Understanding Oracle Indexes: Mastering Degree of Parallelism for Better Performance

Understanding Oracle Indexes and Degree of Parallelism

Oracle indexes play a crucial role in improving query performance by reducing the number of rows that need to be accessed during a query. One of the key parameters associated with an index is its degree of parallelism, which affects how many CPU cores can be utilized simultaneously while executing queries on that index.

In this article, we will delve into the world of Oracle indexes and explore how the degree of parallelism impacts database load. We’ll discuss what degree of parallelism means in the context of Oracle, and provide guidance on how to diagnose and resolve issues related to high loads caused by specific indexes.

What is Degree of Parallelism?

In Oracle, the degree of parallelism refers to the number of CPU cores that can be utilized simultaneously while executing a query. When you create an index with a certain degree of parallelism, Oracle knows that it needs to divide the workload among multiple CPU cores to take full advantage of that core count.

For example, if you have an 8-core CPU and you create an index with a degree of parallelism set to 4, Oracle will utilize all 4 cores for that specific index. This means that while one core is working on a certain portion of the index, another core can be used to work on a different portion of the same index.

How Does Degree of Parallelism Affect Database Load?

When you execute a query with an index, Oracle uses the degree of parallelism to determine how many CPU cores should be utilized. If the degree of parallelism is set too high, it can lead to over-subscription of CPU resources, resulting in increased load on the database.

In the scenario described in the Stack Overflow post, the customer has 4 RAC (Real Application Clusters) nodes with a total of 8 cores each, making a total of 32 CPU cores available. The index in question has a degree of parallelism set to 10, which means that Oracle will utilize up to 10 CPU cores for that specific index.

This high degree of parallelism can lead to several issues:

Over-subscription: With more CPU cores being utilized than are actually available, Oracle may resort to context switching between different processes, leading to increased context switch overhead.
Cache thrashing: When multiple threads contend for the same cache lines, it can result in reduced performance due to cache thrashing.
Increased load on Shared Pool: The Shared Pool is used by the database to store temporary data structures and results. When parallel queries are executed concurrently, they can increase the demand on the Shared Pool, leading to increased load and potential performance issues.

To diagnose issues related to high loads caused by specific indexes, you should consider the following:

Check Oracle statistics: Oracle provides detailed statistics about query execution, including the number of CPU cores utilized. You can check these statistics using the V$SESSTAT and V$SESSION views.
Verify index usage: Use the DBA_INDEXES view to verify which indexes are being used by your queries. You can also use the EXPLAIN PLAN command to see which indexes are being used for a specific query.
Check parallelism settings: Verify that the degree of parallelism is set correctly for each index. You can check this using the DBA_INDEXES view.

To resolve issues related to high loads caused by specific indexes, you can consider the following:

Reduce degree of parallelism: If the degree of parallelism is set too high, try reducing it to see if it improves performance.
Switch on Automatic Memory Management (AMM): AMM helps manage memory allocation and deallocation for database operations. Enabling AMM can help reduce the load caused by parallel queries.
Reduce parallelism of statistic gathering: Statistics gathering is an expensive operation that consumes CPU resources. Reducing the degree of parallelism for statistics gathering can help reduce the load on the database.

Best Practices

To avoid issues related to high loads caused by specific indexes, follow these best practices:

Monitor Oracle statistics regularly: Regularly check Oracle statistics to identify potential performance bottlenecks.
Use EXPLAIN PLAN: Use the EXPLAIN PLAN command to analyze query execution and identify which indexes are being used.
Adjust degree of parallelism correctly: Adjust the degree of parallelism for each index based on your workload and system resources.

Conclusion

In conclusion, understanding how Oracle indexes work is crucial to optimizing database performance. The degree of parallelism plays a significant role in determining how many CPU cores can be utilized simultaneously while executing queries on an index. By following best practices and adjusting the degree of parallelism correctly, you can minimize issues related to high loads caused by specific indexes.

Here are some additional code examples to help illustrate these concepts:

Example 1: Verifying Index Usage

-- Verify which indexes are being used for a specific query
EXPLAIN PLAN FOR SELECT * FROM table_name;

Example 2: Adjusting Degree of Parallelism

-- Reduce degree of parallelism for an index
ALTER INDEX idx_name ON table_name DROP PARALLEL;

-- Re-create the index with reduced degree of parallelism
CREATE INDEX idx_name ON table_name (column1, column2) PARALLEL (4);

Example 3: Monitoring Oracle Statistics

-- Check Oracle statistics to identify potential performance bottlenecks
SELECT * FROM V$SESSTAT WHERE name = 'direct reads';

By following these examples and best practices, you can optimize your database’s performance and minimize issues related to high loads caused by specific indexes.

Last modified on 2024-11-14