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 (for example, background node discovery).
Thread pool type is
scaling
. -
search
-
For count/search/suggest operations. Thread pool type is
fixed_auto_queue_size
with a size ofint((# of available_processors * 3) / 2) + 1
, and initial queue_size of1000
. -
search_throttled
-
For count/search/suggest/get operations on
search_throttled indices
. Thread pool type isfixed_auto_queue_size
with a size of1
, and initial queue_size of100
. -
get
-
For get operations. Thread pool type is
fixed
with a size of# of available processors
, queue_size of1000
. -
analyze
-
For analyze requests. Thread pool type is
fixed
with a size of1
, queue size of16
. -
write
-
For single-document index/delete/update and bulk requests. 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
. -
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 isscaling
with a default max ofmin(10, (# of available processors)/2)
. -
fetch_shard_started
-
For listing shard states.
Thread pool type is
scaling
with keep-alive of5m
and a default maximum size of2 * # of available processors
. -
fetch_shard_store
-
For listing shard stores.
Thread pool type is
scaling
with keep-alive of5m
and a default maximum size of2 * # of available processors
. -
flush
-
For flush, synced flush, and translog
fsync
operations. Thread pool type isscaling
with a keep-alive of5m
and a default maximum size ofmin(5, (# of available processors)/2)
. -
force_merge
-
For force merge operations.
Thread pool type is
fixed
with a size of 1 and an unbounded queue size. -
management
-
For cluster management.
Thread pool type is
scaling
with a keep-alive of5m
and a default maximum size of5
.
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
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.
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: write: size: 30 queue_size: 1000
fixed_auto_queue_size
editThis functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
The fixed_auto_queue_size
thread pool holds a fixed size of threads to handle
the requests with a bounded queue for pending requests that have no threads to
service them. It’s similar to the fixed
threadpool, however, the queue_size
automatically adjusts according to calculations based on
Little’s Law. These calculations
will potentially adjust the queue_size
up or down by 50 every time
auto_queue_frame_size
operations have been completed.
The size
parameter controls the number of threads.
The queue_size
allows to control the initial size of the queue of pending
requests that have no threads to execute them.
The min_queue_size
setting controls the minimum amount the queue_size
can be
adjusted to.
The max_queue_size
setting controls the maximum amount the queue_size
can be
adjusted to.
The auto_queue_frame_size
setting controls the number of operations during
which measurement is taken before the queue is adjusted. It should be large
enough that a single operation cannot unduly bias the calculation.
The target_response_time
is a time value setting that indicates the targeted
average response time for tasks in the thread pool queue. If tasks are routinely
above this time, the thread pool queue will be adjusted down so that tasks are
rejected.
thread_pool: search: size: 30 queue_size: 500 min_queue_size: 10 max_queue_size: 1000 auto_queue_frame_size: 2000 target_response_time: 1s
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, for example, 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, and so on. -
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.