Performance Considerations for Elasticsearch 2.0 Indexing
Blog post from Elastic
Elasticsearch 2.0 introduced a series of improvements aimed at enhancing indexing performance and resilience. One of the significant changes is the introduction of adaptive merge IO throttling, which automatically adjusts the IO rate based on the workload, eliminating the need for manual throttling adjustments. The update also modifies how data is distributed across multiple IO devices by allocating entire shards to specific paths, improving resilience to device failures. The removal of the Auto-ID optimization, previously used for indexing without user-defined IDs, is offset by improvements in ID lookup performance and the adoption of Flake IDs, enhancing reliability and performance. Additional enhancements include enabling doc values by default, improved data compression techniques, and shifts in API functionality to enhance safety and reduce heap usage during merges. These updates collectively aim to optimize Elasticsearch's indexing capabilities and overall system performance.
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