Oracle database - Table Partitioning and Indexing

Oracle Database is a powerful and versatile platform for managing vast amounts of data. While techniques like table partitioning and compression are essential for optimal performance, there’s a wealth of additional knowledge to explore. In this blog post, we’ll discuss a bit on partitioned tables, unpartitioned tables, indexing, and strategies to optimize the performance of an Oracle database.

1: Partitioned Tables vs. Unpartitioned Tables

1.1 Understanding Table Partitioning

In the world of Oracle Database, partitioning is a critical concept. It involves dividing a table into smaller, more manageable pieces called partitions. These partitions can be thought of as separate sub-tables, each containing a subset of the data. Here’s what you need to know:

• Definition: Table partitioning is the process of dividing a large table into smaller, more manageable pieces, called partitions, which can be individually managed and optimized.
• Benefits of Table Partitioning:
  • Improved Query Performance: Partition pruning allows Oracle to scan only relevant partitions when executing queries, resulting in faster query performance.
  • Easier Data Archiving: Partitioning simplifies the process of archiving or purging old data.
  • Enhanced Manageability: Individual partitions can be backed up or maintained separately.

1.2 Unpartitioned Tables

While partitioning offers many benefits, it’s not always the best solution. There are scenarios where unpartitioned tables are preferred:

• When to Use Unpartitioned Tables:
  • Small Tables: For small tables, the overhead of partitioning may not be justified.
  • No Clear Partitioning Key: If there is no natural or logical way to partition the data, unpartitioned tables are more appropriate.
• Comparison of Table Structures:
  • Partitioned Tables: Consist of multiple partitions, each with its data.
  • Unpartitioned Tables: Are a single, undivided structure.

Part 2: Details on Indexing for Both Table Types

2.1 Indexing Basics

Before delving into the specifics of indexing for partitioned and unpartitioned tables, let’s review some essential indexing concepts:

• What Are Indexes? Indexes are database structures that provide fast and efficient access to data in tables.
• Types of Indexes:
  • B-Tree Indexes: Commonly used for general-purpose indexing.
  • Bitmap Indexes: Efficient for columns with a low cardinality, such as gender or status.
  • Function-Based Indexes: Allow indexing on the result of a function.

2.2 Local Indexes

Local indexes are intimately tied to partitioned tables, and understanding how they work is crucial:

• Local Index Definition: A local index is an index that is partitioned in the same way as the underlying table. Each index partition corresponds to a table partition. This allows for more efficient maintenance and query performance, as each index partition only covers a subset of the data.
• Purpose and Structure: Local indexes are designed to enhance query performance on partitioned data. Each index partition covers a specific subset of the data, which makes queries more efficient.
• Creation and Maintenance: When you create a local index on a partitioned table, Oracle automatically creates an index partition for each table partition. The maintenance of these index partitions is closely tied to the maintenance of table partitions. When you add or drop partitions from the table, corresponding index partitions are added or dropped automatically.
• Partition-Wise Join: Partitioned tables and indexes can take advantage of partition-wise joins, which can significantly improve query performance when joining partitioned tables with partitioned indexes.

2.3 Global Indexes

Global indexes, as the name suggests, are not bound to the partitioning structure. Here’s what you should know:

• Global Index Definition: A global index is a single index structure that covers an entire unpartitioned table. Global indexes are not tied to the partitioning scheme of the table and cover the entire table’s data.
• Use Cases: Global indexes are typically used with unpartitioned tables where partitioning is not feasible or necessary.
• Creation and Maintenance: When you create a global index on an unpartitioned table, it is created as a single structure covering the entire table. Maintenance of global indexes is not as tightly integrated with table maintenance. Adding or dropping table partitions does not affect global indexes.
• Performance Implications: Global indexes can be less efficient for large tables in terms of maintenance and query performance, especially when dealing with partitioned data, as they may have to scan the entire index even if only a portion of the table is accessed.

Part 3: The Process of Index Creation

Understanding how indexes are created for partitioned and unpartitioned tables is essential for effective database management.

3.1 Index Creation for Partitioned Tables

When you create an index on a partitioned table, Oracle automatically handles various aspects of index creation:

• Step-by-Step Guide:
  1. Specify the index name and the column(s) to be indexed.
  2. Oracle creates an index partition for each table partition.
  3. Index maintenance is closely tied to table maintenance, with automatic addition or removal of index partitions when corresponding table partitions change.

3.2 Index Creation for Unpartitioned Tables

Index creation for unpartitioned tables follows a different process:

• Single Index Structure: A global index is created as a single index structure that covers the entire unpartitioned table.
• Maintenance Independence: Unlike local indexes, global indexes are not closely tied to table maintenance. Adding or dropping table partitions does not affect global indexes.

Part 4: Performance of Index Creation and Timing Differences

The time required for index creation can vary significantly between local and global indexes.

Local Index:

1. Partitioned Structure: Local indexes are partitioned, meaning they have a separate index structure for each partition of the table. If your partitioned table has many partitions, this can result in the creation of multiple index partitions.
2. Maintenance Overhead: When creating a local index, Oracle has to build and manage separate index structures for each partition. Additionally, maintenance operations such as adding or dropping partitions can also affect the corresponding index partitions. This adds to the time required for the index creation process.

Global Index:

1. Single Structure: Global indexes, on the other hand, are not partitioned and consist of a single index structure that covers the entire table.
2. Simpler Maintenance: Because global indexes do not have the complexity of partitioned structures, their creation and maintenance tend to be more straightforward and faster.

To address the slow performance of local index creation, you can consider the following options:

1. Parallel Index Creation: You can use Oracle’s parallel processing capabilities to speed up the creation of local indexes. This involves specifying the degree of parallelism for the index creation using the PARALLEL clause during index creation. This can significantly reduce the time it takes to build local indexes. For example:
   
   CREATE INDEX your_local_index ON your_partitioned_table(your_column) PARALLEL (DEGREE 4);
   
   
2. Use a Different Degree of Parallelism: Experiment with different degrees of parallelism to find the optimal setting for your environment. The ideal degree of parallelism will depend on your hardware, available system resources, and the nature of your data and workload.
3. Consider Index Compression: You can use index compression to reduce the size of the index, which can also improve index creation performance. Compression can be specified using the COMPRESS clause during index creation. For example:
   
   CREATE INDEX your_local_index ON your_partitioned_table(your_column) COMPRESS 2;
   
   
4. Review Hardware and Resources: Ensure that your hardware and system resources are sufficient to support the index creation process. Slow disk I/O or limited memory can significantly impact index creation performance.
5. Tune SQL Statements: If your partitioned table and index are part of a larger data warehousing or reporting system, consider optimizing the SQL statements that interact with the table and index to minimize the need for full scans.
6. Consider Using Global Indexes: If the performance requirements of your application allow for it, you can consider using global indexes if they meet your query performance needs. Global indexes are generally faster to create and maintain than local indexes for large partitioned tables.

Part 5: Other Considerations:

In addition to partitioning and compression, there are several other techniques and strategies you can employ to optimize the performance and manageability of your Oracle database. Here are some additional approaches you can consider:

1. Use Materialized Views: Materialized views are precomputed and stored result sets that can significantly improve query performance for frequently accessed data. They can be especially beneficial in data warehousing and reporting scenarios.
2. Optimize SQL Queries: Ensure that your SQL queries are well-written and tuned for performance. Properly designed queries, appropriate indexing, and the use of hints can make a significant difference in query response times.
3. Use Index-Organized Tables (IOTs): IOTs store data in a B-tree index structure. They are useful for small lookup tables or tables with unique key values, as they can reduce I/O overhead and improve query performance.
4. Histograms: Implement histograms for columns with skewed data distribution. Histograms provide more accurate statistics to the query optimizer, which can lead to better execution plans.
5. Use Advanced Query Optimization Features: Explore Oracle’s query optimization features, such as the use of SQL Plan Baselines, SQL Profiles, and Adaptive Query Optimization, to improve query performance.
6. Partitioning Exchange: You can use partition exchange to efficiently move data between a non-partitioned table and a partitioned table. This can be useful for data archiving and purging.
7. In-Memory Column Store: Oracle Database offers an In-Memory Column Store feature that allows you to store specific tables or table partitions in memory for faster query processing. This feature can be particularly effective for analytical workloads.
8. Database Tuning Advisor: Use the Database Tuning Advisor to analyze the database and recommend performance optimizations. It can provide recommendations for creating, dropping, or modifying indexes and materialized views.
9. Data Compression: Advanced Compression Options: In addition to basic table compression, Oracle offers advanced compression options like Exadata Hybrid Columnar Compression and Heat Map. These options provide more fine-grained control over data compression and storage.
10. Partition Pruning Techniques: Utilize partition pruning by specifying query predicates that allow Oracle to eliminate unnecessary partitions during query execution. This is crucial for improving query performance on partitioned tables.
11. Regular Database Maintenance: Schedule and perform regular database maintenance tasks, such as gathering statistics, rebuilding indexes, and monitoring system performance.
12. Oracle Database Options: Depending on your specific use case, you may benefit from additional Oracle Database options like Real Application Clusters (RAC), Active Data Guard, or Database In-Memory.
13. Database Monitoring Tools: Implement database monitoring and performance tuning tools, such as Oracle Enterprise Manager (OEM) or third-party solutions, to proactively identify and address performance issues.

Conclusion

There isn’t a single global option or, one-pill 💊 to improve performance of an oracle database, partitioning is just one of them. Various options must be considered and carefully analyzed based on the situation to see what option is the best.