elasticsearch bool query combine must with OR

Question

I am currently trying to migrate a solr-based application to elasticsearch.

I have this lucene query:

(( 
    name:(+foo +bar) 
    OR info:(+foo +bar) 
)) AND state:(1) AND (has_image:(0) OR has_image:(1)^100)

As far as I understand this is a combination of must clauses combined with boolean OR:

Get all documents containing (foo AND bar in name) OR (foo AND bar in info). After that filter results by condition state=1 and boost documents that have an image.

I have been trying to use a bool query with must but I am failing to get boolean OR into must clauses. Here is what I have:

GET /test/object/_search
{
  "from": 0,
  "size": 20,
  "sort": {
    "_score": "desc"
  },
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "name": "foo"
          }
        },
        {
          "match": {
            "name": "bar"
          }
        }
      ],
      "must_not": [],
      "should": [
        {
          "match": {
            "has_image": {
              "query": 1,
              "boost": 100
            }
          }
        }
      ]
    }
  }
}

As you can see, must conditions for info are missing.

** UPDATE **

I have updated my elasticsearch query and got rid of that function score. My base problem still exists.

Answer 1

• OR is spelled should
• AND is spelled must
• NOR is spelled must_not

Example:

You want to see all the items that are (round AND (red OR blue)):

    {
        "query": {
            "bool": {
                "must": [
                    {
                        "term": {"shape": "round"}
                    },
                    {
                        "bool": {
                            "should": [
                                {"term": {"color": "red"}},
                                {"term": {"color": "blue"}}
                            ]
                        }
                    }
                ]
            }
        }
    }

You can also do more complex versions of OR, for example, if you want to match at least 3 out of 5, you can specify 5 options under "should" and set a "minimum_should" of 3.

Thanks to Glen Thompson and Sebastialonso for finding where my nesting wasn't quite right before.

Thanks also to Fatmajk for pointing out that "term" becomes a "match" in ElasticSearch Version 6.

Answer 2

This is how you can nest multiple bool queries in one outer bool query this using Kibana,

• bool indicates we are using boolean
• must is for AND
• should is for OR

GET my_inedx/my_type/_search
{
  "query" : {
     "bool": {             //bool indicates we are using boolean operator
          "must" : [       //must is for **AND**
               {
                 "match" : {
                       "description" : "some text"  
                   }
               },
               {
                  "match" :{
                        "type" : "some Type"
                   }
               },
               {
                  "bool" : {          //here its a nested boolean query
                        "should" : [  //should is for **OR**
                               {
                                 "match" : {
                                     //ur query
                                }
                               },
                               { 
                                  "match" : {} 
                               }     
                             ]
                        }
               }
           ]
      }
  }
}

This is how you can nest a query in ES

---

There are more types in "bool" like,

1. Filter
2. must_not

Answer 3

If you were using Solr's default or Lucene query parser, you can pretty much always put it into a query string query:

POST test/_search
{
  "query": {
    "query_string": {
      "query": "(( name:(+foo +bar) OR info:(+foo +bar)  )) AND state:(1) AND (has_image:(0) OR has_image:(1)^100)"
    }
  }
}

That said, you may want to use a boolean query, like the one you already posted, or even a combination of the two.

Answer 4

$filterQuery = $this->queryFactory->create(QueryInterface::TYPE_BOOL, ['must' => $queries,'should'=>$queriesGeo]);

In must you need to add the query condition array which you want to work with AND and in should you need to add the query condition which you want to work with OR.

You can check this: https://github.com/Smile-SA/elasticsuite/issues/972

Answer 5

I recently had to solve this problem too, and after a LOT of trial and error I came up with this (in PHP, but maps directly to the DSL):

'query' => [
    'bool' => [
        'should' => [
            ['prefix' => ['name_first' => $query]],
            ['prefix' => ['name_last' => $query]],
            ['prefix' => ['phone' => $query]],
            ['prefix' => ['email' => $query]],
            [
                'multi_match' => [
                    'query' => $query,
                    'type' => 'cross_fields',
                    'operator' => 'and',
                    'fields' => ['name_first', 'name_last']
                ]
            ]
        ],
        'minimum_should_match' => 1,
        'filter' => [
            ['term' => ['state' => 'active']],
            ['term' => ['company_id' => $companyId]]
        ]
    ]
]

Which maps to something like this in SQL:

SELECT * from <index> 
WHERE (
    name_first LIKE '<query>%' OR
    name_last LIKE '<query>%' OR
    phone LIKE  '<query>%' OR
    email LIKE '<query>%'
)
AND state = 'active'
AND company_id = <query>

The key in all this is the minimum_should_match setting. Without this the filter totally overrides the should.

Hope this helps someone!

Answer 6

I finally managed to create a query that does exactly what i wanted to have:

A filtered nested boolean query. I am not sure why this is not documented. Maybe someone here can tell me?

Here is the query:

GET /test/object/_search
{
  "from": 0,
  "size": 20,
  "sort": {
    "_score": "desc"
  },
  "query": {
    "filtered": {
      "filter": {
        "bool": {
          "must": [
            {
              "term": {
                "state": 1
              }
            }
          ]
        }
      },
      "query": {
        "bool": {
          "should": [
            {
              "bool": {
                "must": [
                  {
                    "match": {
                      "name": "foo"
                    }
                  },
                  {
                    "match": {
                      "name": "bar"
                    }
                  }
                ],
                "should": [
                  {
                    "match": {
                      "has_image": {
                        "query": 1,
                        "boost": 100
                      }
                    }
                  }
                ]
              }
            },
            {
              "bool": {
                "must": [
                  {
                    "match": {
                      "info": "foo"
                    }
                  },
                  {
                    "match": {
                      "info": "bar"
                    }
                  }
                ],
                "should": [
                  {
                    "match": {
                      "has_image": {
                        "query": 1,
                        "boost": 100
                      }
                    }
                  }
                ]
              }
            }
          ],
          "minimum_should_match": 1
        }
      }    
    }
  }
}

In pseudo-SQL:

SELECT * FROM /test/object
WHERE 
    ((name=foo AND name=bar) OR (info=foo AND info=bar))
AND state=1

Please keep in mind that it depends on your document field analysis and mappings how name=foo is internally handled. This can vary from a fuzzy to strict behavior.

"minimum_should_match": 1 says, that at least one of the should statements must be true.

This statements means that whenever there is a document in the resultset that contains has_image:1 it is boosted by factor 100. This changes result ordering.

"should": [
  {
    "match": {
      "has_image": {
        "query": 1,
        "boost": 100
      }
    }
   }
 ]

Have fun guys :)