Oracle Query Optimizer Tool: Manipulating Index Spaces

Performance becomes a major issue in nearly every real-time production environment. Unlike configuration-related problems or bugs in Oracle, performance issues stem from poorly-designed statements or ill-suited execution plans. That’s why DBAs often end up looking for an Oracle query optimizer tool to improve database speed.

Before doing that, it is important to do an index scan as it helps for high cost-based statements in most cases. However, indexes may also need maintenance or be created again to overcome certain bottlenecks they can cause.

Improve Oracle Database Performance with the Right Index

The space allotted for tables is usually smaller than the space allocated for indexes because quick row access is crucial for acceptable response time. Let’s take a look at some types of indexe structures that help us achieve this:

 

●    The default index structure that Oracle always uses is the B-Tree - the standard since the earliest releases.

●  There is an alternative to B-Tree indexes - Bitmap indexes. These prove more useful in cases with low cardinality. This means a low number of distinct values in an index column, making it extremely quick for read-only databases.

●   Another type of index is the Bitmap join index. It is useful when data columns show in a multi-column index from multiple tables into a junction table.

How Indexes and an Oracle Query Optimizer Tool Help in Optimization

Aside from these various kinds of index structures, DBAs also find different uses for indexes at runtime. Consider some examples of index-based access plans to improve Oracle database performance that are given below:

●      The use of the index_combine hint for combined index access.

●  Scanning an index to gain access to a series of row ids using nested loop joins is a common optimization method.

●   Using index blocks through a database file scattered read helps place index blocks into the buffers. It is a quick full scan that doesn’t read the index nodes.

●     Implementing star joins enables very quick connections for big read-only data warehouse tables. It uses the star index that was earlier a single concatenated index that turned into a bitmap index implementation.

One of the most common questions new Database Administrators have to face is: where does one collect index information? The answer is an execution plan that also includes all object data that it can collect with the help of dba_or v$ views.

When a database professional has to examine indexes, they can view the statistics through the dba_indexes view. Although it is a source of a whole lot of necessary data for the Oracle query optimizer tool, there are a few details it misses.

There is an analyze index command that provides the additional information we need in the form of a temporary table known as index_stats. However, this information is temporary, so you will have to save it because every validate command overlays the data.

Sometimes, DBAs may have to reconstruct Oracle B-Tree indexes from time to time to improve Oracle database performance. Even though there are several thought-processes regarding their use, some experts say doing this results in proper space utilization. According to them, it also increases the rate at which the queries access data, while others believe this should rarely be done.

According to the recent developments, the AMT will look for indexes that require re-construction on its own. This proves the claims made by many experts in terms of performance improvement.