- 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
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- OnError and OnOutOfMemoryError checks
- Early-access check
- G1GC check
- All permission check
- Starting Elasticsearch
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- Adding nodes to your cluster
- Installing X-Pack
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- 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
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- Rollover Index
- Put Mapping
- Get Mapping
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- Types Exists
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- Clear Cache
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- cat APIs
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- Query DSL
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- Analysis
- Anatomy of an analyzer
- Testing analyzers
- Analyzers
- Normalizers
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- Standard Tokenizer
- Letter Tokenizer
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- Whitespace Tokenizer
- UAX URL Email Tokenizer
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- 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
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- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
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- Stop Token Filter
- Word Delimiter Token Filter
- Word Delimiter Graph Token Filter
- Multiplexer Token Filter
- Conditional Token Filter
- Predicate Token Filter Script
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- 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
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- Processors
- Append Processor
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- SQL Access
- Monitor a cluster
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- 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
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- 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
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- How To
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- Add events to calendar
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- Find file structure
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- Rollup APIs
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- Authenticate
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- 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)
Path Hierarchy Tokenizer Examples
editPath Hierarchy Tokenizer Examples
editA common use-case for the path_hierarchy
tokenizer is filtering results by
file paths. If indexing a file path along with the data, the use of the
path_hierarchy
tokenizer to analyze the path allows filtering the results
by different parts of the file path string.
This example configures an index to have two custom analyzers and applies
those analyzers to multifields of the file_path
text field that will
store filenames. One of the two analyzers uses reverse tokenization.
Some sample documents are then indexed to represent some file paths
for photos inside photo folders of two different users.
PUT file-path-test { "settings": { "analysis": { "analyzer": { "custom_path_tree": { "tokenizer": "custom_hierarchy" }, "custom_path_tree_reversed": { "tokenizer": "custom_hierarchy_reversed" } }, "tokenizer": { "custom_hierarchy": { "type": "path_hierarchy", "delimiter": "/" }, "custom_hierarchy_reversed": { "type": "path_hierarchy", "delimiter": "/", "reverse": "true" } } } }, "mappings": { "_doc": { "properties": { "file_path": { "type": "text", "fields": { "tree": { "type": "text", "analyzer": "custom_path_tree" }, "tree_reversed": { "type": "text", "analyzer": "custom_path_tree_reversed" } } } } } } } POST file-path-test/_doc/1 { "file_path": "/User/alice/photos/2017/05/16/my_photo1.jpg" } POST file-path-test/_doc/2 { "file_path": "/User/alice/photos/2017/05/16/my_photo2.jpg" } POST file-path-test/_doc/3 { "file_path": "/User/alice/photos/2017/05/16/my_photo3.jpg" } POST file-path-test/_doc/4 { "file_path": "/User/alice/photos/2017/05/15/my_photo1.jpg" } POST file-path-test/_doc/5 { "file_path": "/User/bob/photos/2017/05/16/my_photo1.jpg" }
A search for a particular file path string against the text field matches all
the example documents, with Bob’s documents ranking highest due to bob
also
being one of the terms created by the standard analyzer boosting relevance for
Bob’s documents.
GET file-path-test/_search { "query": { "match": { "file_path": "/User/bob/photos/2017/05" } } }
It’s simple to match or filter documents with file paths that exist within a
particular directory using the file_path.tree
field.
GET file-path-test/_search { "query": { "term": { "file_path.tree": "/User/alice/photos/2017/05/16" } } }
With the reverse parameter for this tokenizer, it’s also possible to match
from the other end of the file path, such as individual file names or a deep
level subdirectory. The following example shows a search for all files named
my_photo1.jpg
within any directory via the file_path.tree_reversed
field
configured to use the reverse parameter in the mapping.
GET file-path-test/_search { "query": { "term": { "file_path.tree_reversed": { "value": "my_photo1.jpg" } } } }
Viewing the tokens generated with both forward and reverse is instructive in showing the tokens created for the same file path value.
POST file-path-test/_analyze { "analyzer": "custom_path_tree", "text": "/User/alice/photos/2017/05/16/my_photo1.jpg" } POST file-path-test/_analyze { "analyzer": "custom_path_tree_reversed", "text": "/User/alice/photos/2017/05/16/my_photo1.jpg" }
It’s also useful to be able to filter with file paths when combined with other
types of searches, such as this example looking for any files paths with 16
that also must be in Alice’s photo directory.
GET file-path-test/_search { "query": { "bool" : { "must" : { "match" : { "file_path" : "16" } }, "filter": { "term" : { "file_path.tree" : "/User/alice" } } } } }