Elasticsearch Query Tester

The bool query is the primary way to combine multiple queries. It has four clauses: must (all must match, contributes to relevance score), filter (must match but doesn't affect score — cached, faster), should (optional — boosts score if matched), and must_not (excluded, cached). Use filter for structured data like status or date ranges, and must for full-text relevance.

match is for full-text fields — it analyzes the query string using the same analyzer as the indexed field (lowercasing, stemming, etc.). term is for exact value matching on keyword, numeric, and boolean fields. Using term on a text field usually fails because the stored value is tokenized, not the original string.

Use filter for anything where relevance score doesn't matter — IDs, status codes, date ranges, numeric thresholds. Filter results are cached by Elasticsearch, making them significantly faster on repeated queries. Use must only when you want the clause to contribute to the _score (full-text relevance).

Setting size: 0 tells Elasticsearch not to return any document hits — only the aggregation results. This is the standard pattern for analytics queries where you only care about counts, averages, or groupings, not the actual documents.

In a bool query with should clauses, minimum_should_match controls how many should conditions must match. Normally if must or filter clauses exist, should is optional. Set minimum_should_match: 1 to require at least one should clause to match even when must/filter is present.

No. All analysis runs entirely in your browser. Nothing is sent to any server — not Elasticsearch, not our servers, nothing. Your query stays local.