Shard request cache settings
editShard request cache settings
editWhen a search request is run against an index or against many indices, each involved shard executes the search locally and returns its local results to the coordinating node, which combines these shard-level results into a “global” result set.
The shard-level request cache module caches the local results on each shard. This allows frequently used (and potentially heavy) search requests to return results almost instantly. The requests cache is a very good fit for the logging use case, where only the most recent index is being actively updated — results from older indices will be served directly from the cache.
By default, the requests cache will only cache the results of search requests
where size=0
, so it will not cache hits
,
but it will cache hits.total
, aggregations, and
suggestions.
Most queries that use now
(see Date Math) cannot be cached.
Scripted queries that use the API calls which are non-deterministic, such as
Math.random()
or new Date()
are not cached.
Cache invalidation
editThe cache is smart — it keeps the same near real-time promise as uncached search.
Cached results are invalidated automatically whenever the shard refreshes to pick up changes to the documents or when you update the mapping. In other words you will always get the same results from the cache as you would for an uncached search request.
The longer the refresh interval, the longer that cached entries will remain valid even if there are changes to the documents. If the cache is full, the least recently used cache keys will be evicted.
The cache can be expired manually with the clear-cache
API:
resp = client.indices.clear_cache( index=["my-index-000001", "my-index-000002"], request="true", ) print(resp)
response = client.indices.clear_cache( index: 'my-index-000001,my-index-000002', request: true ) puts response
POST /my-index-000001,my-index-000002/_cache/clear?request=true
Enabling and disabling caching
editThe cache is enabled by default, but can be disabled when creating a new index as follows:
resp = client.indices.create( index="my-index-000001", body={"settings": {"index.requests.cache.enable": False}}, ) print(resp)
response = client.indices.create( index: 'my-index-000001', body: { settings: { 'index.requests.cache.enable' => false } } ) puts response
PUT /my-index-000001 { "settings": { "index.requests.cache.enable": false } }
It can also be enabled or disabled dynamically on an existing index with the
update-settings
API:
resp = client.indices.put_settings( index="my-index-000001", body={"index.requests.cache.enable": True}, ) print(resp)
response = client.indices.put_settings( index: 'my-index-000001', body: { 'index.requests.cache.enable' => true } ) puts response
PUT /my-index-000001/_settings { "index.requests.cache.enable": true }
Enabling and disabling caching per request
editThe request_cache
query-string parameter can be used to enable or disable
caching on a per-request basis. If set, it overrides the index-level setting:
resp = client.search( index="my-index-000001", request_cache="true", body={ "size": 0, "aggs": {"popular_colors": {"terms": {"field": "colors"}}}, }, ) print(resp)
response = client.search( index: 'my-index-000001', request_cache: true, body: { size: 0, aggregations: { popular_colors: { terms: { field: 'colors' } } } } ) puts response
GET /my-index-000001/_search?request_cache=true { "size": 0, "aggs": { "popular_colors": { "terms": { "field": "colors" } } } }
Requests where size
is greater than 0 will not be cached even if the request cache is
enabled in the index settings. To cache these requests you will need to use the
query-string parameter detailed here.
Cache key
editA hash of the whole JSON body is used as the cache key. This means that if the JSON changes — for instance if keys are output in a different order — then the cache key will not be recognised.
Most JSON libraries support a canonical mode which ensures that JSON keys are always emitted in the same order. This canonical mode can be used in the application to ensure that a request is always serialized in the same way.
Cache settings
editThe cache is managed at the node level, and has a default maximum size of 1%
of the heap. This can be changed in the config/elasticsearch.yml
file with:
indices.requests.cache.size: 2%
Also, you can use the indices.requests.cache.expire
setting to specify a TTL
for cached results, but there should be no reason to do so. Remember that
stale results are automatically invalidated when the index is refreshed. This
setting is provided for completeness' sake only.
Monitoring cache usage
editThe size of the cache (in bytes) and the number of evictions can be viewed
by index, with the indices-stats
API:
resp = client.indices.stats( metric="request_cache", human=True, ) print(resp)
response = client.indices.stats( metric: 'request_cache', human: true ) puts response
GET /_stats/request_cache?human
or by node with the nodes-stats
API:
resp = client.nodes.stats( metric="indices", index_metric="request_cache", human=True, ) print(resp)
response = client.nodes.stats( metric: 'indices', index_metric: 'request_cache', human: true ) puts response
GET /_nodes/stats/indices/request_cache?human