- Elasticsearch Guide: other versions:
- Getting Started
- Setup Elasticsearch
- Breaking changes
- Breaking changes in 5.0
- Search and Query DSL changes
- Mapping changes
- Percolator changes
- Suggester changes
- Index APIs changes
- Document API changes
- Settings changes
- Allocation changes
- HTTP changes
- REST API changes
- CAT API changes
- Java API changes
- Packaging
- Plugin changes
- Filesystem related changes
- Path to data on disk
- Aggregation changes
- Script related changes
- Breaking changes in 5.0
- API Conventions
- Document APIs
- Search APIs
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Cardinality Aggregation
- Extended Stats Aggregation
- Geo Bounds Aggregation
- Geo Centroid Aggregation
- Max Aggregation
- Min Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- Stats Aggregation
- Sum Aggregation
- Top hits Aggregation
- Value Count Aggregation
- Bucket Aggregations
- Children Aggregation
- Date Histogram Aggregation
- Date Range Aggregation
- Diversified Sampler Aggregation
- Filter Aggregation
- Filters Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- Global Aggregation
- Histogram Aggregation
- IP Range Aggregation
- Missing Aggregation
- Nested Aggregation
- Range Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
- Derivative Aggregation
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation
- Percentiles Bucket Aggregation
- Moving Average Aggregation
- Cumulative Sum Aggregation
- Bucket Script Aggregation
- Bucket Selector Aggregation
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Metrics Aggregations
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Shadow replica indices
- Indices Stats
- Indices Segments
- Indices Recovery
- Indices Shard Stores
- Clear Cache
- Flush
- Refresh
- Force Merge
- cat APIs
- Cluster APIs
- Query DSL
- Mapping
- Analysis
- Anatomy of an analyzer
- Testing analyzers
- Analyzers
- Tokenizers
- Token Filters
- Standard Token Filter
- ASCII Folding Token Filter
- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
- Shingle Token Filter
- Stop Token Filter
- Word Delimiter Token Filter
- Stemmer Token Filter
- Stemmer Override Token Filter
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Snowball Token Filter
- Phonetic Token Filter
- Synonym Token Filter
- Compound Word Token Filter
- Reverse Token Filter
- Elision Token Filter
- Truncate Token Filter
- Unique Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Trim Token Filter
- Limit Token Count Token Filter
- Hunspell Token Filter
- Common Grams Token Filter
- Normalization Token Filter
- CJK Width Token Filter
- CJK Bigram Token Filter
- Delimited Payload Token Filter
- Keep Words Token Filter
- Keep Types Token Filter
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Character Filters
- Modules
- Index Modules
- Ingest Node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- Lowercase Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- Dot Expander Processor
- How To
- Testing
- Glossary of terms
- Release Notes
- 5.0.2 Release Notes
- 5.0.1 Release Notes
- 5.0.0 Combined Release Notes
- 5.0.0 GA Release Notes
- 5.0.0-rc1 Release Notes
- 5.0.0-beta1 Release Notes
- 5.0.0-alpha5 Release Notes
- 5.0.0-alpha4 Release Notes
- 5.0.0-alpha3 Release Notes
- 5.0.0-alpha2 Release Notes
- 5.0.0-alpha1 Release Notes
- 5.0.0-alpha1 Release Notes (Changes previously released in 2.x)
WARNING: Version 5.0 of Elasticsearch has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
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.
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