- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 7.10
- Getting started with Elasticsearch
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- Setting JVM options
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
- Field data cache settings
- HTTP
- Index lifecycle management settings
- Index management settings
- Index recovery settings
- Indexing buffer settings
- License settings
- Local gateway settings
- Logging
- Machine learning settings
- Monitoring settings
- Node
- Network settings
- Node query cache settings
- Search settings
- Security settings
- Shard request cache settings
- Snapshot lifecycle management settings
- Transforms settings
- Transport
- Thread pools
- Watcher settings
- Important Elasticsearch configuration
- Important System Configuration
- Bootstrap Checks
- Heap size check
- File descriptor check
- Memory lock check
- Maximum number of threads check
- Max file size check
- Maximum size virtual memory check
- Maximum map count check
- Client JVM check
- Use serial collector check
- System call filter check
- OnError and OnOutOfMemoryError checks
- Early-access check
- G1GC check
- All permission check
- Discovery configuration check
- Bootstrap Checks for X-Pack
- Starting Elasticsearch
- Stopping Elasticsearch
- Discovery and cluster formation
- Add and remove nodes in your cluster
- Full-cluster restart and rolling restart
- Remote clusters
- Set up X-Pack
- Configuring X-Pack Java Clients
- Plugins
- Upgrade Elasticsearch
- Index modules
- Mapping
- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
- Tokenizer reference
- Token filter reference
- Apostrophe
- ASCII folding
- CJK bigram
- CJK width
- Classic
- Common grams
- Conditional
- Decimal digit
- Delimited payload
- Dictionary decompounder
- Edge n-gram
- Elision
- Fingerprint
- Flatten graph
- Hunspell
- Hyphenation decompounder
- Keep types
- Keep words
- Keyword marker
- Keyword repeat
- KStem
- Length
- Limit token count
- Lowercase
- MinHash
- Multiplexer
- N-gram
- Normalization
- Pattern capture
- Pattern replace
- Phonetic
- Porter stem
- Predicate script
- Remove duplicates
- Reverse
- Shingle
- Snowball
- Stemmer
- Stemmer override
- Stop
- Synonym
- Synonym graph
- Trim
- Truncate
- Unique
- Uppercase
- Word delimiter
- Word delimiter graph
- Character filters reference
- Normalizers
- Index templates
- Data streams
- Ingest node
- Search your data
- Query DSL
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Children
- Composite
- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Geo-distance
- Geohash grid
- Geotile grid
- Global
- Histogram
- IP range
- Missing
- Nested
- Parent
- Range
- Rare terms
- Reverse nested
- Sampler
- Significant terms
- Significant text
- Terms
- Variable width histogram
- Subtleties of bucketing range fields
- Metrics aggregations
- Pipeline aggregations
- Bucket aggregations
- EQL
- SQL access
- Overview
- Getting Started with SQL
- Conventions and Terminology
- Security
- SQL REST API
- SQL Translate API
- SQL CLI
- SQL JDBC
- SQL ODBC
- SQL Client Applications
- SQL Language
- Functions and Operators
- Comparison Operators
- Logical Operators
- Math Operators
- Cast Operators
- LIKE and RLIKE Operators
- Aggregate Functions
- Grouping Functions
- Date/Time and Interval Functions and Operators
- Full-Text Search Functions
- Mathematical Functions
- String Functions
- Type Conversion Functions
- Geo Functions
- Conditional Functions And Expressions
- System Functions
- Reserved keywords
- SQL Limitations
- Scripting
- Data management
- ILM: Manage the index lifecycle
- Overview
- Concepts
- Automate rollover
- Manage Filebeat time-based indices
- Index lifecycle actions
- Configure a lifecycle policy
- Migrate index allocation filters to node roles
- Resolve lifecycle policy execution errors
- Start and stop index lifecycle management
- Manage existing indices
- Skip rollover
- Restore a managed data stream or index
- Monitor a cluster
- Frozen indices
- Roll up or transform your data
- Set up a cluster for high availability
- Snapshot and restore
- Secure a cluster
- Overview
- Configuring security
- User authentication
- Built-in users
- Internal users
- Token-based authentication services
- Realms
- Realm chains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- Kerberos authentication
- Integrating with other authentication systems
- Enabling anonymous access
- Controlling the user cache
- Configuring SAML single-sign-on on the Elastic Stack
- Configuring single sign-on to the Elastic Stack using OpenID Connect
- User authorization
- Built-in roles
- Defining roles
- Granting access to Stack Management features
- Security privileges
- Document level security
- Field level security
- Granting privileges for data streams and index aliases
- Mapping users and groups to roles
- Setting up field and document level security
- Submitting requests on behalf of other users
- Configuring authorization delegation
- Customizing roles and authorization
- Enabling audit logging
- Encrypting communications
- Restricting connections with IP filtering
- Cross cluster search, clients, and integrations
- Tutorial: Getting started with security
- Tutorial: Encrypting communications
- Troubleshooting
- Some settings are not returned via the nodes settings API
- Authorization exceptions
- Users command fails due to extra arguments
- Users are frequently locked out of Active Directory
- Certificate verification fails for curl on Mac
- SSLHandshakeException causes connections to fail
- Common SSL/TLS exceptions
- Common Kerberos exceptions
- Common SAML issues
- Internal Server Error in Kibana
- Setup-passwords command fails due to connection failure
- Failures due to relocation of the configuration files
- Limitations
- Watch for cluster and index events
- Command line tools
- How To
- Glossary of terms
- REST APIs
- API conventions
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- cat count
- cat data frame analytics
- cat datafeeds
- cat fielddata
- cat health
- cat indices
- cat master
- cat nodeattrs
- cat nodes
- cat pending tasks
- cat plugins
- cat recovery
- cat repositories
- cat segments
- cat shards
- cat snapshots
- cat task management
- cat templates
- cat thread pool
- cat trained model
- cat transforms
- Cluster APIs
- Cluster allocation explain
- Cluster get settings
- Cluster health
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Nodes reload secure settings
- Nodes stats
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Cross-cluster replication APIs
- Data stream APIs
- Document APIs
- Enrich APIs
- Graph explore API
- Index APIs
- Add index alias
- Analyze
- Clear cache
- Clone index
- Close index
- Create index
- Delete index
- Delete index alias
- Delete component template
- Delete index template
- Delete index template (legacy)
- Flush
- Force merge
- Freeze index
- Get component template
- Get field mapping
- Get index
- Get index alias
- Get index settings
- Get index template
- Get index template (legacy)
- Get mapping
- Index alias exists
- Index exists
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists (legacy)
- Open index
- Put index template
- Put index template (legacy)
- Put component template
- Put mapping
- Refresh
- Rollover index
- Shrink index
- Simulate index
- Simulate template
- Split index
- Synced flush
- Type exists
- Unfreeze index
- Update index alias
- Update index settings
- Resolve index
- List dangling indices
- Import dangling index
- Delete dangling index
- Index lifecycle management APIs
- Ingest APIs
- Info API
- Licensing APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create jobs
- Create calendars
- Create datafeeds
- Create filters
- Delete calendars
- Delete datafeeds
- Delete events from calendar
- Delete filters
- Delete forecasts
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Delete expired data
- Estimate model memory
- Find file structure
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get machine learning info
- Get model snapshots
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Revert model snapshots
- Set upgrade mode
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
- Update jobs
- Update model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Create trained models
- Update data frame analytics jobs
- Delete data frame analytics jobs
- Delete trained models
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Get trained models
- Get trained models stats
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Migration APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Search APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Clear privileges cache
- Clear API key cache
- Create API keys
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Create or update users
- Delegate PKI authentication
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete users
- Disable users
- Enable users
- Get API key information
- Get application privileges
- Get builtin privileges
- Get role mappings
- Get roles
- Get token
- Get users
- Grant API keys
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect prepare authentication
- OpenID Connect authenticate
- OpenID Connect logout
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SSL certificate
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- Elasticsearch version 7.10.2
- Elasticsearch version 7.10.1
- Elasticsearch version 7.10.0
- Elasticsearch version 7.9.3
- Elasticsearch version 7.9.2
- Elasticsearch version 7.9.1
- Elasticsearch version 7.9.0
- Elasticsearch version 7.8.1
- Elasticsearch version 7.8.0
- Elasticsearch version 7.7.1
- Elasticsearch version 7.7.0
- Elasticsearch version 7.6.2
- Elasticsearch version 7.6.1
- Elasticsearch version 7.6.0
- Elasticsearch version 7.5.2
- Elasticsearch version 7.5.1
- Elasticsearch version 7.5.0
- Elasticsearch version 7.4.2
- Elasticsearch version 7.4.1
- Elasticsearch version 7.4.0
- Elasticsearch version 7.3.2
- Elasticsearch version 7.3.1
- Elasticsearch version 7.3.0
- Elasticsearch version 7.2.1
- Elasticsearch version 7.2.0
- Elasticsearch version 7.1.1
- Elasticsearch version 7.1.0
- Elasticsearch version 7.0.0
- Elasticsearch version 7.0.0-rc2
- Elasticsearch version 7.0.0-rc1
- Elasticsearch version 7.0.0-beta1
- Elasticsearch version 7.0.0-alpha2
- Elasticsearch version 7.0.0-alpha1
- Dependencies and versions
Thread pools
editThread pools
editA 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/suggest operations. Thread pool type is
fixed_auto_queue_size
with a size ofint((
# of allocated 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 allocated 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 allocated processors
, queue_size of10000
. The maximum size for this pool is1 +
# of allocated processors
. -
snapshot
-
For snapshot/restore operations. Thread pool type is
scaling
with a keep-alive of5m
and a max ofmin(5, (
# of allocated processors
) / 2)
. -
warmer
-
For segment warm-up operations. Thread pool type is
scaling
with a keep-alive of5m
and a max ofmin(5, (
# of allocated processors
) / 2)
. -
refresh
-
For refresh operations. Thread pool type is
scaling
with a keep-alive of5m
and a max ofmin(10, (
# of allocated 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 allocated 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 allocated processors
. -
fetch_shard_store
-
For listing shard stores.
Thread pool type is
scaling
with keep-alive of5m
and a default maximum size of2 *
# of allocated 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 allocated 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
. -
system_read
-
For read operations on system indices.
Thread pool type is
fixed
and a default maximum size ofmin(5, (
# of allocated processors
) / 2)
. -
system_write
-
For write operations on system indices.
Thread pool type is
fixed
and a default maximum size ofmin(5, (
# of allocated processors
) / 2)
.
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.
deprecated[7.7.0,The experimental fixed_auto_queue_size
thread pool type is
deprecated and will be removed in 8.0.]
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
Allocated 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
node.processors
setting.
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 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, setnode.processors
to 8. Note that this is an expert-level use case and there’s a lot more involved than just setting thenode.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.