Executing Filtersedit

In the previous section, we skipped over a little detail called the document score (_score field in the search results). The score is a numeric value that is a relative measure of how well the document matches the search query that we specified. The higher the score, the more relevant the document is, the lower the score, the less relevant the document is.

All queries in Elasticsearch trigger computation of the relevance scores. In cases where we do not need the relevance scores, Elasticsearch provides another query capability in the form of filters. Filters are similar in concept to queries except that they are optimized for much faster execution speeds for two primary reasons:

  • Filters do not score so they are faster to execute than queries
  • Filters can be cached in memory allowing repeated search executions to be significantly faster than queries

To understand filters, let’s first introduce the filtered query, which allows you to combine a query (like match_all, match, bool, etc.) together with a filter. As an example, let’s introduce the range filter, which allows us to filter documents by a range of values. This is generally used for numeric or date filtering.

This example uses a filtered query to return all accounts with balances between 20000 and 30000, inclusive. In other words, we want to find accounts with a balance that is greater than or equal to 20000 and less than or equal to 30000.

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
  "query": {
    "filtered": {
      "query": { "match_all": {} },
      "filter": {
        "range": {
          "balance": {
            "gte": 20000,
            "lte": 30000

Dissecting the above, the filtered query contains a match_all query (the query part) and a range filter (the filter part). We can substitute any other query into the query part as well as any other filter into the filter part. In the above case, the range filter makes perfect sense since documents falling into the range all match "equally", i.e., no document is more relevant than another.

In general, the easiest way to decide whether you want a filter or a query is to ask yourself if you care about the relevance score or not. If relevance is not important, use filters, otherwise, use queries. If you come from a SQL background, queries and filters are similar in concept to the SELECT WHERE clause, although more so for filters than queries.

In addition to the match_all, match, bool, filtered, and range queries, there are a lot of other query/filter types that are available and we won’t go into them here. Since we already have a basic understanding of how they work, it shouldn’t be too difficult to apply this knowledge in learning and experimenting with the other query/filter types.