- Elasticsearch Guide: other versions:
- Getting Started
- 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
- Starting Elasticsearch
- Stopping Elasticsearch
- Adding nodes to your cluster
- Installing X-Pack
- Set up X-Pack
- Configuring X-Pack Java Clients
- X-Pack Settings
- Bootstrap Checks for X-Pack
- Upgrade Elasticsearch
- API Conventions
- Document APIs
- Search APIs
- 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
- Bucket Aggregations
- Adjacency Matrix Aggregation
- Auto-interval Date Histogram Aggregation
- Intervals
- Children Aggregation
- Composite 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
- Significant Text 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
- Moving Function Aggregation
- Cumulative Sum 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
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Split Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- 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
- Normalizers
- Tokenizers
- Standard Tokenizer
- Letter Tokenizer
- Lowercase Tokenizer
- Whitespace Tokenizer
- UAX URL Email Tokenizer
- Classic Tokenizer
- Thai Tokenizer
- NGram Tokenizer
- Edge NGram Tokenizer
- Keyword Tokenizer
- Pattern Tokenizer
- Char Group Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
- Path Hierarchy Tokenizer
- Path Hierarchy Tokenizer Examples
- Token Filters
- Standard Token Filter
- ASCII Folding Token Filter
- Flatten Graph 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
- Word Delimiter Graph Token Filter
- Multiplexer Token Filter
- Conditional Token Filter
- Predicate Token Filter Script
- 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
- Synonym Graph Token Filter
- Compound Word Token Filters
- 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
- Exclude mode settings example
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Remove Duplicates Token Filter
- Character Filters
- Modules
- Index Modules
- Ingest Node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Conditional Execution in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Bytes Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Dissect Processor
- Drop Processor
- Dot Expander Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub 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
- SQL Access
- Monitor a cluster
- Rolling up historical data
- Set up a cluster for high availability
- Secure a cluster
- Overview
- Configuring security
- Encrypting communications in Elasticsearch
- Encrypting communications in an Elasticsearch Docker Container
- Enabling cipher suites for stronger encryption
- Separating node-to-node and client traffic
- Configuring an Active Directory realm
- Configuring a file realm
- Configuring an LDAP realm
- Configuring a native realm
- Configuring a PKI realm
- Configuring a SAML realm
- Configuring a Kerberos realm
- FIPS 140-2
- Security settings
- Security files
- Auditing settings
- How security works
- User authentication
- Built-in users
- Internal users
- Realms
- Realm chains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user 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
- User authorization
- Auditing security events
- Encrypting communications
- Restricting connections with IP filtering
- Cross cluster search, tribe, clients, and integrations
- Tutorial: Getting started with security
- Tutorial: Encrypting communications
- Troubleshooting
- Can’t log in after upgrading to 6.5.4
- 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
- X-Pack APIs
- Info API
- Cross-cluster replication APIs
- Explore API
- Licensing APIs
- Migration APIs
- Machine learning APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create calendar
- Create datafeeds
- Create filter
- Create jobs
- Delete calendar
- Delete datafeeds
- Delete events from calendar
- Delete filter
- Delete forecast
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Find file structure
- Flush jobs
- Forecast jobs
- Get calendars
- Get buckets
- Get overall buckets
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get machine learning info
- Get model snapshots
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Revert model snapshots
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filter
- Update jobs
- Update model snapshots
- Rollup APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Create or update users
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete users
- Disable users
- Enable users
- Get application privileges
- Get role mappings
- Get roles
- Get token
- Get users
- Has privileges
- Invalidate token
- SSL certificate
- Watcher APIs
- Definitions
- Release Highlights
- Breaking changes
- Release Notes
- Elasticsearch version 6.5.4
- Elasticsearch version 6.5.3
- Elasticsearch version 6.5.2
- Elasticsearch version 6.5.1
- Elasticsearch version 6.5.0
- Elasticsearch version 6.4.3
- Elasticsearch version 6.4.2
- Elasticsearch version 6.4.1
- Elasticsearch version 6.4.0
- Elasticsearch version 6.3.2
- Elasticsearch version 6.3.1
- Elasticsearch version 6.3.0
- Elasticsearch version 6.2.4
- Elasticsearch version 6.2.3
- Elasticsearch version 6.2.2
- Elasticsearch version 6.2.1
- Elasticsearch version 6.2.0
- Elasticsearch version 6.1.4
- Elasticsearch version 6.1.3
- Elasticsearch version 6.1.2
- Elasticsearch version 6.1.1
- Elasticsearch version 6.1.0
- Elasticsearch version 6.0.1
- Elasticsearch version 6.0.0
- Elasticsearch version 6.0.0-rc2
- Elasticsearch version 6.0.0-rc1
- Elasticsearch version 6.0.0-beta2
- Elasticsearch version 6.0.0-beta1
- Elasticsearch version 6.0.0-alpha2
- Elasticsearch version 6.0.0-alpha1
- Elasticsearch version 6.0.0-alpha1 (Changes previously released in 5.x)
Scripted Metric Aggregation
editScripted Metric Aggregation
editA metric aggregation that executes using scripts to provide a metric output.
Example:
POST ledger/_search?size=0 { "query" : { "match_all" : {} }, "aggs": { "profit": { "scripted_metric": { "init_script" : "state.transactions = []", "map_script" : "state.transactions.add(doc.type.value == 'sale' ? doc.amount.value : -1 * doc.amount.value)", "combine_script" : "double profit = 0; for (t in state.transactions) { profit += t } return profit", "reduce_script" : "double profit = 0; for (a in states) { profit += a } return profit" } } } }
The above aggregation demonstrates how one would use the script aggregation compute the total profit from sale and cost transactions.
The response for the above aggregation:
{ "took": 218, ... "aggregations": { "profit": { "value": 240.0 } } }
The above example can also be specified using stored scripts as follows:
POST ledger/_search?size=0 { "aggs": { "profit": { "scripted_metric": { "init_script" : { "id": "my_init_script" }, "map_script" : { "id": "my_map_script" }, "combine_script" : { "id": "my_combine_script" }, "params": { "field": "amount" }, "reduce_script" : { "id": "my_reduce_script" } } } } }
script parameters for |
For more details on specifying scripts see script documentation.
Allowed return types
editWhilst any valid script object can be used within a single script, the scripts must return or store in the state
object only the following types:
- primitive types
- String
- Map (containing only keys and values of the types listed here)
- Array (containing elements of only the types listed here)
Scope of scripts
editThe scripted metric aggregation uses scripts at 4 stages of its execution:
- init_script
-
Executed prior to any collection of documents. Allows the aggregation to set up any initial state.
In the above example, the
init_script
creates an arraytransactions
in thestate
object. - map_script
-
Executed once per document collected. This is the only required script. If no combine_script is specified, the resulting state needs to be stored in the
state
object.In the above example, the
map_script
checks the value of the type field. If the value is sale the value of the amount field is added to the transactions array. If the value of the type field is not sale the negated value of the amount field is added to transactions. - combine_script
-
Executed once on each shard after document collection is complete. Allows the aggregation to consolidate the state returned from each shard. If a combine_script is not provided the combine phase will return the aggregation variable.
In the above example, the
combine_script
iterates through all the stored transactions, summing the values in theprofit
variable and finally returnsprofit
. - reduce_script
-
Executed once on the coordinating node after all shards have returned their results. The script is provided with access to a variable
states
which is an array of the result of the combine_script on each shard. If a reduce_script is not provided the reduce phase will return thestates
variable.In the above example, the
reduce_script
iterates through theprofit
returned by each shard summing the values before returning the final combined profit which will be returned in the response of the aggregation.
Worked Example
editImagine a situation where you index the following documents into an index with 2 shards:
PUT /transactions/_doc/_bulk?refresh {"index":{"_id":1}} {"type": "sale","amount": 80} {"index":{"_id":2}} {"type": "cost","amount": 10} {"index":{"_id":3}} {"type": "cost","amount": 30} {"index":{"_id":4}} {"type": "sale","amount": 130}
Lets say that documents 1 and 3 end up on shard A and documents 2 and 4 end up on shard B. The following is a breakdown of what the aggregation result is at each stage of the example above.
After init_script
editThis is run once on each shard before any document collection is performed, and so we will have a copy on each shard:
- Shard A
-
"state" : { "transactions" : [] }
- Shard B
-
"state" : { "transactions" : [] }
After map_script
editEach shard collects its documents and runs the map_script on each document that is collected:
- Shard A
-
"state" : { "transactions" : [ 80, -30 ] }
- Shard B
-
"state" : { "transactions" : [ -10, 130 ] }
After combine_script
editThe combine_script is executed on each shard after document collection is complete and reduces all the transactions down to a single profit figure for each shard (by summing the values in the transactions array) which is passed back to the coordinating node:
- Shard A
- 50
- Shard B
- 120
After reduce_script
editThe reduce_script receives a states
array containing the result of the combine script for each shard:
"states" : [ 50, 120 ]
It reduces the responses for the shards down to a final overall profit figure (by summing the values) and returns this as the result of the aggregation to produce the response:
{ ... "aggregations": { "profit": { "value": 170 } } }
Other Parameters
edit
params |
Optional. An object whose contents will be passed as variables to the "params" : {} |
Empty Buckets
editIf a parent bucket of the scripted metric aggregation does not collect any documents an empty aggregation response will be returned from the
shard with a null
value. In this case the reduce_script
's states
variable will contain null
as a response from that shard.
reduce_script
's should therefore expect and deal with null
responses from shards.
On this page