sqlcheck

$ sqlcheck -h

Command line options : sqlcheck <options>
   -f --file_name          :  file name
   -r --risk_level         :  set of anti-patterns to check
                           :  1 (all anti-patterns, default) 
                           :  2 (only medium and high risk anti-patterns) 
                           :  3 (only high risk anti-patterns) 
   -c --color_mode         :  color mode 
   -v --verbose_mode       :  verbose mode

[examples/top_mutexes.sql]: (HIGH RISK) (QUERY ANTI-PATTERN) SELECT *

● Inefficiency in moving data to the consumer:

When you SELECT *, you're often retrieving more columns from the database than
your application really needs to function. This causes more data to move from
the database server to the client, slowing access and increasing load on your
machines, as well as taking more time to travel across the network. This is
especially true when someone adds new columns to underlying tables that didn't
exist and weren't needed when the original consumers coded their data access.   


● Indexing issues:

Consider a scenario where you want to tune a query to a high level of
performance. If you were to use *, and it returned more columns than you
actually needed, the server would often have to perform more expensive methods
to retrieve your data than it otherwise might. For example, you wouldn't be able
to create an index which simply covered the columns in your SELECT list, and
even if you did (including all columns [shudder]), the next developer who came around
and added a column to the underlying table would cause the optimizer to ignore
your optimized covering index, and you'd likely find that the performance of
your query would drop substantially for no readily apparent reason.    
[Matching Expression: select *]

[examples/top_mutexes.sql]: (LOW RISK) (QUERY ANTI-PATTERN) Spaghetti Query Alert   

● Split up a complex spaghetti query into several simpler queries:

SQL is a very expressive language—you can accomplish a lot in a single query
or statement. But that doesn't mean it's mandatory or even a good idea to
approach every task with the assumption it has to be done in one line of code.
One common unintended consequence of producing all your results in one query is
a Cartesian product. This happens when two of the tables in the query have no
condition restricting their relationship. Without such a restriction, the join
of two tables pairs each row in the first table to every row in the other table.
Each such pairing becomes a row of the result set, and you end up with many more
rows than you expect. 

It's important to consider that these queries are simply
hard to write, hard to modify, and hard to debug. You should expect to get
regular requests for incremental enhancements to your database applications.
Managers want more complex reports and more fields in a user interface. If you
design intricate, monolithic SQL queries, it's more costly and time-consuming to
make enhancements to them. Your time is worth something, both to you and to your
project. Split up a complex spaghetti query into several simpler queries. When
you split up a complex SQL query, the result may be many similar queries,
perhaps varying slightly depending on data values. Writing these queries is a
chore, so it's a good application of SQL code generation. Although SQL makes it
seem possible to solve a complex problem in a single line of code, don't be
tempted to build a house of cards.   

==================== Summary ===================   
All Anti-Patterns  :: 2   
>  High Risk   :: 1   
>  Medium Risk :: 0   
>  Low Risk    :: 1