Text Analysis in Database Queries - Ocient Documentation

The enables search and analysis of textual data. You can run queries efficiently using indexes in the OcientAIQ Unified Data Platform to perform text analysis. The database supports different types of indexes. The N-gram index is a type of secondary index that enables text analysis. Cluster Key Indexes Define cluster key (CK) indexes when you create the table.

Index Type	Number of Columns	Column Types	Filters
Primary CK index (always exists)	Multiple	Fixed-length or GDC columns, fixed-length tuple columns	Equality-like, range
Additional CK indexes	Subset of CK in any order

Secondary Indexes You can create or drop secondary indexes at any time.

Index Type	Number of Columns	Column Types	Filters
Inverted indexes	Single	Fixed-length or GDC column, array, or tuple component	Equality-like, range
Hash indexes		Variable-length column, array, or tuple component	Equality-like
N-gram indexes		VARCHAR column, array, or tuple component	LIKE, equality-like

N-gram indexes support text analysis by providing an efficient search of textual data. This type of index works by tokenizing the pattern in the string, and then pruning and transforming the tokens. You can create N-gram indexes at any time. For details about creating an N-gram index, see CREATE INDEX. There are other ways to perform text analysis. For details, see the syntax for LIKE and SIMILAR TO. Data Query Language (DQL) Statement Reference Secondary Indexes

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