Choosing the right indexing strategy for your Amazon OpenSearch Service clusters helps deliver low-latency, accurate results while maintaining efficiency. If your access patterns require complex queries, it’s best to re-evaluate your indexing strategy.
In this post, we demonstrate how you can create a custom index analyzer in OpenSearch to implement autocomplete functionality efficiently by using the Edge n-gram tokenizer to match prefix queries without using wildcards.
What is an index analyzer?
Index analyzers are used to analyze text fields during ingestion of a document. The analyzer outputs the terms you can use to match queries
By default, OpenSearch indexes your data using the standard index analyzer. The standard index analyzer splits tokens on spaces, converts tokens to lowercase, and removes most punctuation. For some use cases (like log analytics), the standard index analyzer might be all you need.
Standard Index Analyzer
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