Quick links
Overview
Index prefixes in Elasticsearch are a crucial aspect of efficient querying and data retrieval. They allow for more precise search operations, especially when dealing with text-based data. This article delves into the intricacies of index prefixes, their usage, and optimization strategies.
Understanding Index Prefixes
Index prefixes in Elasticsearch are primarily used to speed up text search operations. They are part of the inverted index, which is the core data structure used by Elasticsearch to perform full-text search operations. Index prefixes are created during the indexing process, where each term in the text is broken down into a series of prefixes.
For instance, if we have a term “Elasticsearch”, the index prefixes would be “E”, “El”, “Ela”, “Elas”, and so on. These prefixes are then stored in the inverted index, allowing Elasticsearch to quickly match query terms with indexed documents.
Usage of Index Prefixes
Index prefixes are particularly useful when performing prefix queries, wildcard queries, and regexp queries. For example, a prefix query for “Ela*” would match documents containing terms like “Elasticsearch”, “Elastic”, “Elaborate”, etc.
Here’s an example of a prefix query:
GET /_search
{
"query": {
"prefix" : { "user" : "ki" }
}
}In this query, Elasticsearch will return all documents where the “user” field starts with “ki”.
Optimizing Index Prefixes
While index prefixes can significantly speed up search operations, they also increase the size of the inverted index, which can impact the overall performance of Elasticsearch. Therefore, it’s essential to optimize the usage of index prefixes.
One way to optimize index prefixes is by setting the `index_prefixes` field during the mapping process. This field allows you to specify the minimum and maximum length of the prefixes that Elasticsearch should index. The default values are 2 for `min_chars` and 5 for `max_chars`. The allowed values for both prefix lengths range from 1 to 20.
Here’s an example:
PUT /my_index
{
"mappings": {
"properties": {
"user": {
"type": "text",
"index_prefixes": {
"min_chars" : 1,
"max_chars" : 5
}
}
}
}
}In this mapping, Elasticsearch will only index prefixes of the “user” field that are between 1 and 5 characters long.
Another optimization strategy is to use the `index_phrases` setting, which allows Elasticsearch to index two-word phrases. This can speed up phrase queries and should be used in conjunction with `index_prefixes` for optimal performance.
Here’s an example:
PUT /my_index
{
"mappings": {
"properties": {
"user": {
"type": "text",
"index_prefixes": {
"min_chars" : 1,
"max_chars" : 5
},
"index_phrases": true
}
}
}
}Conclusion
In conclusion, index prefixes are a powerful tool in Elasticsearch that can significantly speed up search operations. However, they should be used judiciously and optimized properly to prevent performance issues. If you want to learn about the Elasticsearch exception: can only use prefix queries on keyword text and wildcard fields, check out this guide.
