Field Mapping

Individual Field Mapping

By default, JanusGraph will encode property keys to generate a unique field name for the property key in the mixed index. If one wants to query the mixed index directly in the external index backend can be difficult to deal with and are illegible. For this use case, the field name can be explicitly specified through a parameter.

mgmt = graph.openManagement()
name = mgmt.makePropertyKey('bookname').dataType(String.class).make()
mgmt.buildIndex('booksBySummary', Vertex.class).addKey(name, Parameter.of('mapped-name', 'bookname')).buildMixedIndex("search")
mgmt.commit()

With this field mapping defined as a parameter, JanusGraph will use the same name for the field in the booksBySummary index created in the external index system as for the property key. Note, that it must be ensured that the given field name is unique in the index.

Global Field Mapping

Instead of individually adjusting the field mapping for every key added to a mixed index, one can instruct JanusGraph to always set the field name in the external index to be identical to the property key name. This is accomplished by enabling the configuration option map-name which is configured per indexing backend. If this option is enabled for a particular indexing backend, then all mixed indexes defined against said backend will use field names identical to the property key names.

However, this approach has two limitations: 1) The user has to ensure that the property key names are valid field names for the indexing backend and 2) renaming the property key will NOT rename the field name in the index which can lead to naming collisions that the user has to be aware of and avoid.

Note, that individual field mappings as described above can be used to overwrite the default name for a particular key.

Custom Analyzer

By default, JanusGraph will use the default analyzer from the indexing backend for properties with Mapping.TEXT, and no analyzer for properties with Mapping.STRING. If one wants to use another analyzer, it can be explicitly specified through a parameter : ParameterType.TEXT_ANALYZER for Mapping.TEXT and ParameterType.STRING_ANALYZER for Mapping.STRING.

For Elasticsearch

The name of the analyzer must be set as parameter value.

mgmt = graph.openManagement()
string = mgmt.makePropertyKey('string').dataType(String.class).make()
text = mgmt.makePropertyKey('text').dataType(String.class).make()
textString = mgmt.makePropertyKey('textString').dataType(String.class).make()
mgmt.buildIndex('string', Vertex.class).addKey(string, Mapping.STRING.asParameter(), Parameter.of(ParameterType.STRING_ANALYZER.getName(), 'standard')).buildMixedIndex("search")
mgmt.buildIndex('text', Vertex.class).addKey(text, Mapping.TEXT.asParameter(), Parameter.of(ParameterType.TEXT_ANALYZER.getName(), 'english')).buildMixedIndex("search")
mgmt.buildIndex('textString', Vertex.class).addKey(text, Mapping.TEXTSTRING.asParameter(), Parameter.of(ParameterType.STRING_ANALYZER.getName(), 'standard'), Parameter.of(ParameterType.TEXT_ANALYZER.getName(), 'english')).buildMixedIndex("search")
mgmt.commit()

With these settings, JanusGraph will use the standard analyzer for property key string and the english analyzer for property key text.

For Solr

The class of the tokenizer must be set as parameter value.

mgmt = graph.openManagement()
string = mgmt.makePropertyKey('string').dataType(String.class).make()
text = mgmt.makePropertyKey('text').dataType(String.class).make()
mgmt.buildIndex('string', Vertex.class).addKey(string, Mapping.STRING.asParameter(), Parameter.of(ParameterType.STRING_ANALYZER.getName(), 'org.apache.lucene.analysis.standard.StandardTokenizer')).buildMixedIndex("search")
mgmt.buildIndex('text', Vertex.class).addKey(text, Mapping.TEXT.asParameter(), Parameter.of(ParameterType.TEXT_ANALYZER.getName(), 'org.apache.lucene.analysis.core.WhitespaceTokenizer')).buildMixedIndex("search")
mgmt.commit()

With these settings, JanusGraph will use the standard tokenizer for property key string and the whitespace tokenizer for property key text.