我想知道这在SQL中是否可行。假设你有两个表A和B,你在表A上做一个选择,在表B上做一个连接:

SELECT a.*, b.* FROM TABLE_A a JOIN TABLE_B b USING (some_id);

如果表A有“a_id”、“name”、“some_id”列,表B有“b_id”、“name”、“some_id”列,查询将返回“a_id”、“name”、“some_id”、“b_id”、“name”、“some_id”列。有什么方法可以为表B的列名加上前缀而不单独列出每一列吗?等价于这个:

SELECT a.*, b.b_id as 'b.b_id', b.name as 'b.name', b.some_id as 'b.some_id'
FROM TABLE_A a JOIN TABLE_B b USING (some_id);

但是,如前所述,没有列出每一列,所以像这样:

SELECT a.*, b.* as 'b.*'
FROM TABLE_A a JOIN TABLE_B b USING (some_id);

基本上就是说,“用‘something’为b.*返回的每一列添加前缀”。这可能吗,还是我运气不好?

编辑

关于不使用SELECT *等的建议是有效的建议,但与我的上下文无关,因此请关注眼前的问题——是否可以在连接中为表的所有列名添加前缀(SQL查询中指定的常量)?

我的最终目标是能够通过连接对两个表执行SELECT *操作,并且能够从结果集中获得的列的名称中分辨出哪些列来自表a,哪些列来自表b。同样,我不想单独列出列,我需要能够执行SELECT *操作。


当前回答

或者你可以使用Red Gate SQL Refactor或SQL Prompt,它通过单击Tab按钮将SELECT *展开为列列表

所以在你的例子中,如果你输入SELECT * FROM A JOIN B… 转到*的末尾,Tab键,瞧!你会看到 选择a . columnn1, A.column2, ...., B. columnn1, B.column2 FROM A JOIN

但它不是免费的

其他回答

不同的数据库产品会给你不同的答案;但如果你走得太远,你是在自讨苦吃。您最好选择您想要的列,并为它们提供自己的别名,以便每个列的标识非常清晰,并且可以在结果中区分它们。

对此没有SQL标准。

然而,通过代码生成(在表创建或修改或运行时按需生成),你可以很容易地做到这一点:

CREATE TABLE [dbo].[stackoverflow_329931_a](
    [id] [int] IDENTITY(1,1) NOT NULL,
    [col2] [nchar](10) NULL,
    [col3] [nchar](10) NULL,
    [col4] [nchar](10) NULL,
 CONSTRAINT [PK_stackoverflow_329931_a] PRIMARY KEY CLUSTERED 
(
    [id] ASC
)WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]
) ON [PRIMARY]

CREATE TABLE [dbo].[stackoverflow_329931_b](
    [id] [int] IDENTITY(1,1) NOT NULL,
    [col2] [nchar](10) NULL,
    [col3] [nchar](10) NULL,
    [col4] [nchar](10) NULL,
 CONSTRAINT [PK_stackoverflow_329931_b] PRIMARY KEY CLUSTERED 
(
    [id] ASC
)WITH (PAD_INDEX  = OFF, STATISTICS_NORECOMPUTE  = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS  = ON, ALLOW_PAGE_LOCKS  = ON) ON [PRIMARY]
) ON [PRIMARY]

DECLARE @table1_name AS varchar(255)
DECLARE @table1_prefix AS varchar(255)
DECLARE @table2_name AS varchar(255)
DECLARE @table2_prefix AS varchar(255)
DECLARE @join_condition AS varchar(255)
SET @table1_name = 'stackoverflow_329931_a'
SET @table1_prefix = 'a_'
SET @table2_name = 'stackoverflow_329931_b'
SET @table2_prefix = 'b_'
SET @join_condition = 'a.[id] = b.[id]'

DECLARE @CRLF AS varchar(2)
SET @CRLF = CHAR(13) + CHAR(10)

DECLARE @a_columnlist AS varchar(MAX)
DECLARE @b_columnlist AS varchar(MAX)
DECLARE @sql AS varchar(MAX)

SELECT @a_columnlist = COALESCE(@a_columnlist + @CRLF + ',', '') + 'a.[' + COLUMN_NAME + '] AS [' + @table1_prefix + COLUMN_NAME + ']'
FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_NAME = @table1_name
ORDER BY ORDINAL_POSITION

SELECT @b_columnlist = COALESCE(@b_columnlist + @CRLF + ',', '') + 'b.[' + COLUMN_NAME + '] AS [' + @table2_prefix + COLUMN_NAME + ']'
FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_NAME = @table2_name
ORDER BY ORDINAL_POSITION

SET @sql = 'SELECT ' + @a_columnlist + '
,' + @b_columnlist + '
FROM [' + @table1_name + '] AS a
INNER JOIN [' + @table2_name + '] AS b
ON (' + @join_condition + ')'

PRINT @sql
-- EXEC (@sql)

这个问题在实践中很有用。在软件编程中,只需要列出所有显式列,在这些列中,您需要特别小心地处理所有条件。

想象一下,当调试或尝试使用DBMS作为日常办公工具,而不是特定程序员的抽象底层基础设施的可变实现时,我们需要编写大量的sql。这种场景随处可见,比如数据库转换、迁移、管理等。这些sql大多只执行一次,不会再使用,给每个列名只是浪费时间。不要忘记SQL的发明不仅仅是为程序员使用的。

通常我会创建一个带列名前缀的实用程序视图,这里是pl/pgsql中的函数,这并不容易,但你可以将它转换为其他过程语言。

-- Create alias-view for specific table.

create or replace function mkaview(schema varchar, tab varchar, prefix varchar)
    returns table(orig varchar, alias varchar) as $$
declare
    qtab varchar;
    qview varchar;
    qcol varchar;
    qacol varchar;
    v record;
    sql varchar;
    len int;
begin
    qtab := '"' || schema || '"."' || tab || '"';
    qview := '"' || schema || '"."av' || prefix || tab || '"';
    sql := 'create view ' || qview || ' as select';

    for v in select * from information_schema.columns
            where table_schema = schema and table_name = tab
    loop
        qcol := '"' || v.column_name || '"';
        qacol := '"' || prefix || v.column_name || '"';

        sql := sql || ' ' || qcol || ' as ' || qacol;
        sql := sql || ', ';

        return query select qcol::varchar, qacol::varchar;
    end loop;

    len := length(sql);
    sql := left(sql, len - 2); -- trim the trailing ', '.
    sql := sql || ' from ' || qtab;

    raise info 'Execute SQL: %', sql;
    execute sql;
end
$$ language plpgsql;

例子:

-- This will create a view "avp_person" with "p_" prefix to all column names.
select * from mkaview('public', 'person', 'p_');

select * from avp_person;

我完全理解为什么这是必要的——至少对我来说,在快速创建原型时,有很多表需要连接,包括许多内部连接,这很方便。只要一个列名在第二个joinedtable中是相同的。*"字段通配符,主表的字段值将被joinedtable值覆盖。容易出错,令人沮丧和违反DRY时,必须手动指定表字段与别名一遍又一遍…

下面是一个PHP (Wordpress)函数,通过代码生成以及如何使用它的示例来实现这一点。在本例中,它用于快速生成一个自定义查询,该查询将提供通过高级自定义fields字段引用的相关wordpress帖子的字段。

function prefixed_table_fields_wildcard($table, $alias)
{
    global $wpdb;
    $columns = $wpdb->get_results("SHOW COLUMNS FROM $table", ARRAY_A);

    $field_names = array();
    foreach ($columns as $column)
    {
        $field_names[] = $column["Field"];
    }
    $prefixed = array();
    foreach ($field_names as $field_name)
    {
        $prefixed[] = "`{$alias}`.`{$field_name}` AS `{$alias}.{$field_name}`";
    }

    return implode(", ", $prefixed);
}

function test_prefixed_table_fields_wildcard()
{
    global $wpdb;

    $query = "
    SELECT
        " . prefixed_table_fields_wildcard($wpdb->posts, 'campaigns') . ",
        " . prefixed_table_fields_wildcard($wpdb->posts, 'venues') . "
        FROM $wpdb->posts AS campaigns
    LEFT JOIN $wpdb->postmeta meta1 ON (meta1.meta_key = 'venue' AND campaigns.ID = meta1.post_id)
    LEFT JOIN $wpdb->posts venues ON (venues.post_status = 'publish' AND venues.post_type = 'venue' AND venues.ID = meta1.meta_value)
    WHERE 1
    AND campaigns.post_status = 'publish'
    AND campaigns.post_type = 'campaign'
    LIMIT 1
    ";

    echo "<pre>$query</pre>";

    $posts = $wpdb->get_results($query, OBJECT);

    echo "<pre>";
    print_r($posts);
    echo "</pre>";
}

输出:

SELECT
    `campaigns`.`ID` AS `campaigns.ID`, `campaigns`.`post_author` AS `campaigns.post_author`, `campaigns`.`post_date` AS `campaigns.post_date`, `campaigns`.`post_date_gmt` AS `campaigns.post_date_gmt`, `campaigns`.`post_content` AS `campaigns.post_content`, `campaigns`.`post_title` AS `campaigns.post_title`, `campaigns`.`post_excerpt` AS `campaigns.post_excerpt`, `campaigns`.`post_status` AS `campaigns.post_status`, `campaigns`.`comment_status` AS `campaigns.comment_status`, `campaigns`.`ping_status` AS `campaigns.ping_status`, `campaigns`.`post_password` AS `campaigns.post_password`, `campaigns`.`post_name` AS `campaigns.post_name`, `campaigns`.`to_ping` AS `campaigns.to_ping`, `campaigns`.`pinged` AS `campaigns.pinged`, `campaigns`.`post_modified` AS `campaigns.post_modified`, `campaigns`.`post_modified_gmt` AS `campaigns.post_modified_gmt`, `campaigns`.`post_content_filtered` AS `campaigns.post_content_filtered`, `campaigns`.`post_parent` AS `campaigns.post_parent`, `campaigns`.`guid` AS `campaigns.guid`, `campaigns`.`menu_order` AS `campaigns.menu_order`, `campaigns`.`post_type` AS `campaigns.post_type`, `campaigns`.`post_mime_type` AS `campaigns.post_mime_type`, `campaigns`.`comment_count` AS `campaigns.comment_count`,
    `venues`.`ID` AS `venues.ID`, `venues`.`post_author` AS `venues.post_author`, `venues`.`post_date` AS `venues.post_date`, `venues`.`post_date_gmt` AS `venues.post_date_gmt`, `venues`.`post_content` AS `venues.post_content`, `venues`.`post_title` AS `venues.post_title`, `venues`.`post_excerpt` AS `venues.post_excerpt`, `venues`.`post_status` AS `venues.post_status`, `venues`.`comment_status` AS `venues.comment_status`, `venues`.`ping_status` AS `venues.ping_status`, `venues`.`post_password` AS `venues.post_password`, `venues`.`post_name` AS `venues.post_name`, `venues`.`to_ping` AS `venues.to_ping`, `venues`.`pinged` AS `venues.pinged`, `venues`.`post_modified` AS `venues.post_modified`, `venues`.`post_modified_gmt` AS `venues.post_modified_gmt`, `venues`.`post_content_filtered` AS `venues.post_content_filtered`, `venues`.`post_parent` AS `venues.post_parent`, `venues`.`guid` AS `venues.guid`, `venues`.`menu_order` AS `venues.menu_order`, `venues`.`post_type` AS `venues.post_type`, `venues`.`post_mime_type` AS `venues.post_mime_type`, `venues`.`comment_count` AS `venues.comment_count`
    FROM wp_posts AS campaigns
LEFT JOIN wp_postmeta meta1 ON (meta1.meta_key = 'venue' AND campaigns.ID = meta1.post_id)
LEFT JOIN wp_posts venues ON (venues.post_status = 'publish' AND venues.post_type = 'venue' AND venues.ID = meta1.meta_value)
WHERE 1
AND campaigns.post_status = 'publish'
AND campaigns.post_type = 'campaign'
LIMIT 1

Array
(
    [0] => stdClass Object
        (
            [campaigns.ID] => 33
            [campaigns.post_author] => 2
            [campaigns.post_date] => 2012-01-16 19:19:10
            [campaigns.post_date_gmt] => 2012-01-16 19:19:10
            [campaigns.post_content] => Lorem ipsum
            [campaigns.post_title] => Lorem ipsum
            [campaigns.post_excerpt] => 
            [campaigns.post_status] => publish
            [campaigns.comment_status] => closed
            [campaigns.ping_status] => closed
            [campaigns.post_password] => 
            [campaigns.post_name] => lorem-ipsum
            [campaigns.to_ping] => 
            [campaigns.pinged] => 
            [campaigns.post_modified] => 2012-01-16 21:01:55
            [campaigns.post_modified_gmt] => 2012-01-16 21:01:55
            [campaigns.post_content_filtered] => 
            [campaigns.post_parent] => 0
            [campaigns.guid] => http://example.com/?p=33
            [campaigns.menu_order] => 0
            [campaigns.post_type] => campaign
            [campaigns.post_mime_type] => 
            [campaigns.comment_count] => 0
            [venues.ID] => 84
            [venues.post_author] => 2
            [venues.post_date] => 2012-01-16 20:12:05
            [venues.post_date_gmt] => 2012-01-16 20:12:05
            [venues.post_content] => Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
            [venues.post_title] => Lorem ipsum venue
            [venues.post_excerpt] => 
            [venues.post_status] => publish
            [venues.comment_status] => closed
            [venues.ping_status] => closed
            [venues.post_password] => 
            [venues.post_name] => lorem-ipsum-venue
            [venues.to_ping] => 
            [venues.pinged] => 
            [venues.post_modified] => 2012-01-16 20:53:37
            [venues.post_modified_gmt] => 2012-01-16 20:53:37
            [venues.post_content_filtered] => 
            [venues.post_parent] => 0
            [venues.guid] => http://example.com/?p=84
            [venues.menu_order] => 0
            [venues.post_type] => venue
            [venues.post_mime_type] => 
            [venues.comment_count] => 0
        )
)

最近在NodeJS和Postgres中遇到了这个问题。

ES6方法

我知道没有任何RDBMS特性提供这种功能,所以我创建了一个包含我所有字段的对象,例如:

const schema = { columns: ['id','another_column','yet_another_column'] }

定义了一个reducer将字符串与表名连接在一起:

const prefix = (table, columns) => columns.reduce((previous, column) => {
  previous.push(table + '.' + column + ' AS ' + table + '_' + column);
  return previous;
}, []);

这将返回一个字符串数组。为每个表调用它并合并结果:

const columns_joined = [...prefix('tab1',schema.columns), ...prefix('tab2',schema.columns)];

输出最后的SQL语句:

console.log('SELECT ' + columns_joined.join(',') + ' FROM tab1, tab2 WHERE tab1.id = tab2.id');