- Elasticsearch Guide: other versions:
- What’s new in 8.17
- Elasticsearch basics
- Quick starts
- Set up Elasticsearch
- Run Elasticsearch locally
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch configuration
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Miscellaneous cluster settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
- Data stream lifecycle settings
- Field data cache settings
- Local gateway settings
- Health Diagnostic settings
- Index lifecycle management settings
- Index management settings
- Index recovery settings
- Indexing buffer settings
- Inference settings
- License settings
- Machine learning settings
- Monitoring settings
- Node settings
- Networking
- Node query cache settings
- Path settings
- Search settings
- Security settings
- Shard request cache settings
- Snapshot and restore settings
- Transforms settings
- Thread pools
- Watcher settings
- Set JVM options
- 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
- 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
- Plugins
- Upgrade Elasticsearch
- Index modules
- Mapping
- Dynamic mapping
- Explicit mapping
- Runtime fields
- Field data types
- Aggregate metric
- Alias
- Arrays
- Binary
- Boolean
- Completion
- Date
- Date nanoseconds
- Dense vector
- Flattened
- Geopoint
- Geoshape
- Histogram
- IP
- Join
- Keyword
- Nested
- Numeric
- Object
- Pass-through object
- Percolator
- Point
- Range
- Rank feature
- Rank features
- Search-as-you-type
- Semantic text
- Shape
- Sparse vector
- Text
- Token count
- Unsigned long
- Version
- Metadata fields
- Mapping parameters
analyzer
coerce
copy_to
doc_values
dynamic
eager_global_ordinals
enabled
format
ignore_above
index.mapping.ignore_above
ignore_malformed
index
index_options
index_phrases
index_prefixes
meta
fields
normalizer
norms
null_value
position_increment_gap
properties
search_analyzer
similarity
store
subobjects
term_vector
- Mapping limit settings
- Removal of mapping types
- 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 pipelines
- Example: Parse logs
- Enrich your data
- Processor reference
- Append
- Attachment
- Bytes
- Circle
- Community ID
- Convert
- CSV
- Date
- Date index name
- Dissect
- Dot expander
- Drop
- Enrich
- Fail
- Fingerprint
- Foreach
- Geo-grid
- GeoIP
- Grok
- Gsub
- HTML strip
- Inference
- IP Location
- Join
- JSON
- KV
- Lowercase
- Network direction
- Pipeline
- Redact
- Registered domain
- Remove
- Rename
- Reroute
- Script
- Set
- Set security user
- Sort
- Split
- Terminate
- Trim
- Uppercase
- URL decode
- URI parts
- User agent
- Ingest pipelines in Search
- Aliases
- Search your data
- Re-ranking
- Query DSL
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Categorize text
- Children
- Composite
- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Frequent item sets
- Geo-distance
- Geohash grid
- Geohex grid
- Geotile grid
- Global
- Histogram
- IP prefix
- IP range
- Missing
- Multi Terms
- Nested
- Parent
- Random sampler
- Range
- Rare terms
- Reverse nested
- Sampler
- Significant terms
- Significant text
- Terms
- Time series
- Variable width histogram
- Subtleties of bucketing range fields
- Metrics aggregations
- Pipeline aggregations
- Average bucket
- Bucket script
- Bucket count K-S test
- Bucket correlation
- Bucket selector
- Bucket sort
- Change point
- Cumulative cardinality
- Cumulative sum
- Derivative
- Extended stats bucket
- Inference bucket
- Max bucket
- Min bucket
- Moving function
- Moving percentiles
- Normalize
- Percentiles bucket
- Serial differencing
- Stats bucket
- Sum bucket
- Bucket aggregations
- Geospatial analysis
- Connectors
- EQL
- ES|QL
- SQL
- 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
- Tutorial: Customize built-in policies
- Tutorial: Automate rollover
- Index management in Kibana
- Overview
- Concepts
- Index lifecycle actions
- Configure a lifecycle policy
- Migrate index allocation filters to node roles
- Troubleshooting index lifecycle management errors
- Start and stop index lifecycle management
- Manage existing indices
- Skip rollover
- Restore a managed data stream or index
- Data tiers
- Autoscaling
- Monitor a cluster
- Roll up or transform your data
- Set up a cluster for high availability
- Snapshot and restore
- Secure the Elastic Stack
- Elasticsearch security principles
- Start the Elastic Stack with security enabled automatically
- Manually configure security
- Updating node security certificates
- User authentication
- Built-in users
- Service accounts
- Internal users
- Token-based authentication services
- User profiles
- Realms
- Realm chains
- Security domains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- Kerberos authentication
- JWT authentication
- Integrating with other authentication systems
- Enabling anonymous access
- Looking up users without authentication
- 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
- Role restriction
- Security privileges
- Document level security
- Field level security
- Granting privileges for data streams 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
- Enable audit logging
- Restricting connections with IP filtering
- Securing clients and integrations
- Operator privileges
- 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
- Watcher
- Cross-cluster replication
- Data store architecture
- REST APIs
- API conventions
- Common options
- REST API compatibility
- Autoscaling APIs
- Behavioral Analytics APIs
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- cat component templates
- 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
- Health
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Prevalidate node removal
- Nodes reload secure settings
- Nodes stats
- Cluster Info
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Create or update desired nodes
- Get desired nodes
- Delete desired nodes
- Get desired balance
- Reset desired balance
- Cross-cluster replication APIs
- Connector APIs
- Create connector
- Delete connector
- Get connector
- List connectors
- Update connector API key id
- Update connector configuration
- Update connector index name
- Update connector features
- Update connector filtering
- Update connector name and description
- Update connector pipeline
- Update connector scheduling
- Update connector service type
- Create connector sync job
- Cancel connector sync job
- Delete connector sync job
- Get connector sync job
- List connector sync jobs
- Check in a connector
- Update connector error
- Update connector last sync stats
- Update connector status
- Check in connector sync job
- Claim connector sync job
- Set connector sync job error
- Set connector sync job stats
- Data stream APIs
- Document APIs
- Enrich APIs
- EQL APIs
- ES|QL APIs
- Features APIs
- Fleet APIs
- Graph explore API
- Index APIs
- Alias exists
- Aliases
- Analyze
- Analyze index disk usage
- Clear cache
- Clone index
- Close index
- Create index
- Create or update alias
- Create or update component template
- Create or update index template
- Create or update index template (legacy)
- Delete component template
- Delete dangling index
- Delete alias
- Delete index
- Delete index template
- Delete index template (legacy)
- Exists
- Field usage stats
- Flush
- Force merge
- Get alias
- Get component template
- Get field mapping
- Get index
- Get index settings
- Get index template
- Get index template (legacy)
- Get mapping
- Import dangling index
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists (legacy)
- List dangling indices
- Open index
- Refresh
- Resolve index
- Resolve cluster
- Rollover
- Shrink index
- Simulate index
- Simulate template
- Split index
- Unfreeze index
- Update index settings
- Update mapping
- Index lifecycle management APIs
- Create or update lifecycle policy
- Get policy
- Delete policy
- Move to step
- Remove policy
- Retry policy
- Get index lifecycle management status
- Explain lifecycle
- Start index lifecycle management
- Stop index lifecycle management
- Migrate indices, ILM policies, and legacy, composable and component templates to data tiers routing
- Inference APIs
- Delete inference API
- Get inference API
- Perform inference API
- Create inference API
- Stream inference API
- Update inference API
- AlibabaCloud AI Search inference integration
- Amazon Bedrock inference integration
- Anthropic inference integration
- Azure AI studio inference integration
- Azure OpenAI inference integration
- Cohere inference integration
- Elasticsearch inference integration
- ELSER inference integration
- Google AI Studio inference integration
- Google Vertex AI inference integration
- HuggingFace inference integration
- Mistral inference integration
- OpenAI inference integration
- Watsonx inference integration
- Info API
- Ingest APIs
- Licensing APIs
- Logstash APIs
- Machine learning 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
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get model snapshots
- Get model snapshot upgrade statistics
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Reset jobs
- Revert model snapshots
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
- Update jobs
- Update model snapshots
- Upgrade model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Delete data frame analytics jobs
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Preview data frame analytics
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Update data frame analytics jobs
- Machine learning trained model APIs
- Clear trained model deployment cache
- Create or update trained model aliases
- Create part of a trained model
- Create trained models
- Create trained model vocabulary
- Delete trained model aliases
- Delete trained models
- Get trained models
- Get trained models stats
- Infer trained model
- Start trained model deployment
- Stop trained model deployment
- Update trained model deployment
- Migration APIs
- Node lifecycle APIs
- Query rules APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Root API
- Script APIs
- Search APIs
- Search Application APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Clear privileges cache
- Clear API key cache
- Clear service account token caches
- Create API keys
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Bulk create or update roles API
- Bulk delete roles API
- Create or update users
- Create service account tokens
- Delegate PKI authentication
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete service account token
- Delete users
- Disable users
- Enable users
- Enroll Kibana
- Enroll node
- Get API key information
- Get application privileges
- Get builtin privileges
- Get role mappings
- Get roles
- Query Role
- Get service accounts
- Get service account credentials
- Get Security settings
- Get token
- Get user privileges
- Get users
- Grant API keys
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect prepare authentication
- OpenID Connect authenticate
- OpenID Connect logout
- Query API key information
- Query User
- Update API key
- Update Security settings
- Bulk update API keys
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SAML complete logout
- SAML service provider metadata
- SSL certificate
- Activate user profile
- Disable user profile
- Enable user profile
- Get user profiles
- Suggest user profile
- Update user profile data
- Has privileges user profile
- Create Cross-Cluster API key
- Update Cross-Cluster API key
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Synonyms APIs
- Text structure APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Command line tools
- elasticsearch-certgen
- elasticsearch-certutil
- elasticsearch-create-enrollment-token
- elasticsearch-croneval
- elasticsearch-keystore
- elasticsearch-node
- elasticsearch-reconfigure-node
- elasticsearch-reset-password
- elasticsearch-saml-metadata
- elasticsearch-service-tokens
- elasticsearch-setup-passwords
- elasticsearch-shard
- elasticsearch-syskeygen
- elasticsearch-users
- Optimizations
- Troubleshooting
- Fix common cluster issues
- Diagnose unassigned shards
- Add a missing tier to the system
- Allow Elasticsearch to allocate the data in the system
- Allow Elasticsearch to allocate the index
- Indices mix index allocation filters with data tiers node roles to move through data tiers
- Not enough nodes to allocate all shard replicas
- Total number of shards for an index on a single node exceeded
- Total number of shards per node has been reached
- Troubleshooting corruption
- Fix data nodes out of disk
- Fix master nodes out of disk
- Fix other role nodes out of disk
- Start index lifecycle management
- Start Snapshot Lifecycle Management
- Restore from snapshot
- Troubleshooting broken repositories
- Addressing repeated snapshot policy failures
- Troubleshooting an unstable cluster
- Troubleshooting discovery
- Troubleshooting monitoring
- Troubleshooting transforms
- Troubleshooting Watcher
- Troubleshooting searches
- Troubleshooting shards capacity health issues
- Troubleshooting an unbalanced cluster
- Capture diagnostics
- Migration guide
- Release notes
- Elasticsearch version 8.17.1
- Elasticsearch version 8.17.0
- Elasticsearch version 8.16.2
- Elasticsearch version 8.16.1
- Elasticsearch version 8.16.0
- Elasticsearch version 8.15.5
- Elasticsearch version 8.15.4
- Elasticsearch version 8.15.3
- Elasticsearch version 8.15.2
- Elasticsearch version 8.15.1
- Elasticsearch version 8.15.0
- Elasticsearch version 8.14.3
- Elasticsearch version 8.14.2
- Elasticsearch version 8.14.1
- Elasticsearch version 8.14.0
- Elasticsearch version 8.13.4
- Elasticsearch version 8.13.3
- Elasticsearch version 8.13.2
- Elasticsearch version 8.13.1
- Elasticsearch version 8.13.0
- Elasticsearch version 8.12.2
- Elasticsearch version 8.12.1
- Elasticsearch version 8.12.0
- Elasticsearch version 8.11.4
- Elasticsearch version 8.11.3
- Elasticsearch version 8.11.2
- Elasticsearch version 8.11.1
- Elasticsearch version 8.11.0
- Elasticsearch version 8.10.4
- Elasticsearch version 8.10.3
- Elasticsearch version 8.10.2
- Elasticsearch version 8.10.1
- Elasticsearch version 8.10.0
- Elasticsearch version 8.9.2
- Elasticsearch version 8.9.1
- Elasticsearch version 8.9.0
- Elasticsearch version 8.8.2
- Elasticsearch version 8.8.1
- Elasticsearch version 8.8.0
- Elasticsearch version 8.7.1
- Elasticsearch version 8.7.0
- Elasticsearch version 8.6.2
- Elasticsearch version 8.6.1
- Elasticsearch version 8.6.0
- Elasticsearch version 8.5.3
- Elasticsearch version 8.5.2
- Elasticsearch version 8.5.1
- Elasticsearch version 8.5.0
- Elasticsearch version 8.4.3
- Elasticsearch version 8.4.2
- Elasticsearch version 8.4.1
- Elasticsearch version 8.4.0
- Elasticsearch version 8.3.3
- Elasticsearch version 8.3.2
- Elasticsearch version 8.3.1
- Elasticsearch version 8.3.0
- Elasticsearch version 8.2.3
- Elasticsearch version 8.2.2
- Elasticsearch version 8.2.1
- Elasticsearch version 8.2.0
- Elasticsearch version 8.1.3
- Elasticsearch version 8.1.2
- Elasticsearch version 8.1.1
- Elasticsearch version 8.1.0
- Elasticsearch version 8.0.1
- Elasticsearch version 8.0.0
- Elasticsearch version 8.0.0-rc2
- Elasticsearch version 8.0.0-rc1
- Elasticsearch version 8.0.0-beta1
- Elasticsearch version 8.0.0-alpha2
- Elasticsearch version 8.0.0-alpha1
- Dependencies and versions
Reindex a time series data stream (TSDS)
editReindex a time series data stream (TSDS)
editIntroduction
editWith reindexing, you can copy documents from an old time-series data stream (TSDS) to a new one. Data streams support reindexing in general, with a few restrictions. Still, time-series data streams introduce additional challenges due to tight control on the accepted timestamp range for each backing index they contain. Direct use of the reindex API would likely error out due to attempting to insert documents with timestamps that are outside the current acceptance window.
To avoid these limitations, use the process that is outlined below:
- Create an index template for the destination data stream that will contain the re-indexed data.
-
Update the template to
-
Set
index.time_series.start_time
andindex.time_series.end_time
index settings to match the lowest and highest@timestamp
values in the old data stream. -
Set the
index.number_of_shards
index setting to the sum of all primary shards of all backing indices of the old data stream. -
Set
index.number_of_replicas
to zero and unset theindex.lifecycle.name
index setting.
-
Set
- Run the reindex operation to completion.
- Revert the overriden index settings in the destination index template.
-
Invoke the
rollover
api to create a new backing index that can receive new documents.
This process only applies to time-series data streams without downsampling configuration. Data streams with downsampling can only be re-indexed by re-indexing their backing indexes individually and adding them to an empty destination data stream.
In what follows, we elaborate on each step of the process with examples.
Create a TSDS template to accept old documents
editConsider a TSDS with the following template:
resp = client.cluster.put_component_template( name="source_template", template={ "settings": { "index": { "number_of_replicas": 2, "number_of_shards": 2, "mode": "time_series", "routing_path": [ "metricset" ] } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "metricset": { "type": "keyword", "time_series_dimension": True }, "k8s": { "properties": { "tx": { "type": "long" }, "rx": { "type": "long" } } } } } }, ) print(resp) resp1 = client.indices.put_index_template( name="1", index_patterns=[ "k8s*" ], composed_of=[ "source_template" ], data_stream={}, ) print(resp1)
response = client.cluster.put_component_template( name: 'source_template', body: { template: { settings: { index: { number_of_replicas: 2, number_of_shards: 2, mode: 'time_series', routing_path: [ 'metricset' ] } }, mappings: { properties: { "@timestamp": { type: 'date' }, metricset: { type: 'keyword', time_series_dimension: true }, "k8s": { properties: { tx: { type: 'long' }, rx: { type: 'long' } } } } } } } ) puts response response = client.indices.put_index_template( name: 1, body: { index_patterns: [ 'k8s*' ], composed_of: [ 'source_template' ], data_stream: {} } ) puts response
const response = await client.cluster.putComponentTemplate({ name: "source_template", template: { settings: { index: { number_of_replicas: 2, number_of_shards: 2, mode: "time_series", routing_path: ["metricset"], }, }, mappings: { properties: { "@timestamp": { type: "date", }, metricset: { type: "keyword", time_series_dimension: true, }, k8s: { properties: { tx: { type: "long", }, rx: { type: "long", }, }, }, }, }, }, }); console.log(response); const response1 = await client.indices.putIndexTemplate({ name: 1, index_patterns: ["k8s*"], composed_of: ["source_template"], data_stream: {}, }); console.log(response1);
POST /_component_template/source_template { "template": { "settings": { "index": { "number_of_replicas": 2, "number_of_shards": 2, "mode": "time_series", "routing_path": [ "metricset" ] } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "metricset": { "type": "keyword", "time_series_dimension": true }, "k8s": { "properties": { "tx": { "type": "long" }, "rx": { "type": "long" } } } } } } } POST /_index_template/1 { "index_patterns": [ "k8s*" ], "composed_of": [ "source_template" ], "data_stream": {} }
A possible output of /k8s/_settings
looks like:
{ ".ds-k8s-2023.09.01-000002": { "settings": { "index": { "mode": "time_series", "routing": { "allocation": { "include": { "_tier_preference": "data_hot" } } }, "hidden": "true", "number_of_shards": "2", "time_series": { "end_time": "2023-09-01T14:00:00.000Z", "start_time": "2023-09-01T10:00:00.000Z" }, "provided_name": ".ds-k9s-2023.09.01-000002", "creation_date": "1694439857608", "number_of_replicas": "2", "routing_path": [ "metricset" ], ... } } }, ".ds-k8s-2023.09.01-000001": { "settings": { "index": { "mode": "time_series", "routing": { "allocation": { "include": { "_tier_preference": "data_hot" } } }, "hidden": "true", "number_of_shards": "2", "time_series": { "end_time": "2023-09-01T10:00:00.000Z", "start_time": "2023-09-01T06:00:00.000Z" }, "provided_name": ".ds-k9s-2023.09.01-000001", "creation_date": "1694439837126", "number_of_replicas": "2", "routing_path": [ "metricset" ], ... } } } }
To reindex this TSDS, do not to re-use its index template in the destination data stream, to avoid impacting its functionality. Instead, clone the template of the source TSDS and apply the following modifications:
-
Set
index.time_series.start_time
andindex.time_series.end_time
index settings explicitly. Their values should be based on the lowest and highest@timestamp
values in the data stream to reindex. This way, the initial backing index can load all data that is contained in the source data stream. -
Set
index.number_of_shards
index setting to the sum of all primary shards of all backing indices of the source data stream. This helps maintain the same level of search parallelism, as each shard is processed in a separate thread (or more). -
Unset the
index.lifecycle.name
index setting, if any. This prevents ILM from modifying the destination data stream during reindexing. -
(Optional) Set
index.number_of_replicas
to zero. This helps speed up the reindex operation. Since the data gets copied, there is limited risk of data loss due to lack of replicas.
Using the example above as source TSDS, the template for the destination TSDS would be:
resp = client.cluster.put_component_template( name="destination_template", template={ "settings": { "index": { "number_of_replicas": 0, "number_of_shards": 4, "mode": "time_series", "routing_path": [ "metricset" ], "time_series": { "end_time": "2023-09-01T14:00:00.000Z", "start_time": "2023-09-01T06:00:00.000Z" } } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "metricset": { "type": "keyword", "time_series_dimension": True }, "k8s": { "properties": { "tx": { "type": "long" }, "rx": { "type": "long" } } } } } }, ) print(resp) resp1 = client.indices.put_index_template( name="2", index_patterns=[ "k9s*" ], composed_of=[ "destination_template" ], data_stream={}, ) print(resp1)
const response = await client.cluster.putComponentTemplate({ name: "destination_template", template: { settings: { index: { number_of_replicas: 0, number_of_shards: 4, mode: "time_series", routing_path: ["metricset"], time_series: { end_time: "2023-09-01T14:00:00.000Z", start_time: "2023-09-01T06:00:00.000Z", }, }, }, mappings: { properties: { "@timestamp": { type: "date", }, metricset: { type: "keyword", time_series_dimension: true, }, k8s: { properties: { tx: { type: "long", }, rx: { type: "long", }, }, }, }, }, }, }); console.log(response); const response1 = await client.indices.putIndexTemplate({ name: 2, index_patterns: ["k9s*"], composed_of: ["destination_template"], data_stream: {}, }); console.log(response1);
POST /_component_template/destination_template { "template": { "settings": { "index": { "number_of_replicas": 0, "number_of_shards": 4, "mode": "time_series", "routing_path": [ "metricset" ], "time_series": { "end_time": "2023-09-01T14:00:00.000Z", "start_time": "2023-09-01T06:00:00.000Z" } } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "metricset": { "type": "keyword", "time_series_dimension": true }, "k8s": { "properties": { "tx": { "type": "long" }, "rx": { "type": "long" } } } } } } } POST /_index_template/2 { "index_patterns": [ "k9s*" ], "composed_of": [ "destination_template" ], "data_stream": {} }
Reindex
editInvoke the reindex api, for instance:
resp = client.reindex( source={ "index": "k8s" }, dest={ "index": "k9s", "op_type": "create" }, ) print(resp)
response = client.reindex( body: { source: { index: 'k8s' }, dest: { index: 'k9s', op_type: 'create' } } ) puts response
const response = await client.reindex({ source: { index: "k8s", }, dest: { index: "k9s", op_type: "create", }, }); console.log(response);
POST /_reindex { "source": { "index": "k8s" }, "dest": { "index": "k9s", "op_type": "create" } }
Restore the destination index template
editOnce the reindexing operation completes, restore the index template for the destination TSDS as follows:
-
Remove the overrides for
index.time_series.start_time
andindex.time_series.end_time
. -
Restore the values of
index.number_of_shards
,index.number_of_replicas
andindex.lifecycle.name
as applicable.
Using the previous example, the destination template is modified as follows:
resp = client.cluster.put_component_template( name="destination_template", template={ "settings": { "index": { "number_of_replicas": 2, "number_of_shards": 2, "mode": "time_series", "routing_path": [ "metricset" ] } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "metricset": { "type": "keyword", "time_series_dimension": True }, "k8s": { "properties": { "tx": { "type": "long" }, "rx": { "type": "long" } } } } } }, ) print(resp)
response = client.cluster.put_component_template( name: 'destination_template', body: { template: { settings: { index: { number_of_replicas: 2, number_of_shards: 2, mode: 'time_series', routing_path: [ 'metricset' ] } }, mappings: { properties: { "@timestamp": { type: 'date' }, metricset: { type: 'keyword', time_series_dimension: true }, "k8s": { properties: { tx: { type: 'long' }, rx: { type: 'long' } } } } } } } ) puts response
const response = await client.cluster.putComponentTemplate({ name: "destination_template", template: { settings: { index: { number_of_replicas: 2, number_of_shards: 2, mode: "time_series", routing_path: ["metricset"], }, }, mappings: { properties: { "@timestamp": { type: "date", }, metricset: { type: "keyword", time_series_dimension: true, }, k8s: { properties: { tx: { type: "long", }, rx: { type: "long", }, }, }, }, }, }, }); console.log(response);
POST /_component_template/destination_template { "template": { "settings": { "index": { "number_of_replicas": 2, "number_of_shards": 2, "mode": "time_series", "routing_path": [ "metricset" ] } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "metricset": { "type": "keyword", "time_series_dimension": true }, "k8s": { "properties": { "tx": { "type": "long" }, "rx": { "type": "long" } } } } } } }
Next, Invoke the rollover
api on the destination data stream without any conditions set.
resp = client.indices.rollover( alias="k9s", ) print(resp)
response = client.indices.rollover( alias: 'k9s' ) puts response
const response = await client.indices.rollover({ alias: "k9s", }); console.log(response);
POST /k9s/_rollover/
This creates a new backing index with the updated index settings. The destination data stream is now ready to accept new documents.
Note that the initial backing index can still accept documents within the range of timestamps derived from the source data stream. If this is not desired, mark it as read-only explicitly.
On this page