Note : – If there are queries that return slowly from the underlying databases, then you can capture the SQL statements for the queries in the query log and provide them to the database administrator (DBA) for analysis. Usually DBA are able to fix performance issues. But let me summarizes methods that you can use to improve query performance:
- Table Indexes : It is very import for underlying table or tables to have indexes. There are different types of indexes E.g. (Primary Key, Bitmap, and Composite), make sure to use them properly. Indexes can become invalid for many reasons, make sure to check them on regular bases. It’s a big topic and I am planning to write a blog about Indexes in Data Warehouse in details.
- Table Partitions : if table is big and contain a lot of rows, you can improve OBIEE query performance by partitioning underlying table(s). There are many types to partitions in Oracle like range, hash and interval, make sure to use them properly.
- Table Join : There are different type of join in Oracle (Hash Join, Nested Loop Join), I have personally drastic performance different using different type of join.
- Avoid Disk Sorts : SQL statement execution can create sort activity, especially if you are using Oracle aggregate functions. Check if query is doing Disk Sort and find a way to avoid disk sorts.
- SQL HINT(s) : Sometime query don’t get best execution plan from optimizer and you can use SQL hints to enforce optimum execution plan in Oracle.
- Aggregate Tables : It is extremely important to use aggregate tables to improve query performance. Aggregate tables contain precalculated summarizations of data. It is much faster to retrieve an answer from an aggregate table than to recompute the answer from thousands of rows of detail.
- Database Cache : There are different types of caching technique in Oracle like result cache, database cache and Exadata Flash Cache. Caching can significantly improve query performance , use them properly.
- OBIEE Caching : The Oracle BI Server can store query results for reuse by subsequent queries. Query caching can dramatically improve the apparent performance of the system for users, particularly for commonly used dashboards, but it does not improve performance for most ad-hoc analysis.