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Roman Shtykh commented on IGNITE-2016: -------------------------------------- Denis, Yes, it makes sense. Thank you. The only remaining issue is using autoflushing. We already invoke _IgniteDataStreamer.flush()_ on _SinkTask.put(...)_, which interval can be configured by the user. Therefore I think we don't need to expose __IgniteDataStreamer_'s autoflushing. Do you agree? As to buffering on _SinkTask.put(...)_ and then flushing, it is needed to increase throughput (pretty common). It is needed only in case we use _cache.putAll(...)_, which was my first solution. _In fact, in many cases internal buffering will be useful so an entire batch of records can be sent at once, reducing the overhead of inserting events into the downstream data store._ http://kafka.apache.org/documentation.html#connect As I understand, the same thing is achieved _IgniteDataStreamer_ and, since we go with it, explicit buffering is not needed anymore ;) > Update KafkaStreamer to fit new features introduced in Kafka 0.9 > ---------------------------------------------------------------- > > Key: IGNITE-2016 > URL: https://issues.apache.org/jira/browse/IGNITE-2016 > Project: Ignite > Issue Type: New Feature > Components: streaming > Reporter: Roman Shtykh > Assignee: Roman Shtykh > > Particularly, > - new consumer > - Kafka Connect (Copycat) > http://www.confluent.io/blog/apache-kafka-0.9-is-released > This can be a a different integration task or a complete re-write of the > current implementation, considering the fact that Kafka Connect is a new > standard way for "large-scale, real-time data import and export for Kafka." -- This message was sent by Atlassian JIRA (v6.3.4#6332)