Proactive approach to tuning

Typically you will create an index for the most selective columns and create statistics for the least selective columns in a query. By creating an index, the optimizer knows that the column is selective and it also gives the optimizer the ability to use that index to implement the query.

In a perfect radix index, the order of the columns is important. In fact, it can make a difference as to whether the optimizer uses it for data retrieval at all. As a general rule, order the columns in an index in the following way:

Equal predicates first. That is, any predicate that uses the "=" operator may narrow down the range of rows the fastest and should therefore be first in the index.
If all predicates have an equal operator, then order the columns as follows:
- Selection predicates + join predicates
- Join predicates + selection predicates
- Selection predicates + group by columns
- Selection predicates + order by columns

In addition to the guidelines above, in general, the most selective key columns should be placed first in the index.

Consider the following SQL statement:

SELECT b.col1, b.col2, a.col1
   FROM table1 a, table2 b
   WHERE b.col1='some_value' AND
     b.col2=some_number AND
     a.join_col=b.join_col
   GROUP BY b.col1, b.col2, a.col1
   ORDER BY b.col1

With a query like this, the proactive index creation process can begin. The basic rules are:

Custom-build a radix index for the largest or most commonly used queries. Example using the query above:

radix index over join column(s) - a.join_col and b.join_col 
radix index over most commonly used local 	selection column(s) - b.col2

For ad hoc online analytical processing (OLAP) environments or less frequently used queries, build single-key EVIs over the local selection column(s) used in the queries. Example using the query above:
```
 EVI over non-unique local selection columns - b.col1 and b.col2
```