# groonga - An open-source fulltext search engine and column store.

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# 8.11.8. query

## 8.11.8.1. Summary

`query` provides `--match_columns` and `--query` parameters of select feature as function. You can specify multiple `query` functions in `--filter` parameter in select.

Because of such flexibility, you can control full text search behavior by combination of multiple `query` functions.

`query` can be used in only `--filter` in select.

## 8.11.8.2. Syntax

`query` requires two arguments - `match_columns` and `query_string`.

The parameter `query_expander` or `substitution_table` is optional.

    query(match_columns, query_string)
    query(match_columns, query_string, query_expander)
    query(match_columns, query_string, substitution_table)

## 8.11.8.3. Usage

Here are a schema definition and sample data to show usage.

Sample schema:

Execution example:

    table_create Documents TABLE_NO_KEY
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    column_create Documents content COLUMN_SCALAR Text
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    table_create Terms TABLE_PAT_KEY|KEY_NORMALIZE ShortText --default_tokenizer TokenBigram
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    column_create Terms documents_content_index COLUMN_INDEX|WITH_POSITION Documents content
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    table_create Users TABLE_NO_KEY
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    column_create Users name COLUMN_SCALAR ShortText
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    column_create Users memo COLUMN_SCALAR ShortText
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    table_create Lexicon TABLE_HASH_KEY ShortText \
      --default_tokenizer TokenBigramSplitSymbolAlphaDigit \
      --normalizer NormalizerAuto
    column_create Lexicon users_name COLUMN_INDEX|WITH_POSITION Users name
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    column_create Lexicon users_memo COLUMN_INDEX|WITH_POSITION Users memo
    # [[0, 1337566253.89858, 0.000355720520019531], true]

Sample data:

Execution example:

    load --table Users
    [
    {"name": "Alice", "memo": "groonga user"},
    {"name": "Alisa", "memo": "mroonga user"},
    {"name": "Bob",   "memo": "rroonga user"},
    {"name": "Tom",   "memo": "nroonga user"},
    {"name": "Tobby", "memo": "groonga and mroonga user. mroonga is ..."},
    ]
    # [[0, 1337566253.89858, 0.000355720520019531], true]
    # [[0, 1337566253.89858, 0.000355720520019531], 5]

Here is the simple usage of `query` function which execute full text search by keyword 'alice' without using `--match_columns` and `--query` arguments in `--filter`.

Execution example:

    select Users --output_columns name,_score --filter 'query("name * 10", "alice")'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "name",
    #           "ShortText"
    #         ],
    #         [
    #           "_score",
    #           "Int32"
    #         ]
    #       ],
    #       [
    #         "Alice",
    #         10
    #       ]
    #     ]
    #   ]
    # ]

When executing above query, the keyword 'alice' is weighted to the value - '10'.

Here are the contrasting examples with/without `query`.

Execution example:

    select Users --output_columns name,memo,_score --match_columns "memo * 10" --query "memo:@groonga OR memo:@mroonga OR memo:@user" --sortby -_score
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         5
    #       ],
    #       [
    #         [
    #           "name",
    #           "ShortText"
    #         ],
    #         [
    #           "memo",
    #           "ShortText"
    #         ],
    #         [
    #           "_score",
    #           "Int32"
    #         ]
    #       ],
    #       [
    #         "Tobby",
    #         "groonga and mroonga user. mroonga is ...",
    #         4
    #       ],
    #       [
    #         "Alice",
    #         "groonga user",
    #         2
    #       ],
    #       [
    #         "Alisa",
    #         "mroonga user",
    #         2
    #       ],
    #       [
    #         "Bob",
    #         "rroonga user",
    #         1
    #       ],
    #       [
    #         "Tom",
    #         "nroonga user",
    #         1
    #       ]
    #     ]
    #   ]
    # ]

In this case, the keywords 'groonga' and 'mroonga' and 'user' are given same weight value. You can't pass different weight value to each keyword in this way.

Execution example:

    select Users --output_columns name,memo,_score --filter 'query("memo * 10", "groonga") || query("memo * 20", "mroonga") || query("memo * 1", "user")' --sortby -_score
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         5
    #       ],
    #       [
    #         [
    #           "name",
    #           "ShortText"
    #         ],
    #         [
    #           "memo",
    #           "ShortText"
    #         ],
    #         [
    #           "_score",
    #           "Int32"
    #         ]
    #       ],
    #       [
    #         "Tobby",
    #         "groonga and mroonga user. mroonga is ...",
    #         51
    #       ],
    #       [
    #         "Alisa",
    #         "mroonga user",
    #         21
    #       ],
    #       [
    #         "Alice",
    #         "groonga user",
    #         11
    #       ],
    #       [
    #         "Tom",
    #         "nroonga user",
    #         1
    #       ],
    #       [
    #         "Bob",
    #         "rroonga user",
    #         1
    #       ]
    #     ]
    #   ]
    # ]

On the other hand, by specifying multiple `query`, the keywords 'groonga' and 'mroonga' and 'user' are given different value of weight.

As a result, you can control full text search result by giving different weight to the keywords on your purpose.

## 8.11.8.4. Parameters

### 8.11.8.4.1. Required parameter

There are two required parameter, `match_columns` and `query_string`.

#### 8.11.8.4.1.1. `match_columns`

It specifies the default target column for fulltext search by `query_string` parameter value. It is the same role as match_columns parameter in `select`.

#### 8.11.8.4.1.2. `query_string`

It specifies the search condition in Query syntax. It is the same role as `query` parameter in `select`.

See match_columns about `query` parameter in `select`.

### 8.11.8.4.2. Optional parameter

There are some optional parameters.

#### 8.11.8.4.2.1. `query_expander`

It specifies the plugin name for query expansion.

There is one plugin bundled in official release - QueryExpanderTSV.

See QueryExpanderTSV about details.

#### 8.11.8.4.2.2. `substitution_table`

It specifies the substitution table and substitution column name by following format such as `${TABLE}.${COLUMN}` for query expansion.

See query_expander about details.

## 8.11.8.5. Return value

`query` returns whether any record is matched or not. If one or more records are matched, it returns `true`. Otherwise, it returns `false`.

## 8.11.8.6. TODO

- Support query_flags

## 8.11.8.7. See also

- select