SQL select join: is it possible to prefix all columns as 'prefix.*'?

Question

It seems the answer to your question is no, however one hack you can use is to assign a dummy column to separate each new table. This works especially well if you're looping through a result set for a list of columns in a scripting language such as Python or PHP.

SELECT '' as table1_dummy, table1.*, '' as table2_dummy, table2.*, '' as table3_dummy, table3.* FROM table1
JOIN table2 ON table2.table1id = table1.id
JOIN table3 ON table3.table1id = table1.id

I realize this doesn't answer your question exactly, but if you're a coder this is a great way to separate tables with duplicate column names. Hope this helps somebody.

I see two possible situations here. First, you want to know if there is a SQL standard for this, that you can use in general regardless of the database. No, there is not. Second, you want to know with regard to a specific dbms product. Then you need to identify it. But I imagine the most likely answer is that you'll get back something like "a.id, b.id" since that's how you'd need to identify the columns in your SQL expression. And the easiest way to find out what the default is, is just to submit such a query and see what you get back. If you want to specify what prefix comes before the dot, you can use "SELECT * FROM a AS my_alias", for instance.

I totally understand why this is necessary - at least for me it's handy during rapid prototyping when there are a lot of tables necessary to be joined, including many inner joins. As soon as a column name is the same in a second "joinedtable.*" field wild card, the main table's field values are overriden with the joinedtable values. Error prone, frustrating and a violation of DRY when having to manually specify the table fields with aliases over and over...

Here is a PHP (Wordpress) function to achieve this through code generation together with an example of how to use it. In the example, it is used to rapidly generate a custom query that will provide the fields of a related wordpress post that was referenced through a advanced custom fields field.

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>";
}

The output:

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
        )
)

The only database I know that does this is SQLite, depending on the settings you configure with PRAGMA full_column_names and PRAGMA short_column_names. See http://www.sqlite.org/pragma.html

Otherwise all I can recommend is to fetch columns in a result set by ordinal position rather than by column name, if it's too much trouble for you to type the names of the columns in your query.

This is a good example of why it's bad practice to use SELECT * -- because eventually you'll have a need to type out all the column names anyway.

I understand the need to support columns that may change name or position, but using wildcards makes that harder, not easier.

This question is very useful in practice. It's only necessary to list every explicit columns in software programming, where you pay particular careful to deal with all conditions.

Imagine when debugging, or, try to use DBMS as daily office tool, instead of something alterable implementation of specific programmer's abstract underlying infrastructure, we need to code a lot of SQLs. The scenario can be found everywhere, like database conversion, migration, administration, etc. Most of these SQLs will be executed only once and never be used again, give the every column names is just waste of time. And don't forget the invention of SQL isn't only for the programmers use.

Usually I will create a utility view with column names prefixed, here is the function in pl/pgsql, it's not easy but you can convert it to other procedure languages.

-- 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;

Examples:

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

select * from avp_person;

I am in kind of the same boat as OP - I have dozens of fields from 3 different tables that I'm joining, some of which have the same name(ie. id, name, etc). I don't want to list each field, so my solution was to alias those fields that shared a name and use select * for those that have a unique name.

For example :

table a : id, name, field1, field2 ...

table b : id, name, field3, field4 ...

select a.id as aID, a.name as aName, a. * , b.id as bID, b.name as bName, b. * .....

When accessing the results I us the aliased names for these fields and ignore the "original" names.

Maybe not the best solution but it works for me....i'm use mysql