Whats the best way to query exact match and full text at the same time?

Elastic Stack Elasticsearch
1

Hi all,

I had an ES search running on ES 2 that was working as I hoped but since upgrading to ES5 and subsequently to ES 6 the relevance has degraded somewhat (probably due to poor DSL I guess). Its just a shame that it was working nicely and now isn't.

So we have a number of documents that contain some codes such as '1/2' or '000045/000009' as well lots of bespoke screen text (from a third party application).

We have a single 'search everything' input box and go button, a la Google, which has stopped providing the relevance we got used to with ES2.

As part of the upgrade we changed the Code field to be stored as a keyword and the screen text is still stored as text (there's a lot of this; lots of names and addresses mostly, amongst other types of data).

I was hoping someone might be able to help shed light on why the query below isn't returning a document with a code exactly matching '1/2' as the first hit? I get about 140 hits before it where the is a number 1 or 2 somewhere on a piece of screen data..?

{
  "query": {
    "bool": {
      "filter": [
        {
          "terms": {
            "systemId": [
              1,
              2
            ]
          }
        }
      ],
      "minimum_should_match": 1,
      "should": [
        {
          "multi_match": {
            "fields": [
              "code",
              "code.standard",
              "name",
              "notes",
              "notes.english",
              "shortName"
            ],
            "query": "1/2",
            "type": "best_fields"
          }
        },
        {
          "nested": {
            "path": "matterKeyDates",
            "query": {
              "multi_match": {
                "fields": [
                  "matterKeyDates.notes",
                  "matterKeyDates.notes.english"
                ],
                "query": "1/2",
                "type": "best_fields"
              }
            }
          }
        },
        {
          "nested": {
            "path": "screenData",
            "query": {
              "multi_match": {
                "fields": [
                  "screenData.valueString",
                  "screenData.valueString.english"
                ],
                "query": "1/2",
                "type": "best_fields"
              }
            }
          }
        }
      ]
    }
  },
  "size": 10,
  "_source": {
    "excludes": [
      "screenData.*"
    ]
  }
}

Any help appreciated ... :smile:

2

So I thought I'd expand the problem with a replication script...

PUT tests

PUT tests/test/_mapping
{
  "test" : {
    "dynamic" : "false",
    "date_detection" : false,
    "numeric_detection" : false,
    "properties" : {
      "code" : {
        "type" : "keyword"
        },
        "screenData" : {
          "type" : "nested",
          "dynamic" : "false",
          "properties" : {
            "valueString" : {
              "type" : "text"
          }
        }
      }
    }
  }
}

PUT tests/test/1
{
  "code": "1/1",
  "screenData": [
    {
    "valueString": "1 smith road"
    },
    {
    "valueString": "2 smith road"
    }
  ]
}
PUT tests/test/2
{
  "code": "1/2",
  "screenData": [
    {
    "valueString": "3 smith road"
    },
    {
    "valueString": "4 smith road"
    }
  ]
}

GET tests/_search
{
      "query": {
        "bool": {
          "minimum_should_match": 1,
          "should": [
            {
              "multi_match": {
                "fields": [
                  "code"
                ],
                "query": "1/2"
              }
            },
            {
              "nested": {
                "path": "screenData",
                "query": {
                  "multi_match": {
                    "fields": [
                      "screenData.valueString",
                      "screenData.valueString.english"
                    ],
                    "query": "1/2"
                  }
                }
              }
            }
          ]
        }
      },
      "size": 10,
      "_source": {
        "excludes": [
          "screenData.*"
        ]
      }
    }

In this example document 2 scores higher than document 1. I would expect the keyword exact match to score higher than hits on the screenData..

I'd prefer to not start boosting here and there and am sure there should be a way to better write the query to ensure exact matches on keywords score higher than full text matches.

Any ideas?

3

You can use this in your query to look at the details of scores:

   "explain": true,

Using that I can see that doc 1 scores highly because it matches two tokens 1 and 2 whereas document 2 only matches one token 1/2. All tokens are of equal rarity and therefore value.

The solution is not for me to recommend a fix for this single scenario. You need to come up with a search template for handling user input that performs well across a whole range of queries. What fixes one query may be detrimental to many others.
Querying across multiple fields is one of the more complex things to get right in a search application and whole books have been written on the subject. The explain feature is your friend on this journey

4

Thanks Mark

5

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