Index codecs determine how the index’s stored fields are compressed and stored on disk. The index codec is controlled by the static
index.codec setting that specifies the compression algorithm. The setting impacts the index shard size and index operation performance.
OpenSearch provides support for four codecs that can be used for compressing the stored fields. Each codec offers different tradeoffs between compression ratio (storage size) and indexing performance (speed):
default– This codec employs the LZ4 algorithm with a preset dictionary, which prioritizes performance over compression ratio. It offers faster indexing and search operations when compared with
best_compressionbut may result in larger index/shard sizes. If no codec is provided in the index settings, then LZ4 is used as the default algorithm for compression.
best_compression– This codec uses zlib as an underlying algorithm for compression. It achieves high compression ratios that result in smaller index sizes. However, this may incur additional CPU usage during index operations and may subsequently result in high indexing and search latencies.
As of OpenSearch 2.9, two new codecs based on the Zstandard compression algorithm are available. This algorithm provides a good balance between compression ratio and speed.
It may be challenging to change the codec setting of an existing index (see Changing an index codec), so it is important to test a representative workload in a non-production environment before using a new codec setting.
zstd(OpenSearch 2.9 and later) – This codec provides significant compression comparable to the
best_compressioncodec with reasonable CPU usage and improved indexing and search performance compared to the
zstd_no_dict(OpenSearch 2.9 and later) – This codec is similar to
zstdbut excludes the dictionary compression feature. It provides faster indexing and search operations compared to
zstdat the expense of a slightly larger index size.
zstd_no_dict codecs, you can optionally specify a compression level in the
index.codec.compression_level setting. This setting takes integers in the [1, 6] range. A higher compression level results in a higher compression ratio (smaller storage size) with a tradeoff in speed (slower compression and decompression speeds lead to greater indexing and search latencies).
When an index segment is created, it uses the current index codec for compression. If you update the index codec, any segment created after the update will use the new compression algorithm. For specific operation considerations, see Index codec considerations for index operations.
Choosing a codec
The choice of index codec impacts the amount of disk space required to store the index data. Codecs like
zstd_no_dict can achieve higher compression ratios, resulting in smaller index sizes. Conversely, the
default codec doesn’t prioritize compression ratio, resulting in larger index sizes but faster search operations than
Index codec considerations for index operations
The following index codec considerations apply to various index operations.
Every index consists of shards, each of which is further divided into Lucene segments. During index writes, the new segments are created based on the codec specified in the index settings. If you update the codec for an index, the new segments will use the new codec algorithm.
During segment merges, OpenSearch combines smaller index segments into larger segments in order to provide optimal resource utilization and improve performance. The index codec setting influences the speed and efficiency of the merge operations. The number of merges that happen on an index is a factor of the segment size, and a smaller segment size directly translates into smaller merge sizes. If you update the
index.codec setting, the new merge operations will use the new codec when creating merged segments. The merged segments will have the compression characteristics of the new codec.
Splits and shrinks
The Split API splits an original index into a new index where each original primary shard is divided into two or more primary shards. The Shrink API shrinks an existing index to a new index with a smaller number of primary shards. As part of split or shrink operations, any newly created segments will use the latest codec settings.
When creating a snapshot, the index codec setting influences the size of the snapshot and the time required for its creation. If the codec of an index is updated, newly created snapshots will use the latest codec setting. The resulting snapshot size will reflect the compression characteristics of the latest codec setting. Existing segments included in the snapshot will retain their original compression characteristics.
When you restore the indexes from a snapshot of a cluster to another cluster, it is important to verify that the target cluster supports the codecs of the segments in the source snapshot. For example, if the source snapshot contains segments of the
zstd_no_dict codecs (introduced in OpenSearch 2.9), you won’t be able to restore the snapshot to a cluster that runs on an older OpenSearch version because it doesn’t support these codecs.
When you are performing a reindex operation from a source index, the new segments created in the target index will have the properties of the codec settings of the target index.
Index rollups and transforms
When an index rollup or transform job is completed, the segments created in the target index will have the properties of the index codec specified during target index creation, irrespective of the source index codec. If the target index is created dynamically through a rollup job, the default codec is used for segments of the target index.
Changing an index codec
It is not possible to change the codec setting of an open index. You can close the index, apply the new index codec setting, and reopen the index, at which point only new segments will be written with the new codec. This requires stopping all reads and writes to the index for a brief period to make the codec change and may result in inconsistent segment sizes and compression ratios. Alternatively, you can reindex all data from a source index into a new index with a different codec setting, though this is a very resource-intensive operation.
Performance tuning and benchmarking
Depending on your specific use case, you might need to experiment with different index codec settings to fine-tune the performance of your OpenSearch cluster. Conducting benchmark tests with different codecs and measuring the impact on indexing speed, search performance, and resource utilization can help you identify the optimal index codec setting for your workload. With the
zstd_no_dict codecs, you can also fine-tune the compression level in order to identify the optimal configuration for your cluster.
The following table provides a performance comparison of the
zstd_no_dict codecs against the
default codec. The tests were performed with the
nyc_taxi dataset. The results are listed in terms of percent change, and bold results indicate performance improvement.