- 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
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- Max file size check
- Maximum map count check
- Client JVM check
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- OnError and OnOutOfMemoryError checks
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- Stopping Elasticsearch
- Upgrade Elasticsearch
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- Breaking changes
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- Aggregations changes
- Analysis changes
- Cat API changes
- Clients changes
- Cluster changes
- Document API changes
- Indices changes
- Ingest changes
- Java API changes
- Mapping changes
- Packaging changes
- Percolator changes
- Plugins changes
- Reindex changes
- REST changes
- Scripting changes
- Search and Query DSL changes
- Settings changes
- Stats and info changes
- Breaking changes in 6.1
- Breaking changes in 6.0
- X-Pack Breaking Changes
- API Conventions
- Document APIs
- Search APIs
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Cardinality Aggregation
- Extended Stats Aggregation
- Geo Bounds Aggregation
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- Max Aggregation
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- Percentiles Aggregation
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- Bucket Aggregations
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- Date Histogram Aggregation
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- Filters Aggregation
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- Global Aggregation
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- IP Range Aggregation
- Missing Aggregation
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- Range Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
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- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation
- Percentiles Bucket Aggregation
- Moving Average Aggregation
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- Bucket Script Aggregation
- Bucket Selector Aggregation
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- 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
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- Put Mapping
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- cat APIs
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- Analysis
- Anatomy of an analyzer
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- Analyzers
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- Token Filters
- Standard Token Filter
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- Length Token Filter
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- KStem Token Filter
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- Compound Word Token Filters
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- CJK Width Token Filter
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- Keep Words Token Filter
- Keep Types Token Filter
- Classic Token Filter
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- Fingerprint Token Filter
- Minhash Token Filter
- Character Filters
- Modules
- Index Modules
- Ingest Node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
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- Monitoring Elasticsearch
- X-Pack APIs
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- Close Jobs
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- Security APIs
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- Definitions
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- How To
- Testing
- Glossary of terms
- Release Notes
- 6.1.4 Release Notes
- 6.1.3 Release Notes
- 6.1.2 Release Notes
- 6.1.1 Release Notes
- 6.1.0 Release Notes
- 6.0.1 Release Notes
- 6.0.0 Release Notes
- 6.0.0-rc2 Release Notes
- 6.0.0-rc1 Release Notes
- 6.0.0-beta2 Release Notes
- 6.0.0-beta1 Release Notes
- 6.0.0-alpha2 Release Notes
- 6.0.0-alpha1 Release Notes
- 6.0.0-alpha1 Release Notes (Changes previously released in 5.x)
- X-Pack Release Notes
WARNING: Version 6.1 of Elasticsearch has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
eager_global_ordinals
editeager_global_ordinals
editGlobal ordinals is a data-structure on top of doc values, that maintains an
incremental numbering for each unique term in a lexicographic order. Each
term has a unique number and the number of term A is lower than the
number of term B. Global ordinals are only supported with
keyword
and text
fields. In keyword
fields, they
are available by default but text
fields can only use them when fielddata
,
with all of its associated baggage, is enabled.
Doc values (and fielddata) also have ordinals, which is a unique numbering for all terms in a particular segment and field. Global ordinals just build on top of this, by providing a mapping between the segment ordinals and the global ordinals, the latter being unique across the entire shard. Given that global ordinals for a specific field are tied to all the segments of a shard, they need to be entirely rebuilt whenever a once new segment becomes visible.
Global ordinals are used for features that use segment ordinals, such as
the terms
aggregation,
to improve the execution time. A terms aggregation relies purely on global
ordinals to perform the aggregation at the shard level, then converts global
ordinals to the real term only for the final reduce phase, which combines
results from different shards.
The loading time of global ordinals depends on the number of terms in a field, but in general it is low, since it source field data has already been loaded. The memory overhead of global ordinals is a small because it is very efficiently compressed.
By default, global ordinals are loaded at search-time, which is the right
trade-off if you are optimizing for indexing speed. However, if you are more
interested in search speed, it could be interesting to set
eager_global_ordinals: true
on fields that you plan to use in terms
aggregations:
PUT my_index/_mapping/my_type { "properties": { "tags": { "type": "keyword", "eager_global_ordinals": true } } }
This will shift the cost from search-time to refresh-time. Elasticsearch will make sure that global ordinals are built before publishing updates to the content of the index.
If you ever decide that you do not need to run terms
aggregations on this
field anymore, then you can disable eager loading of global ordinals at any
time:
PUT my_index/_mapping/my_type { "properties": { "tags": { "type": "keyword", "eager_global_ordinals": false } } }