Kafka main parsing loop

One of the threads from scheduled_pool (pre 20.9) / background_message_broker_schedule_pool (after 20.9) do that in infinite loop:

  1. Batch poll (time limit: kafka_poll_timeout_ms 500ms, messages limit: kafka_poll_max_batch_size 65536)
  2. Parse messages.
  3. If we don’t have enough data (rows limit: kafka_max_block_size 1048576) or time limit reached (kafka_flush_interval_ms 7500ms) - continue polling (goto p.1)
  4. Write a collected block of data to MV
  5. Do commit (commit after write = at-least-once).

On any error, during that process, Kafka client is restarted (leading to rebalancing - leave the group and get back in few seconds).

Kafka batching

Important settings

These usually should not be adjusted:

  • kafka_poll_max_batch_size = max_block_size (65536)
  • kafka_poll_timeout_ms = stream_poll_timeout_ms (500ms)

You may want to adjust those depending on your scenario:

  • kafka_flush_interval_ms = stream_poll_timeout_ms (7500ms)
  • kafka_max_block_size = max_insert_block_size / kafka_num_consumers (for the single consumer: 1048576)

See also


Disable at-least-once delivery

kafka_commit_every_batch = 1 will change the loop logic mentioned above. Consumed batch commited to the Kafka and the block of rows send to Materialized Views only after that. It could be resembled as at-most-once delivery mode as prevent duplicate creation but allow loss of data in case of failures.