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Thread Pool
editThread Pool
editA 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:
-
generic
-
For generic operations (e.g., background node discovery).
Thread pool type is
scaling
. -
index
-
For index/delete operations. Thread pool type is
fixed
with a size of# of available processors
, queue_size of200
. The maximum size for this pool is1 + # of available processors
. -
search
-
For count/search/suggest operations. Thread pool type is
fixed
with a size ofint((# of available_processors * 3) / 2) + 1
, queue_size of1000
. -
get
-
For get operations. Thread pool type is
fixed
with a size of# of available processors
, queue_size of1000
. -
bulk
-
For bulk operations. Thread pool type is
fixed
with a size of# of available processors
, queue_size of50
. The maximum size for this pool is1 + # of available processors
. -
snapshot
-
For snapshot/restore operations. Thread pool type is
scaling
with a keep-alive of5m
and a max ofmin(5, (# of available processors)/2)
. -
warmer
-
For segment warm-up operations. Thread pool type is
scaling
with a keep-alive of5m
and a max ofmin(5, (# of available processors)/2)
. -
refresh
-
For refresh operations. Thread pool type is
scaling
with a keep-alive of5m
and a max ofmin(10, (# of available processors)/2)
. -
listener
-
Mainly for java client executing of action when listener threaded is set to true.
Thread pool type is
scaling
with a default max ofmin(10, (# of available processors)/2)
.
Changing a specific thread pool can be done by setting its type-specific parameters; for example, changing the index
thread pool to have more threads:
thread_pool: index: size: 30
Thread pool types
editThe following are the types of thread pools and their respective parameters:
fixed
editThe 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.
thread_pool: index: size: 30 queue_size: 1000
scaling
editThe 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.
thread_pool: warmer: core: 1 max: 8 keep_alive: 2m
Processors setting
editThe 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: 2
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, setprocessors
to 8). Note that this is an expert-level use-case and there’s a lot more involved than just setting theprocessors
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 theulimit
appropriately, you can override this bound by explicitly setting theprocessors
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.