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Thread Pool

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Thread Pool

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A node holds several thread pools in order to improve how threads memory consumption are managed within a node. Many of these pools also have queues associated with them, which allow pending requests to be held instead of discarded.

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

`index`	For index/delete operations. Defaults to `fixed` with a size of `# of available processors`, queue_size of `200`.
`search`	For count/search operations. Defaults to `fixed` with a size of `int((# of available_processors * 3) / 2) + 1`, queue_size of `1000`.
`suggest`	For suggest operations. Defaults to `fixed` with a size of `# of available processors`, queue_size of `1000`.
`get`	For get operations. Defaults to `fixed` with a size of `# of available processors`, queue_size of `1000`.
`bulk`	For bulk operations. Defaults to `fixed` with a size of `# of available processors`, queue_size of `50`.
`percolate`	For percolate operations. Defaults to `fixed` with a size of `# of available processors`, queue_size of `1000`.
`snapshot`	For snapshot/restore operations. Defaults to `scaling`, keep-alive `5m` with a size of `(# of available processors)/2`.
`warmer`	For segment warm-up operations. Defaults to `scaling` with a `5m` keep-alive.
`refresh`	For refresh operations. Defaults to `scaling` with a `5m` keep-alive.
`listener`	Mainly for java client executing of action when listener threaded is set to true. Default size of `(# of available processors)/2`, max at 10.

Changing a specific thread pool can be done by setting its type and specific type parameters, for example, changing the index thread pool to have more threads:

threadpool:
    index:
        type: fixed
        size: 30

you can update threadpool settings live using Cluster Update Settings.

Thread pool types

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The following are the types of thread pools that can be used and their respective parameters:

`cache`

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The cache thread pool is an unbounded thread pool that will spawn a thread if there are pending requests. Here is an example of how to set it:

threadpool:
    index:
        type: cached

`fixed`

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The fixed thread pool holds a fixed size of threads to handle the requests with a queue (optionally bounded) for pending requests that have no threads to service them.

The size parameter controls the number of threads, and defaults to the number of cores times 5.

The queue_size allows to control the size of the queue of pending requests that have no threads to execute them. By default, it is set to -1 which means its unbounded. When a request comes in and the queue is full, it will abort the request.

threadpool:
    index:
        type: fixed
        size: 30
        queue_size: 1000

Processors setting

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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 processors setting.

processors: 4

There are a few use-cases for explicitly overriding the 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 processors setting to the desired fraction (e.g., if you’re running two instances of Elasticsearch on a 16-core machine, set processors to 8). Note that this is an expert-level use-case and there’s a lot more involved than just setting the processors setting as there are other considerations like changing the number of garbage collector threads, pinning processes to cores, etc.
The number of processors is by default bounded to 32. This means that on systems that have more than 32 processors, Elasticsearch will size its thread pools as if there are only 32 processors present. This limitation was added to avoid creating too many threads on systems that have not properly adjusted the ulimit for max number of processes. In cases where you’ve adjusted the ulimit appropriately, you can override this bound by explicitly setting the processors setting.
Sometimes the number of processors is wrongly detected and in such cases explicitly setting the processors setting will workaround such issues.

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

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