- Elasticsearch Guide: other versions:
- Elasticsearch introduction
- Getting started with Elasticsearch
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- 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
- Starting Elasticsearch
- Stopping Elasticsearch
- Adding nodes to your cluster
- Full-cluster restart and rolling restart
- Set up X-Pack
- Configuring X-Pack Java Clients
- Bootstrap Checks for X-Pack
- Upgrade Elasticsearch
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Weighted 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
- Median Absolute Deviation Aggregation
- Bucket Aggregations
- Adjacency Matrix Aggregation
- Auto-interval Date Histogram Aggregation
- Children Aggregation
- Composite Aggregation
- Date histogram aggregation
- Date Range Aggregation
- Diversified Sampler Aggregation
- Filter Aggregation
- Filters Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- GeoTile Grid Aggregation
- Global Aggregation
- Histogram Aggregation
- IP Range Aggregation
- Missing Aggregation
- Nested Aggregation
- Parent Aggregation
- Range Aggregation
- Rare Terms Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Subtleties of bucketing range fields
- 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
- Moving Function Aggregation
- Cumulative Sum Aggregation
- Cumulative Cardinality Aggregation
- Bucket Script Aggregation
- Bucket Selector Aggregation
- Bucket Sort Aggregation
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Metrics Aggregations
- Query DSL
- Search across clusters
- Scripting
- Mapping
- Analysis
- Anatomy of an analyzer
- Testing analyzers
- Analyzers
- Normalizers
- Tokenizers
- Char Group Tokenizer
- Classic Tokenizer
- Edge n-gram tokenizer
- Keyword Tokenizer
- Letter Tokenizer
- Lowercase Tokenizer
- N-gram tokenizer
- Path Hierarchy Tokenizer
- Path Hierarchy Tokenizer Examples
- Pattern Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
- Standard Tokenizer
- Thai Tokenizer
- UAX URL Email Tokenizer
- Whitespace Tokenizer
- Token Filters
- Apostrophe
- ASCII folding
- CJK bigram
- CJK width
- Classic
- Common grams
- Conditional
- Decimal digit
- Delimited payload
- Dictionary decompounder
- Edge n-gram
- Elision
- Fingerprint
- Flatten Graph Token Filter
- Hunspell Token Filter
- Hyphenation decompounder
- Keep types
- Keep words
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Length Token Filter
- Limit Token Count Token Filter
- Lowercase Token Filter
- MinHash Token Filter
- Multiplexer Token Filter
- N-gram
- Normalization Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Phonetic Token Filter
- Porter Stem Token Filter
- Predicate Token Filter Script
- Remove Duplicates Token Filter
- Reverse Token Filter
- Shingle Token Filter
- Snowball Token Filter
- Stemmer Token Filter
- Stemmer Override Token Filter
- Stop Token Filter
- Synonym Token Filter
- Synonym Graph Token Filter
- Trim Token Filter
- Truncate Token Filter
- Unique Token Filter
- Uppercase Token Filter
- Word Delimiter Token Filter
- Word Delimiter Graph Token Filter
- Character Filters
- Modules
- Index modules
- Ingest node
- Pipeline Definition
- Accessing Data in Pipelines
- Conditional Execution in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Bytes Processor
- Circle Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Dissect Processor
- Dot Expander Processor
- Drop Processor
- Fail Processor
- Foreach Processor
- GeoIP Processor
- Grok Processor
- Gsub Processor
- HTML Strip Processor
- Join Processor
- JSON Processor
- KV Processor
- Lowercase Processor
- Pipeline Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Set Security User Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- URL Decode Processor
- User Agent processor
- Managing the index lifecycle
- Getting started with index lifecycle management
- Policy phases and actions
- Set up index lifecycle management policy
- Using policies to manage index rollover
- Update policy
- Index lifecycle error handling
- Restoring snapshots of managed indices
- Start and stop index lifecycle management
- Using ILM with existing indices
- Getting started with snapshot lifecycle management
- 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
- Monitor a cluster
- Frozen indices
- Roll up or transform your data
- Set up a cluster for high availability
- 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
- Security privileges
- Document level security
- Field level security
- Granting privileges for indices and 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
- Alerting on cluster and index events
- Command line tools
- How To
- Testing
- Glossary of terms
- REST APIs
- API conventions
- cat APIs
- Cluster APIs
- Cross-cluster replication APIs
- Document APIs
- Explore API
- Index APIs
- Add index alias
- Analyze
- Clear cache
- Clone index
- Close index
- Create index
- Delete index
- Delete index alias
- Delete index template
- Flush
- Force merge
- Freeze index
- Get field mapping
- Get index
- Get index alias
- Get index settings
- Get index template
- Get mapping
- Index alias exists
- Index exists
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists
- Open index
- Put index template
- Put mapping
- Refresh
- Rollover index
- Shrink index
- Split index
- Synced flush
- Type exists
- Unfreeze index
- Update index alias
- Update index settings
- Index lifecycle management API
- Ingest APIs
- Info API
- Licensing APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create jobs
- Create calendar
- Create datafeeds
- Create filter
- Delete calendar
- Delete datafeeds
- Delete events from calendar
- Delete filter
- Delete forecast
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Delete expired data
- 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 filter
- Update jobs
- Update model snapshots
- Machine learning data frame analytics APIs
- Migration APIs
- Reload search analyzers
- Rollup APIs
- Search APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles 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
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect Prepare Authentication API
- OpenID Connect authenticate API
- OpenID Connect logout API
- SSL certificate
- Snapshot lifecycle management API
- Transform APIs
- Watcher APIs
- Definitions
- Release highlights
- Breaking changes
- Release notes
- 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
Translog
editTranslog
editChanges to Lucene are only persisted to disk during a Lucene commit, which is a relatively expensive operation and so cannot be performed after every index or delete operation. Changes that happen after one commit and before another will be removed from the index by Lucene in the event of process exit or hardware failure.
Lucene commits are too expensive to perform on every individual change, so each shard copy also writes operations into its transaction log known as the translog. All index and delete operations are written to the translog after being processed by the internal Lucene index but before they are acknowledged. In the event of a crash, recent operations that have been acknowledged but not yet included in the last Lucene commit are instead recovered from the translog when the shard recovers.
An Elasticsearch flush is the process of performing a Lucene commit and starting a new translog generation. Flushes are performed automatically in the background in order to make sure the translog does not grow too large, which would make replaying its operations take a considerable amount of time during recovery. The ability to perform a flush manually is also exposed through an API, although this is rarely needed.
Translog settings
editThe data in the translog is only persisted to disk when the translog is
fsync
ed and committed. In the event of a hardware failure or an operating
system crash or a JVM crash or a shard failure, any data written since the
previous translog commit will be lost.
By default, index.translog.durability
is set to request
meaning that
Elasticsearch will only report success of an index, delete, update, or bulk
request to the client after the translog has been successfully fsync
ed and
committed on the primary and on every allocated replica. If
index.translog.durability
is set to async
then Elasticsearch fsync
s and
commits the translog only every index.translog.sync_interval
which means that
any operations that were performed just before a crash may be lost when the node
recovers.
The following dynamically updatable per-index settings control the behaviour of the translog:
-
index.translog.sync_interval
-
How often the translog is
fsync
ed to disk and committed, regardless of write operations. Defaults to5s
. Values less than100ms
are not allowed. -
index.translog.durability
-
Whether or not to
fsync
and commit the translog after every index, delete, update, or bulk request. This setting accepts the following parameters:-
request
-
(default)
fsync
and commit after every request. In the event of hardware failure, all acknowledged writes will already have been committed to disk. -
async
-
fsync
and commit in the background everysync_interval
. In the event of a failure, all acknowledged writes since the last automatic commit will be discarded.
-
-
index.translog.flush_threshold_size
-
The translog stores all operations that are not yet safely persisted in Lucene
(i.e., are not part of a Lucene commit point). Although these operations are
available for reads, they will need to be replayed if the shard was stopped
and had to be recovered. This setting controls the maximum total size of these
operations, to prevent recoveries from taking too long. Once the maximum size
has been reached a flush will happen, generating a new Lucene commit point.
Defaults to
512mb
.
Translog retention
editIf an index is not using soft deletes to retain historical operations then Elasticsearch recovers each replica shard by replaying operations from the primary’s translog. This means it is important for the primary to preserve extra operations in its translog in case it needs to rebuild a replica. Moreover it is important for each replica to preserve extra operations in its translog in case it is promoted to primary and then needs to rebuild its own replicas in turn. The following settings control how much translog is retained for peer recoveries.
-
index.translog.retention.size
-
This controls the total size of translog files to keep for each shard.
Keeping more translog files increases the chance of performing an operation
based sync when recovering a replica. If the translog files are not
sufficient, replica recovery will fall back to a file based sync. Defaults to
512mb
. This setting is ignored, and should not be set, if soft deletes are enabled. Soft deletes are enabled by default in indices created in Elasticsearch versions 7.0.0 and later. -
index.translog.retention.age
-
This controls the maximum duration for which translog files are kept by each
shard. Keeping more translog files increases the chance of performing an
operation based sync when recovering replicas. If the translog files are not
sufficient, replica recovery will fall back to a file based sync. Defaults to
12h
. This setting is ignored, and should not be set, if soft deletes are enabled. Soft deletes are enabled by default in indices created in Elasticsearch versions 7.0.0 and later.
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