7.15.21. query — Groonga v16.0.5 documentation

Skip to main content
`Ctrl`+`K`

# 7.15.21. `query`

## 7.15.21.1. 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.

## 7.15.21.2. Syntax

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

The parameter `query_expander` and `options` are optional:

    query(match_columns, query_string)
    query(match_columns, query_string, query_expander)
    query(match_columns, query_string, options)

`options` uses the following format. All of key-value pairs are optional:

    {
      "expander": query_expander,
      "default_mode": default_mode,
      "default_operator": default_operator,
      "flags": flags
    }

## 7.15.21.3. 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 ShortText --default_tokenizer TokenBigram  --normalizer NormalizerAuto
    # [[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
    # [[0,1337566253.89858,0.000355720520019531],true]
    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],5]

Here is the simple usage of `query` function which executes 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" --sort_keys -_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 all keywords `groonga`, `mroonga` and `user` use the default weight. 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")' --sort_keys -_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`, `mroonga` and `user` use different weight.

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

## 7.15.21.4. Parameters

### 7.15.21.4.1. Required parameters

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

#### 7.15.21.4.1.1. `match_columns`

Specifies the default target columns for full text search by `query_string` parameter value. It is the same role as match_columns parameter in `select`.

#### 7.15.21.4.1.2. `query_string`

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`.

### 7.15.21.4.2. Optional parameters

There are some optional parameters.

#### 7.15.21.4.2.1. `query_expander`

Specifies the query expander name or substitution column name for query expansion.

See Query expanders for available query expanders.

Substitution column name uses `${TABLE}.${COLUMN}` format.

See query_expander for details.

#### 7.15.21.4.2.2. `default_mode`

Specifies the default search mode. You can change search mode by `column:@keyword` like syntax. The default search mode is used when you just specify `keyword` instead of `column:@keyword`. See Query syntax for more syntax details.

Here are available modes. The default is `"MATCH"` mode. It does full text search.

Mode | Aliases | Description
--- | --- | ---
`"EQUAL"` | `"=="` | It uses Equal condition as the default mode.
`"NOT_EQUAL"` | `"!="` | It uses Not equal condition as the default mode.
`"LESS"` | `"<"` | It uses Less than condition as the default mode.
`"GREATER"` | `">"` | It uses Greater than condition as the default mode.
`"LESS_EQUAL"` | `"<="` | It uses Less than or equal to condition as the default mode.
`"GREATER_EQUAL"` | `">="` | It uses Greater than or equal to condition as the default mode.
`"MATCH"` | `"@"` | It uses Full text search condition as the default mode. It’s the default.
`"NEAR"` | `"*N"` | It uses Near search condition as the default mode.
`"SIMILAR"` | `"*S"` | It uses Similar search condition as the default mode.
`"PREFIX"` | `"^"`, `"@^"` | It uses Prefix search condition as the default mode.
`"SUFFIX"` | `"$"`, `"@$"` | It uses Suffix search condition as the default mode.
`"REGEXP"` | `"~"`, `"@~"` | It uses Regular expression condition as the default mode.

#### 7.15.21.4.2.3. `default_operator`

Specifies the default logical operator. It’s used when no logical operator such as `OR` and `-` are specified between conditional expressions like `keyword1 keyword2`. The default logical operator is used to combine `keyword1` result set and `keyword2` result set. The default logical operator is `AND`. So `keyword1 keyword2` result set includes only records that they are included in both `keyword1` result set and `keyword2` result set.

Here are available logical operators. The default is `"AND"`.

Logical operator | Aliases | Description
--- | --- | ---
`"AND"` | `"&&"`, `"+"` | It uses Logical AND as the default logical operator.
`"OR"` | `"||"` | It uses Logical OR as the default logical operator.
`"AND_NOT"` | `"&!"`, `"-"` | It uses Logical AND NOT as the default logical operator.

#### 7.15.21.4.2.4. `flags`

Specifies the flags that customizes how to parse query.

You can specify multiple flags by separating each flags by `|`. Here is the example to specify multiple flags:

    query("title * 10 || content",
          "keyword",
          {"flags": "ALLOW_COLUMN|ALLOW_LEADING_NOT"})

See query_flags for available flags.

## 7.15.21.5. Return value

This function returns whether a record is matched or not as boolean.

This function is also worked as a selector. It means that this function can be executable effectively.

## 7.15.21.6. See also

- select

- query_parallel_or