1. Elasticsearch (Presentation 02) By Maruf Hassan Email: maruf571@gmail.com Date: 06 April, 2015 2. ContentContent Query DSL Queries Vs Filters Filters term Filter terms Filter range Filter exists and missing Filters bool Filter Query match_all Query match Query multi_match Query Bool Query Queries with Filters 3. Query DSL There are two types of (query) DSL. filter DSL & query DSL filter DSL: A filter asks yes/no question of every document and is used for fields that contain exact values. Example: Is the `created` date in the range `2013` - `2014`? Does the `status` field contain the term `published`? Is the `lat_lon` field within `10km` of a specified point? query DSL :A query is similar to a filter, but also asks the question: How well does this document match? A query calculates how relevant each document is to the query, and assigns it a relevance `_score`. Example: Best matching the words `full text search` Containing the word `run`, but maybe also matching `runs`, `running`, `jog`, or `sprint` Containing the words `quick`, `brown`, and `fox`; the closer together they are, the more relevant the document 4. Queries Vs Filters Filter:The output from most filter clauses --a simple list of the documents that match the filter --is quick to calculate and easy to cache in memory Queries: Queries have to not only find matching documents --but also --calculate how relevant each document is --query results are not cache. When to Use Which Use query clauses for full-text search or for any condition that should affect the relevance score And use filter clauses for everything else Filter is faster :) 5. Filters Most important filters term Filter terms Filter range Filter exists and missing Filters bool Filter 6. term Filter The `term` filter is used to filter by exact values, be they numbers, dates, Booleans, or not_analyzed` exact-value string fields Example: { "term": { "age": 26 }} { "term": { "date": "2014-09-01" }} { "term": { "public": true }} { "term": { "tag": "full_text" }} 7. terms Filter Allows you to specify multiple values to match. If the field contains any of the specified values, the document matches Example: { "terms": { "tag": [ "search", "full_text", "nosql" ] } } 8. range Filter The `range` filter allows you to find numbers or dates that fall into a specified range Example: { "range": { "age": { "gte": 20, "lt": 30 }}} 9. exists and missing Filters The `exists` and `missing` filters are used to find documents in which the specified field either has one or more values or doesn't have any values Example: { "exists": { "field": "title" } } 10. bool Filter The `bool` filter is used to combine multiple filter clauses using Boolean logic. It accepts three parameters must: These clauses must match, like and must_not: These clauses must not match, like not. should: At least one of these clauses must match, like or. Example: { "bool": { "must": { "term": { "folder": "inbox" }}, "must_not": { "term": { "tag": "spam" }}, "should": [ { "term": { "starred": true }}, { "term": { "unread": true }} ] }} 11. Query most important queries match_all Query match Query multi_match Query bool Query 12. match_all Query The `match_all` query simply matches all documents. It is the default query that is used if no query has been specified Example: { "match_all": {}} 13. match Query The `match` query should be the standard query that you reach for whenever you want to query for a full-text or exact value in almost any field. Example: (need analyze the query) { "match": { "tweet": "About Search" }} (not_analyzed) { "match": { "age": 26 }} { "match": { "date": "2014-09-01" }} { "match": { "public": true }} { "match": { "tag": "full_text" }} 14. multi_match Query The `multi_match` query allows to run the same `match` query on multiple fields Example: { "multi_match": { "query": "full text search", "fields": [ "title", "body" ] } } 15. bool Query The `bool` query used to combine multiple query clauses.This query accepts the following parameters: `must`: Clauses that must_match for the document to be included. `must_not`:Clauses that must not match for the document to be included. `should`:If these clauses match, they increase the `_score`; otherwise, they have no effect. { "bool": { "must": { "match": { "title": "how to make millions" }}, "must_not": { "match": { "tag": "spam" }}, "should": [ { "match": { "tag": "starred" }}, { "range": { "date": { "gte": "2014-01-01" }}} ] } } 16. Queries with Filters It is often useful to apply a filter to a query or, less frequently, to use a full-text query as a filter. Filtering a Query Match Query: { "query": { "match": { "interests": internet" }} } Term filter: { "filter": { "range": { "age": { "gte": 18 }}} Filtering query GET /cefalo/employee/_search { "query": { "filtered": { "query": { "match": { "interests": "internet" } }, "filter": { "range": { "age": { "gte": 25 }} }}}} 17. Queries with Filters Just as a Filter Query: { "query": { "match_all": {}} Filter: "filter": { "term": { "age": "28" } } Just filter in a all document GET /cefalo/employee/_search { "query": { "filtered": { "query": { "match_all": {}}, "filter": { "term": { "age": "28" } } }}} 18. Thanks