- 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
- Median Absolute Deviation Aggregation
- Bucket Aggregations
- Adjacency Matrix Aggregation
- Auto-interval Date Histogram 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
- Parent 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
- Parsing synonym files
- 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
- Dot Expander Processor
- Drop Processor
- Fail Processor
- Foreach Processor
- GeoIP Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- KV 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
- User Agent processor
- Managing the index lifecycle
- SQL Access
- Monitor a cluster
- Rolling up historical data
- Frozen indices
- 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
- Token-based authentication services
- 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 6.7.2
- 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
- Freeze index
- Index lifecycle management 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
- Delete expired data
- 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
- Set upgrade mode
- 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 API keys
- 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 API key information
- Get application privileges
- Get role mappings
- Get roles
- Get token
- Get users
- Has privileges
- Invalidate API key
- Invalidate token
- SSL certificate
- Unfreeze index
- Watcher APIs
- Definitions
- Release Highlights
- Breaking changes
- Release Notes
- Elasticsearch version 6.7.2
- Elasticsearch version 6.7.1
- Elasticsearch version 6.7.0
- Elasticsearch version 6.6.2
- Elasticsearch version 6.6.1
- Elasticsearch version 6.6.0
- 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)
_all field
edit_all
field
editDeprecated in 6.0.0.
_all
may no longer be enabled for indices created in 6.0+, use a custom field and the mapping copy_to
parameter
The _all
field is a special catch-all field which concatenates the values
of all of the other fields into one big string, using space as a delimiter, which is then
analyzed and indexed, but not stored. This means that it can be
searched, but not retrieved.
The _all
field allows you to search for values in documents without knowing
which field contains the value. This makes it a useful option when getting
started with a new dataset. For instance:
PUT /my_index { "mapping": { "user": { "_all": { "enabled": true } } } } PUT /my_index/user/1 { "first_name": "John", "last_name": "Smith", "date_of_birth": "1970-10-24" } GET /my_index/_search { "query": { "match": { "_all": "john smith 1970" } } }
Enabling the |
|
The |
All values treated as strings
The date_of_birth
field in the above example is recognised as a date
field
and so will index a single term representing 1970-10-24 00:00:00 UTC
. The
_all
field, however, treats all values as strings, so the date value is
indexed as the three string terms: "1970"
, "24"
, "10"
.
It is important to note that the _all
field combines the original values
from each field as a string. It does not combine the terms from each field.
The _all
field is just a text
field, and accepts the same
parameters that other string fields accept, including analyzer
,
term_vectors
, index_options
, and store
.
The _all
field can be useful, especially when exploring new data using
simple filtering. However, by concatenating field values into one big string,
the _all
field loses the distinction between short fields (more relevant)
and long fields (less relevant). For use cases where search relevance is
important, it is better to query individual fields specifically.
The _all
field is not free: it requires extra CPU cycles and uses more disk
space. For this reason, it is disabled by default. If needed, it can be
enabled.
Using the _all
field in queries
editThe query_string
and
simple_query_string
queries query the
_all
field by default if it is enabled, unless another field is specified:
GET _search { "query": { "query_string": { "query": "john smith new york" } } }
The same goes for the ?q=
parameter in URI search
requests (which is rewritten to a query_string
query internally):
GET _search?q=john+smith+new+york
Other queries, such as the match
and
term
queries require you to specify the _all
field
explicitly, as per the first example.
Enabling the _all
field
editThe _all
field can be enabled per-type by setting enabled
to true
:
PUT my_index { "mappings": { "type_1": { "properties": {...} }, "type_2": { "_all": { "enabled": true }, "properties": {...} } } }
If the _all
field is enabled, then URI search requests and the query_string
and simple_query_string
queries can automatically use it for queries (see
Using the _all
field in queries). You can configure them to use a different field with
the index.query.default_field
setting:
Index boosting and the _all
field
editIndividual fields can be boosted at index time, with the boost
parameter. The _all
field takes these boosts into account:
PUT myindex { "mappings": { "mytype": { "_all": {"enabled": true}, "properties": { "title": { "type": "text", "boost": 2 }, "content": { "type": "text" } } } } }
When querying the |
Using index-time boosting with the _all
field has a significant
impact on query performance. Usually the better solution is to query fields
individually, with optional query time boosting.
Custom _all
fields
editWhile there is only a single _all
field per index, the copy_to
parameter allows the creation of multiple custom _all
fields. For
instance, first_name
and last_name
fields can be combined together into
the full_name
field:
PUT myindex { "mappings": { "mytype": { "properties": { "first_name": { "type": "text", "copy_to": "full_name" }, "last_name": { "type": "text", "copy_to": "full_name" }, "full_name": { "type": "text" } } } } } PUT myindex/mytype/1 { "first_name": "John", "last_name": "Smith" } GET myindex/_search { "query": { "match": { "full_name": "John Smith" } } }
Highlighting and the _all
field
editA field can only be used for highlighting if
the original string value is available, either from the
_source
field or as a stored field.
The _all
field is not present in the _source
field and it is not stored or
enabled by default, and so cannot be highlighted. There are two options. Either
store the _all
field or highlight the
original fields.
Store the _all
field
editIf store
is set to true
, then the original field value is retrievable and
can be highlighted:
PUT myindex { "mappings": { "mytype": { "_all": { "enabled": true, "store": true } } } } PUT myindex/mytype/1 { "first_name": "John", "last_name": "Smith" } GET _search { "query": { "match": { "_all": "John Smith" } }, "highlight": { "fields": { "_all": {} } } }
Of course, enabling and storing the _all
field will use significantly more
disk space and, because it is a combination of other fields, it may result in
odd highlighting results.
The _all
field also accepts the term_vector
and index_options
parameters, allowing highlighting to use it.
Highlight original fields
editYou can query the _all
field, but use the original fields for highlighting as follows:
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