Hi all, I have a pipeline that is currently reading from Kafka and writing to Elasticsearch. I recently was doing some testing for how it handles failures and was wondering if there’s a best practice or recommendation for doing so. Specifically, if I have a batch of 100 records being sent via a BulkProcessor call (internally from the sink), and a single record in the batch is bad (for whatever reason), how I might handle this.
Ideally, I’d be able to only retry the message(s) in the batch that failed, but that may require access to the BulkProcessor instance directly (if possible at all). I don’t see a way to easily discern or govern how reindexing should be handled within the onFailure handler, or if I would need access to the afterBulk handler on the processor specifically. Just trying to leverage the batching without making a potentially large additional bulk request to Elastic due to one bad record in a batch. Any recommendations on how I might handle this? It doesn’t seem like disabling batching (I.e. send one record at at time) is anywhere near performance enough and fails under large volumes. Rion (dev+user for reach)
