- Elasticsearch Guide: other versions:
- Getting Started
- Setup Elasticsearch
- Breaking changes
- Breaking changes in 5.1
- Breaking changes in 5.0
- Search and Query DSL changes
- Mapping changes
- Percolator changes
- Suggester changes
- Index APIs changes
- Document API changes
- Settings changes
- Allocation changes
- HTTP changes
- REST API changes
- CAT API changes
- Java API changes
- Packaging
- Plugin changes
- Filesystem related changes
- Path to data on disk
- Aggregation changes
- Script related 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
- Children 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
- 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
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Metrics Aggregations
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Shadow replica indices
- 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
- Tokenizers
- Token Filters
- Standard Token Filter
- ASCII Folding 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
- 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
- Compound Word Token Filter
- 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
- Lowercase Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- Dot Expander Processor
- How To
- Testing
- Glossary of terms
- Release Notes
- 5.1.2 Release Notes
- 5.1.1 Release Notes
- 5.1.0 Release Notes
- 5.0.2 Release Notes
- 5.0.1 Release Notes
- 5.0.0 Combined Release Notes
- 5.0.0 GA Release Notes
- 5.0.0-rc1 Release Notes
- 5.0.0-beta1 Release Notes
- 5.0.0-alpha5 Release Notes
- 5.0.0-alpha4 Release Notes
- 5.0.0-alpha3 Release Notes
- 5.0.0-alpha2 Release Notes
- 5.0.0-alpha1 Release Notes
- 5.0.0-alpha1 Release Notes (Changes previously released in 2.x)
WARNING: Version 5.1 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.
Match Phrase Prefix Query
editMatch Phrase Prefix Query
editThe match_phrase_prefix
is the same as match_phrase
, except that it
allows for prefix matches on the last term in the text. For example:
GET /_search { "query": { "match_phrase_prefix" : { "message" : "quick brown f" } } }
It accepts the same parameters as the phrase type. In addition, it also
accepts a max_expansions
parameter (default 50
) that can control to how
many suffixes the last term will be expanded. It is highly recommended to set
it to an acceptable value to control the execution time of the query. For
example:
GET /_search { "query": { "match_phrase_prefix" : { "message" : { "query" : "quick brown f", "max_expansions" : 10 } } } }
The match_phrase_prefix
query is a poor-man’s autocomplete. It is very easy
to use, which lets you get started quickly with search-as-you-type but its
results, which usually are good enough, can sometimes be confusing.
Consider the query string quick brown f
. This query works by creating a
phrase query out of quick
and brown
(i.e. the term quick
must exist and
must be followed by the term brown
). Then it looks at the sorted term
dictionary to find the first 50 terms that begin with f
, and
adds these terms to the phrase query.
The problem is that the first 50 terms may not include the term fox
so the
phrase quick brown fox
will not be found. This usually isn’t a problem as
the user will continue to type more letters until the word they are looking
for appears.
For better solutions for search-as-you-type see the completion suggester and Index-Time Search-as-You-Type.