input (only after the idle time passed, processing would continue even if one side is empty).
For a GlobalKTable the behavior is different. This table would be loaded on startup before any processing starts. Hence, I am not sure why this did not work for you.
来源：https://stackoverflow.com/questions/60588408/kstream-to-ktable-inner-join-producing-different-number-of-records-every-time-pr