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SQL::Catalog - query queries, label queries, db independant SQL, separate Perl and SQL


 shell% cd sql_repository/city,date/weather/1/

 shell% cat concrete.sql 
 select city, date from weather where temp_lo < 20 and temp_hi > 40 LIMIT 10
 shell% sql_test concrete.sql 
 # see results of prepare, execute on this
 shell% cat concrete.sql._test

 shell% cat abstract.sql
 select city, date from weather where temp_lo < ? and temp_hi > ?
 # send in placeholder value
 shell% sql_test abstract.sql 55 
 # let's see results... looks good
 shell% cat abstract.sql._test

 shell% sql_register abstract.sql basic_weather "basic weather query"
 shell% cat abstract.sql._register
 [basic_weather] inserted as 
 [select city from weather where temp_lo < ? and temp_hi > ?]

 ... then in a Perl program (e.g. in this distribution)
 # Cache all queries to a Cache::Cache instead of runtime db-lookup
 % shell perl -MSQL::Catalog -e 'SQL::Catalog->spider'

 my $dbh = get_the_handle_as_you_please;
 my $sql = memory and in a large system memory is precious.
 my $sth = $dbh->prepare($sql);

 my $rows = $sth->rows;


Over time, it has become obvious that a few things about SQL queries are necessary. And before this module, time-consuming:

  • database independence

    You may at some time to be forced to deploy an application which has to work on more than one database. Prior to SQL::Catalog, there were two choices - DBIx::AnyDBD and DBIx::Recordset. SQL::Catalog will work well alongside the latter. And in fact, SQL::Catalog itself uses DBIx::AnyDBD.

    Note though that because some databases can do in one query what takes 4 in another (ie, Postgres has SELECT * FROM X INTO ...), you may have to create subclasses of your database layer classes to actually handle each needed function. This is what DBIx::AnyDBD handles for you.

  • labelled queries

    A large, well-scaled business database application has several layers with simple well-defined tasks. The layer just above the database does database things. It inserts. It retrieves. It updates. etc, etc. Call this the database application layer. Just above the database application layer is the business object layer. These are conceptual entities whose data structures are program data structures. For permanent stores, they make simple, technology-agnostic requests of the database application layer, which then takes the business data and stores it as database data. Then above this we have the application layer. And this layer makes use of business objects, ldap objects, web objects, what have you, to string together a complete application.

  • queryable queries

    That's right, you want to be able to query on the queries themselves. It makes it easy to do a study on just what queries are doing what.

  • separation of concerns

    By now, everyone has heard that phrase: "my templating module is the best because it allows the HTML designer to work separately from the Perl programmer." Well, given that databases are another foreign technology to Perl proper, it only makes sense that the same ability that is afforded to HTML designers be afforded to SQL programmers.

  • centralization of queries

    This makes it easy for someone to see how you did something so they can imitate.

  • memory preservation

    You may be sitting there thinking "this is no better than a Perl hashref". And if you are, then I congratulate you on making it to the 6th bulleted item instead of impatiently finding something else to do.

    Anyway, the problem with using a Perl hashref is that it will consume memory and in a large system memory is precious.

    Now you could go the way of tying hashrefs to disk, but then you don't get the querying capabilities with a Perl hashref that you get with logging your SQL in a database, so THERE... heheh.

SQL::Catalog addresses all of these issues.

Furthermore, you don't get the querying capabilities with a Perl hashref.

SQL::Catalog addresses all of these issues.


Develop your concrete query in a db shell

The first step to developing a database query is to play around at the db shell. In this case, you normally don't have any placeheld values. You just keep mucking with the query until it gives you what you want.

When you finally get what you want, save it in a file, say concrete.sql for example. Here is a concrete query:

 select city, date from weather where temp_hi > 20

Abstract your query with placeholders

Now it's time to make your query more abstract. So we do the following:

 select city, date from weather where temp_hi > ? 

and save in a different file, say abstract.sql.

Now let's test this query also, being sure to pass in data for the placeholder fields:

 sql_test abstract.sql 34

Certain drivers are not very good with their error messages in response to queries sent in without placeholder bindings, so take care here.

And let's cat testexec.out to see the results.

Register your query (store in the sql_category table)

 sql_register abstract.sql city_date_via_temp_hi

and the system tells you

 [city_date_via_temp_hi] saved as
 [select city, date from weather where temp_hi > ?] 

Use your query from DBI:

 use SQL::Catalog;

 my $dbh = SQL::Catalog->db_handle; # or however you get your DBI handles
 my $SQL = sql_lookup('city_date_via_temp_hi') or die "not found";
 my $sth = $dbh->prepare($SQL, $cgi->param('degrees'));
  .... etc


See the README in the home directory of the distribution.

What SQL::Catalog does

It stores each query in a database table with the label as key and the SQL query as the one value for that key. Then there is a foreign table with a number of useful query attributes such as type of query, tables and columns used and number of placeholders.

Right now we have schema creation and SQL code which works for MySQL (thanks to Jason W. May), Informix (thanks to Jonathan Leffler) and Postgresql (thanks to me, although I did use Marcel Grunaer's DBIx::Renderer to make it) and welcome more.

The queries are stored in these tables (this file is db-creation/postgresql.sql):

 CREATE TABLE sql_catalog (
        label varchar(80) ,
        cmd varchar(40) ,
        phold int4 ,
        author varchar(40) ,
        query varchar(65536) ,
        comments varchar(1600) ,
        PRIMARY KEY (label)
CREATE TABLE sql_catalog_ft (
        label_ft varchar(80) ,
        tbl varchar(255) ,
        col varchar(255) ,
        PRIMARY KEY (label_ft)

And here is the result of ONE sql_register:

 mydb=# select * from sql_catalog_ft;
 label_ft |   tbl   |   col   
 basic_weather     | weather | city
 basic_weather     | weather | date
 basic_weather     | weather | temp_lo
 basic_weather     | weather | temp_hi
 (4 rows)

 mydb=# select * from sql_catalog;
 label |  cmd   | phold |  author  |                                    query                                     | comments 
 basic_weather  | SELECT |     1 | metaperl | select city, date, temp_lo, temp_hi from weather where temp_lo < ? LIMIT 40
 | ahah
 (1 row)

Queries are only *stored* in the database, by calling SQL::Catalog-spider>, you can move them into main memory or a file cache or whatever other kind of cache that Cache::Cache supports.


  • Pleasing DBIx::AnyDBD

    DBIx::AnyDBD has this requirement that when searching for the implementation classes (e.g. Cannot find SQL/Catalog/ module! in /Users/metaperl/src/sql_catalog at /Users/metaperl/install/lib/site_perl/5.7.2/DBIx/ line 99.) that it uses the current working directory as the relative path.

    Unfortunately this means that when you run sql_test or sql_register that they must run from $dir such that load_module <$dir/> will find <SQL/Catalog/>.

  • Do NOT end your SQL statements for testing within this framework with a semicolon.

  • It is entirely feasible (and oh so cool), to have a "query server". Ie, a cheap Linux box running MySQL which has no table but sql_catalog on it. And all it does is serve the queries. Then your actual "data database" can be on a completely different machine. The idea is that SQL::Catalog connects to the table sql_catalog based on its DSN value (see README) while your data database connects based on a different DSN.

  • When dropping these tables, you will also have to drop one index


T. M. Brannon, <>

Substantial contribution (and ass-kicking) by Jonathan Leffler. MySQL table creation code contribution by Jason W. May.


There are several related modules on CPAN. Each do some of what SQL::Catalog does.

  • Ima::DBI provides an object-oriented interface to connection and sql management.

  • SQL::Library

  • Data::Phrasebook

  • DBIx::Librarian provides labelled access to queries and shortens the prepare-execute ritual a bit.

  • Class::Phrasebook::SQL stores a "phrasebook" of SQL in XML files. Allows for retrieval of queries via a convenient API. The querying of queries that SQL::Catalog supports can be done using an XML processor along with SQL::Statement.

  • DBIx::SearchProfiles. Does query labeling and also has some convenience functions for query retrieval. It does not store the SQL in a database or make it searchable by table, column, or number of placeholders. Your standard Perl data munging techniques would be the way to do statistical analysis of your queries.

  • Queries stored in Perl modules

    A different approach is suggested using Perl modules. Interesting idea.

  • "Leashing DBI"

    Various issues in building applications on top of DBI.