Elasticsearch  Elasticsearch Percolate Query

By Opster Team

Updated: Aug 29, 2023

| 2 min read

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If you want to learn more about Elasticsearch Percolate Query, check out this guide.

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Introduction

The Percolate Query is a unique and advanced feature in Elasticsearch that allows users to pre-register queries and then evaluate a document against these queries. This article will delve into the intricacies of the Percolate Query, its use cases, and how to effectively implement it in your Elasticsearch environment.

Use cases of percolate query

The Percolate Query is particularly useful in scenarios where you need to match documents against a large set of queries. Some common use cases include:

1. Alerting: You can use the Percolate Query to trigger alerts whenever a document matches a pre-registered query.

2. Classification: It can be used to classify documents into different categories based on their content.

3. Real-time analytics: The Percolate Query can be used to perform real-time analytics on streaming data.

Implementing the percolate query

To use the Percolate Query, you first need to register your queries in an index. This is done by defining a field named `query` of type `percolator` in your index mapping along with the fields being queried in your query. Here is an example of how to register a query:

PUT /my-index/
{

  "mappings": {

    "properties": {

      "message": {

        "type": "text"

      },

      "query": {

        "type": "percolator"

      }

    }

  }

}

In this example, we are defining a field of type text called “message” as well as a field of type `percolator` called “query”.

Once you have defined your index mapping, you can index your query. For instance, we’re indexing the following match query on the field “message” for the term “Elasticsearch” with the ID 1.

PUT /my-index/_doc/1

{

  "query": {

    "match": {

      "message": "Elasticsearch"

    }

  }

}


Once you have registered all your queries, you can then percolate a document. This is done using the percolate query. Here is an example:

GET /my-index/_search
{
  "query" : {
    "percolate" : {
      "field" : "query",
      "document" : {
        "message" : "I love Elasticsearch"
      }
    }
  }
}

In this example, we are percolating a document with the message “I love Elasticsearch”. The percolate query will return the ID of any registered queries that match this document.

Optimizing the percolate query

While the Percolate Query is a useful tool, it can be resource-intensive, especially when dealing with a large number of queries. Here are some tips to optimize the performance of the Percolate Query:

1. Limit the number of clauses: Each clause in a query adds to the computational complexity. Try to keep your queries as simple as possible.

2. Use filters: Filters are faster than queries as they do not calculate relevance scores. If scoring is not important for your use case, consider using filters.

3. High number of queries: If you have a high number of queries, consider using a separate index for indexing queries so as not to store them in the same index as your documents.

4. Use the `ignore_unmapped` option: If a field specified in a query does not exist in the document, the query will fail. To prevent this, you can set the `ignore_unmapped` option to true.

GET /my-index/_search
{
  "query" : {
    "percolate" : {
      "field" : "query",
      "document" : {
        "message" : "I love Elasticsearch"
      },
      "ignore_unmapped" : true
    }
  }
}

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