- 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)
Rollup search
editRollup search
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.
The Rollup Search endpoint allows searching rolled-up data using the standard query DSL. The Rollup Search endpoint is needed because, internally, rolled-up documents utilize a different document structure than the original data. The Rollup Search endpoint rewrites standard query DSL into a format that matches the rollup documents, then takes the response and rewrites it back to what a client would expect given the original query.
Request
editGET {index}/_rollup_search
Path Parameters
edit-
index
- (string) Index, indices or index-pattern to execute a rollup search against. This can include both rollup and non-rollup indices.
Rules for the index
parameter:
- At least one index/index-pattern must be specified. This can be either a rollup or non-rollup index. Omitting the index parameter,
or using _all
, is not permitted
- Multiple non-rollup indices may be specified
- Only one rollup index may be specified. If more than one are supplied an exception will be thrown
- Index patterns may be used, but if they match more than one rollup index an exception will be thrown.
Request Body
editThe request body supports a subset of features from the regular Search API. It supports:
-
query
param for specifying an DSL query, subject to some limitations (see Rollup Search Limitations and Rollup Aggregation Limitations -
aggregations
param for specifying aggregations
Functionality that is not available:
-
size
: because rollups work on pre-aggregated data, no search hits can be returned and so size must be set to zero or omitted entirely. -
highlighter
,suggestors
,post_filter
,profile
,explain
are similarly disallowed
Historical-only search example
editImagine we have an index named sensor-1
full of raw data, and we have created a rollup job with the following configuration:
PUT _xpack/rollup/job/sensor { "index_pattern": "sensor-*", "rollup_index": "sensor_rollup", "cron": "*/30 * * * * ?", "page_size" :1000, "groups" : { "date_histogram": { "field": "timestamp", "interval": "1h", "delay": "7d" }, "terms": { "fields": ["node"] } }, "metrics": [ { "field": "temperature", "metrics": ["min", "max", "sum"] }, { "field": "voltage", "metrics": ["avg"] } ] }
This rolls up the sensor-*
pattern and stores the results in sensor_rollup
. To search this rolled up data, we
need to use the _rollup_search
endpoint. However, you’ll notice that we can use regular query DSL to search the
rolled-up data:
GET /sensor_rollup/_rollup_search { "size": 0, "aggregations": { "max_temperature": { "max": { "field": "temperature" } } } }
The query is targeting the sensor_rollup
data, since this contains the rollup data as configured in the job. A max
aggregation has been used on the temperature
field, yielding the following response:
{ "took" : 102, "timed_out" : false, "terminated_early" : false, "_shards" : ... , "hits" : { "total" : 0, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "max_temperature" : { "value" : 202.0 } } }
The response is exactly as you’d expect from a regular query + aggregation; it provides some metadata about the request
(took
, _shards
, etc), the search hits (which is always empty for rollup searches), and the aggregation response.
Rollup searches are limited to functionality that was configured in the rollup job. For example, we are not able to calculate
the average temperature because avg
was not one of the configured metrics for the temperature
field. If we try
to execute that search:
GET sensor_rollup/_rollup_search { "size": 0, "aggregations": { "avg_temperature": { "avg": { "field": "temperature" } } } }
{ "error" : { "root_cause" : [ { "type" : "illegal_argument_exception", "reason" : "There is not a rollup job that has a [avg] agg with name [avg_temperature] which also satisfies all requirements of query.", "stack_trace": ... } ], "type" : "illegal_argument_exception", "reason" : "There is not a rollup job that has a [avg] agg with name [avg_temperature] which also satisfies all requirements of query.", "stack_trace": ... }, "status": 400 }
Searching both historical rollup and non-rollup data
editThe Rollup Search API has the capability to search across both "live", non-rollup data as well as the aggregated rollup data. This is done by simply adding the live indices to the URI:
GET sensor-1,sensor_rollup/_rollup_search { "size": 0, "aggregations": { "max_temperature": { "max": { "field": "temperature" } } } }
When the search is executed, the Rollup Search endpoint will do two things:
- The original request will be sent to the non-rollup index unaltered
- A rewritten version of the original request will be sent to the rollup index.
When the two responses are received, the endpoint will then rewrite the rollup response and merge the two together. During the merging process, if there is any overlap in buckets between the two responses, the buckets from the non-rollup index will be used.
The response to the above query will look as expected, despite spanning rollup and non-rollup indices:
{ "took" : 102, "timed_out" : false, "terminated_early" : false, "_shards" : ... , "hits" : { "total" : 0, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "max_temperature" : { "value" : 202.0 } } }
On this page