- Java REST Client (deprecated): other versions:
- Overview
- Java Low Level REST Client
- Java High Level REST Client
- Getting started
- Document APIs
- Search APIs
- Async Search APIs
- Miscellaneous APIs
- Index APIs
- Analyze API
- Create Index API
- Delete Index API
- Index Exists API
- Open Index API
- Close Index API
- Shrink Index API
- Split Index API
- Clone Index API
- Refresh API
- Flush API
- Flush Synced API
- Clear Cache API
- Force Merge API
- Rollover Index API
- Put Mapping API
- Get Mappings API
- Get Field Mappings API
- Index Aliases API
- Delete Alias API
- Exists Alias API
- Get Alias API
- Update Indices Settings API
- Get Settings API
- Put Template API
- Validate Query API
- Get Templates API
- Templates Exist API
- Get Index API
- Freeze Index API
- Unfreeze Index API
- Delete Template API
- Reload Search Analyzers API
- Cluster APIs
- Ingest APIs
- Snapshot APIs
- Tasks APIs
- Script APIs
- Licensing APIs
- Machine Learning APIs
- Put anomaly detection job API
- Get anomaly detection jobs API
- Delete anomaly detection job API
- Open anomaly detection job API
- Close anomaly detection job API
- Update anomaly detection job API
- Flush Job API
- Put datafeed API
- Update datafeed API
- Get datafeed API
- Delete datafeed API
- Preview Datafeed API
- Start datafeed API
- Stop Datafeed API
- Get datafeed stats API
- Get anomaly detection job stats API
- Forecast Job API
- Delete Forecast API
- Get buckets API
- Get overall buckets API
- Get records API
- Post Data API
- Get influencers API
- Get categories API
- Get calendars API
- Put calendar API
- Get calendar events API
- Post Calendar Event API
- Delete calendar event API
- Put anomaly detection jobs in calendar API
- Delete anomaly detection jobs from calendar API
- Delete calendar API
- Estimate anomaly detection job model memory API
- Get data frame analytics jobs API
- Get data frame analytics jobs stats API
- Put data frame analytics jobs API
- Delete data frame analytics jobs API
- Start data frame analytics jobs API
- Stop data frame analytics jobs API
- Evaluate data frame analytics API
- Explain data frame analytics API
- Get trained models API
- Put trained model API
- Get trained models stats API
- Delete trained model API
- Put Filter API
- Get filters API
- Update filter API
- Delete Filter API
- Get model snapshots API
- Delete Model Snapshot API
- Revert Model Snapshot API
- Update model snapshot API
- ML get info API
- Delete Expired Data API
- Set Upgrade Mode API
- Migration APIs
- Rollup APIs
- Security APIs
- Put User API
- Get Users API
- Delete User API
- Enable User API
- Disable User API
- Change Password API
- Put Role API
- Get Roles API
- Delete Role API
- Delete Privileges API
- Get Builtin Privileges API
- Get Privileges API
- Clear Roles Cache API
- Clear Realm Cache API
- Authenticate API
- Has Privileges API
- Get User Privileges API
- SSL Certificate API
- Put Role Mapping API
- Get Role Mappings API
- Delete Role Mapping API
- Create Token API
- Invalidate Token API
- Put Privileges API
- Create API Key API
- Get API Key information API
- Invalidate API Key API
- Watcher APIs
- Graph APIs
- CCR APIs
- Index Lifecycle Management APIs
- Snapshot Lifecycle Management APIs
- Put Snapshot Lifecycle Policy API
- Delete Snapshot Lifecycle Policy API
- Get Snapshot Lifecycle Policy API
- Start Snapshot Lifecycle Management API
- Stop Snapshot Lifecycle Management API
- Snapshot Lifecycle Management Status API
- Execute Snapshot Lifecycle Policy API
- Execute Snapshot Lifecycle Retention API
- Transform APIs
- Enrich APIs
- Using Java Builders
- Migration Guide
- License
Term Vectors API
editTerm Vectors API
editTerm Vectors API returns information and statistics on terms in the fields of a particular document. The document could be stored in the index or artificially provided by the user.
Term Vectors Request
editA TermVectorsRequest
expects an index
, a type
and an id
to specify
a certain document, and fields for which the information is retrieved.
TermVectorsRequest request = new TermVectorsRequest("authors", "1"); request.setFields("user");
Term vectors can also be generated for artificial documents, that is for documents not present in the index:
XContentBuilder docBuilder = XContentFactory.jsonBuilder(); docBuilder.startObject().field("user", "guest-user").endObject(); TermVectorsRequest request = new TermVectorsRequest("authors", docBuilder);
An artificial document is provided as an |
Optional arguments
editrequest.setFieldStatistics(false); request.setTermStatistics(true); request.setPositions(false); request.setOffsets(false); request.setPayloads(false); Map<String, Integer> filterSettings = new HashMap<>(); filterSettings.put("max_num_terms", 3); filterSettings.put("min_term_freq", 1); filterSettings.put("max_term_freq", 10); filterSettings.put("min_doc_freq", 1); filterSettings.put("max_doc_freq", 100); filterSettings.put("min_word_length", 1); filterSettings.put("max_word_length", 10); request.setFilterSettings(filterSettings); Map<String, String> perFieldAnalyzer = new HashMap<>(); perFieldAnalyzer.put("user", "keyword"); request.setPerFieldAnalyzer(perFieldAnalyzer); request.setRealtime(false); request.setRouting("routing");
Set |
|
Set |
|
Set |
|
Set |
|
Set |
|
Set |
|
Set |
|
Set |
|
Set a routing parameter |
Synchronous execution
editWhen executing a TermVectorsRequest
in the following manner, the client waits
for the TermVectorsResponse
to be returned before continuing with code execution:
TermVectorsResponse response = client.termvectors(request, RequestOptions.DEFAULT);
Synchronous calls may throw an IOException
in case of either failing to
parse the REST response in the high-level REST client, the request times out
or similar cases where there is no response coming back from the server.
In cases where the server returns a 4xx
or 5xx
error code, the high-level
client tries to parse the response body error details instead and then throws
a generic ElasticsearchException
and adds the original ResponseException
as a
suppressed exception to it.
Asynchronous execution
editExecuting a TermVectorsRequest
can also be done in an asynchronous fashion so that
the client can return directly. Users need to specify how the response or
potential failures will be handled by passing the request and a listener to the
asynchronous term-vectors method:
The asynchronous method does not block and returns immediately. Once it is
completed the ActionListener
is called back using the onResponse
method
if the execution successfully completed or using the onFailure
method if
it failed. Failure scenarios and expected exceptions are the same as in the
synchronous execution case.
A typical listener for term-vectors
looks like:
Term Vectors Response
editTermVectorsResponse
contains the following information:
String index = response.getIndex(); String type = response.getType(); String id = response.getId(); boolean found = response.getFound();
The index name of the document. |
|
The type name of the document. |
|
The id of the document. |
|
Indicates whether or not the document found. |
Inspecting Term Vectors
editIf TermVectorsResponse
contains non-null list of term vectors,
more information about each term vector can be obtained using the following:
for (TermVectorsResponse.TermVector tv : response.getTermVectorsList()) { String fieldname = tv.getFieldName(); int docCount = tv.getFieldStatistics().getDocCount(); long sumTotalTermFreq = tv.getFieldStatistics().getSumTotalTermFreq(); long sumDocFreq = tv.getFieldStatistics().getSumDocFreq(); if (tv.getTerms() != null) { List<TermVectorsResponse.TermVector.Term> terms = tv.getTerms(); for (TermVectorsResponse.TermVector.Term term : terms) { String termStr = term.getTerm(); int termFreq = term.getTermFreq(); int docFreq = term.getDocFreq(); long totalTermFreq = term.getTotalTermFreq(); float score = term.getScore(); if (term.getTokens() != null) { List<TermVectorsResponse.TermVector.Token> tokens = term.getTokens(); for (TermVectorsResponse.TermVector.Token token : tokens) { int position = token.getPosition(); int startOffset = token.getStartOffset(); int endOffset = token.getEndOffset(); String payload = token.getPayload(); } } } } }
The name of the current field |
|
Fields statistics for the current field - document count |
|
Fields statistics for the current field - sum of total term frequencies |
|
Fields statistics for the current field - sum of document frequencies |
|
Terms for the current field |
|
The name of the term |
|
Term frequency of the term |
|
Document frequency of the term |
|
Total term frequency of the term |
|
Score of the term |
|
Tokens of the term |
|
Position of the token |
|
Start offset of the token |
|
End offset of the token |
|
Payload of the token |
On this page