Thread pool settings

Self Managed

A node uses several thread pools to manage memory consumption. Queues associated with many of the thread pools enable pending requests to be held instead of discarded.

There are several thread pools, but the important ones include:

generic: For generic operations (for example, background node discovery). Thread pool type is scaling.

search: For count/search operations at the shard level. Used also by fetch and other search related operations Thread pool type is fixed with a size of int((# of allocated processors * 3) / 2) + 1, and queue_size of 1000.
search_throttled: For count/search/suggest/get operations on search_throttled indices. Thread pool type is fixed with a size of 1, and queue_size of 100.
search_coordination: For lightweight search-related coordination operations. Thread pool type is fixed with a size of (# of allocated processors) / 2, and queue_size of 1000.
get: For get operations. Thread pool type is fixed with a size of int((# of allocated processors * 3) / 2) + 1, and queue_size of 1000.
analyze: For analyze requests. Thread pool type is fixed with a size of 1, queue size of 16.
write: For single-document index/delete/update, ingest processors, and bulk requests. Thread pool type is fixed with a size of # of allocated processors, queue_size of 10000. The maximum size for this pool is 1 + # of allocated processors.
snapshot: For snapshot/restore operations. Thread pool type is scaling with a keep-alive of 5m. On nodes with at least 750MB of heap the maximum size of this pool is 10 by default. On nodes with less than 750MB of heap the maximum size of this pool is min(5, (# of allocated processors) / 2) by default.
snapshot_meta: For snapshot repository metadata read operations. Thread pool type is scaling with a keep-alive of 5m and a max of min(50, (# of allocated processors* 3)).
warmer: For segment warm-up operations. Thread pool type is scaling with a keep-alive of 5m and a max of min(5, (# of allocated processors) / 2).
refresh: For refresh operations. Thread pool type is scaling with a keep-alive of 5m and a max of min(10, (# of allocated processors) / 2).
fetch_shard_started: For listing shard states. Thread pool type is scaling with keep-alive of 5m and a default maximum size of 2 * # of allocated processors.
fetch_shard_store: For listing shard stores. Thread pool type is scaling with keep-alive of 5m and a default maximum size of 2 * # of allocated processors.
flush: For flush and translog fsync operations. Thread pool type is scaling with a keep-alive of 5m and a default maximum size of min(5, (# of allocated processors) / 2).
force_merge: For force merge operations. Thread pool type is fixed with a size of max(1, (# of allocated processors) / 8) and an unbounded queue size.
management: For cluster management. Thread pool type is scaling with a keep-alive of 5m and a default maximum size of 5.
system_read: For read operations on system indices. Thread pool type is fixed with a default maximum size of min(5, (# of allocated processors) / 2).
system_write: For write operations on system indices. Thread pool type is fixed with a default maximum size of min(5, (# of allocated processors) / 2).
system_critical_read: For critical read operations on system indices. Thread pool type is fixed with a default maximum size of min(5, (# of allocated processors) / 2).
system_critical_write: For critical write operations on system indices. Thread pool type is fixed with a default maximum size of min(5, (# of allocated processors) / 2).
watcher: For watch executions. Thread pool type is fixed with a default maximum size of min(5 * (# of allocated processors), 50) and queue_size of 1000.
esql_worker: Executes ES|QL operations. Thread pool type is fixed with a size of int((# of allocated processors * 3) / 2) + 1, and queue_size of 1000.

Thread pool settings are static and can be changed by editing elasticsearch.yml. Changing a specific thread pool can be done by setting its type-specific parameters; for example, changing the number of threads in the write thread pool:

		thread_pool:
    write:
        size: 30

	

Thread pool types

The following are the types of thread pools and their respective parameters:

`fixed`

A fixed thread pool holds a fixed number of threads as determined by the size parameter. If a task is submitted to a fixed thread pool and there are fewer than size busy threads in the pool then the task will execute immediately. If all the threads are busy when a task is submitted then it will be held in a queue for later execution. The queue_size parameter controls the maximum size of this queue. A queue_size of -1 means that the queue is unbounded, but most fixed thread pools specify a bound on their queue size by default. If a bounded queue is full then it will reject further work, which typically causes the corresponding requests to fail.

		thread_pool:
    write:
        size: 30
        queue_size: 1000

	

`scaling`

The scaling thread pool holds a dynamic number of threads. This number is proportional to the workload and varies between the value of the core and max parameters.

The keep_alive parameter determines how long a thread should be kept around in the thread pool without it doing any work.

If a task is submitted to a scaling thread pool when its maximum number of threads are already busy with other tasks, the new task will be held in a queue for later execution. The queue in a scaling thread pool is always unbounded.

		thread_pool:
    warmer:
        core: 1
        max: 8
        keep_alive: 2m

	

Allocated processors setting

The number of processors is automatically detected, and the thread pool settings are automatically set based on it. In some cases it can be useful to override the number of detected processors. This can be done by explicitly setting the node.processors setting. This setting is bounded by the number of available processors and accepts floating point numbers, which can be useful in environments where the Elasticsearch nodes are configured to run with CPU limits, such as cpu shares or quota under Cgroups.

node.processors: 2

There are a few use-cases for explicitly overriding the node.processors setting:

If you are running multiple instances of Elasticsearch on the same host but want Elasticsearch to size its thread pools as if it only has a fraction of the CPU, you should override the node.processors setting to the desired fraction, for example, if you’re running two instances of Elasticsearch on a 16-core machine, set node.processors to 8. Note that this is an expert-level use case and there’s a lot more involved than just setting the node.processors setting as there are other considerations like changing the number of garbage collector threads, pinning processes to cores, and so on.
Sometimes the number of processors is wrongly detected and in such cases explicitly setting the node.processors setting will workaround such issues.

In order to check the number of processors detected, use the nodes info API with the os flag.