- 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
- Maximum size virtual memory check
- Max file size 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
- Stopping Elasticsearch
- Upgrade Elasticsearch
- Set up X-Pack
- Breaking changes
- Breaking changes in 6.0
- 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
- 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
- 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
- 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
- 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
- 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
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- 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
- Convert Processor
- Date Processor
- Date Index Name Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- KV Processor
- Lowercase Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- Dot Expander Processor
- URL Decode Processor
- Monitoring Elasticsearch
- X-Pack APIs
- Info API
- Explore API
- Machine Learning APIs
- Close Jobs
- Create Datafeeds
- Create Jobs
- Delete Datafeeds
- Delete Jobs
- Delete Model Snapshots
- Flush Jobs
- Forecast Jobs
- Get Buckets
- Get Overall Buckets
- Get Categories
- Get Datafeeds
- Get Datafeed Statistics
- Get Influencers
- Get Jobs
- Get Job Statistics
- Get Model Snapshots
- Get Records
- Open Jobs
- Post Data to Jobs
- Preview Datafeeds
- Revert Model Snapshots
- Start Datafeeds
- Stop Datafeeds
- Update Datafeeds
- Update Jobs
- Update Model Snapshots
- Security APIs
- Watcher APIs
- Migration APIs
- Deprecation Info APIs
- Definitions
- X-Pack Commands
- 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.
General recommendations
editGeneral recommendations
editDon’t return large result sets
editElasticsearch is designed as a search engine, which makes it very good at getting back the top documents that match a query. However, it is not as good for workloads that fall into the database domain, such as retrieving all documents that match a particular query. If you need to do this, make sure to use the Scroll API.
Avoid large documents
editGiven that the default http.max_context_length
is set to
100MB, Elasticsearch will refuse to index any document that is larger than
that. You might decide to increase that particular setting, but Lucene still
has a limit of about 2GB.
Even without considering hard limits, large documents are usually not
practical. Large documents put more stress on network, memory usage and disk,
even for search requests that do not request the _source
since Elasticsearch
needs to fetch the _id
of the document in all cases, and the cost of getting
this field is bigger for large documents due to how the filesystem cache works.
Indexing this document can use an amount of memory that is a multiplier of the
original size of the document. Proximity search (phrase queries for instance)
and highlighting also become more expensive
since their cost directly depends on the size of the original document.
It is sometimes useful to reconsider what the unit of information should be.
For instance, the fact you want to make books searchable doesn’t necesarily
mean that a document should consist of a whole book. It might be a better idea
to use chapters or even paragraphs as documents, and then have a property in
these documents that identifies which book they belong to. This does not only
avoid the issues with large documents, it also makes the search experience
better. For instance if a user searches for two words foo
and bar
, a match
across different chapters is probably very poor, while a match within the same
paragraph is likely good.