1234567891011121314151617181920212223242526272829303132333435363738 |
- [[index-rollover]]
- === Rollover
- When indexing time-series data like logs or metrics, you can't write to a single index indefinitely.
- To meet your indexing and search performance requirements and manage resource usage,
- you write to an index until some threshold is met and
- then create a new index and start writing to it instead.
- Using rolling indices enables you to:
- * Optimize the active index for high ingest rates on high-performance _hot_ nodes.
- * Optimize for search performance on _warm_ nodes.
- * Shift older, less frequently accessed data to less expensive _cold_ nodes,
- * Delete data according to your retention policies by removing entire indices.
- Rollover relies on three things:
- * An _index template_ that specifies the settings for each new index in the series.
- You optimize this configuration for ingestion, typically using as many shards as you have hot nodes.
- * An _index alias_ that references the entire set of indices.
- * A single index designated as the _write index_.
- This is the active index that handles all write requests.
- On each rollover, the new index becomes the write index.
- [discrete]
- [role="xpack"]
- [testenv="basic"]
- [[ilm-automatic-rollover]]
- === Automatic rollover
- {ilm-init} enables you to automatically roll over to a new index based
- on the index size, document count, or age. When a rollover is triggered, a new
- index is created, the write alias is updated to point to the new index, and all
- subsequent updates are written to the new index.
- TIP: Rolling over to a new index based on size, document count, or age is preferable
- to time-based rollovers. Rolling over at an arbitrary time often results in
- many small indices, which can have a negative impact on performance and
- resource usage.
|