Composite Partitioning FAQS

1. What is Composite Partitioning in Oracle?

Answer: Composite partitioning is a technique where you combine two or more partitioning methods (like range, list, and hash partitioning) in a single table or index. It allows you to partition data by one method (e.g., range) and then further subpartition it using another method (e.g., hash or list) to optimize performance and data management.

2. Why would I use Composite Partitioning?

Answer: Composite partitioning is useful when:

• You want to combine the benefits of different partitioning methods.
• You have complex data access patterns that can't be optimized by a single partitioning method.
• You need to improve parallel query performance or distribute data more evenly across partitions.

3. What are the types of Composite Partitioning in Oracle?

Answer: The three main types of composite partitioning are:

• Range-Hash Partitioning: Combines range partitioning and hash partitioning. First, data is divided into ranges, and then each range is further distributed using hash partitioning.
• Range-List Partitioning: Combines range partitioning and list partitioning. Data is divided by ranges and then subpartitioned by specific values in a list.
• List-Hash Partitioning: Combines list partitioning and hash partitioning. First, data is divided into specific values (list), and then each list is further divided using hash partitioning.

4. Can I combine all three partitioning methods in Oracle?

Answer: No, you can only combine two partitioning methods at a time in Oracle. Composite partitioning is typically limited to two methods (e.g., range + hash or range + list). You cannot use all three methods together for a single table.

5. How does Range-Hash Partitioning work?

Answer: In Range-Hash Partitioning, the data is first divided into partitions based on a range (e.g., date or numerical range). Then, each range partition is further divided into multiple subpartitions using hash partitioning, which ensures an even distribution of data.

Example:

CREATE TABLE sales (

    sale_id NUMBER,

    sale_date DATE,

    amount NUMBER

)

PARTITION BY RANGE (sale_date)

SUBPARTITION BY HASH (sale_id)

SUBPARTITIONS 4;

6. What are the benefits of Composite Partitioning?

Answer:

• Better Data Distribution: Composite partitioning allows for more even distribution of data across partitions.
• Improved Query Performance: Different partitioning strategies optimize specific types of queries, improving overall performance.
• Parallelism: Helps in parallel query execution since different partitions or subpartitions can be processed concurrently.
• Flexibility: Allows fine-grained control over how data is partitioned based on access patterns.

7. How does Partition Pruning work in Composite Partitioning?

Answer: Partition pruning is more limited in composite partitioning compared to a single partitioning method. In range or list partitioning, partition pruning can be done based on the partition key. However, with composite partitioning (especially in range-hash or list-hash), pruning is less efficient because of the need to evaluate multiple partitioning methods. Query filters might need to scan multiple partitions or subpartitions.

8. Can I alter a composite partitioned table after creation?

Answer: Yes, you can modify the partitioning scheme of a table using the ALTER TABLE command. However, there are limitations. You cannot change the number of partitions or subpartitions directly. To modify the partitioning structure, you might need to recreate the table or use partition exchange methods.

9. Can I use indexes with composite partitioned tables?

Answer: Yes, you can create local or global indexes on composite partitioned tables:

• Local indexes: The index is partitioned the same way as the table. Each partition of the table has a corresponding partition in the index.
• Global indexes: The index is created over all partitions, and it spans the entire table. Global indexes may require extra maintenance during partition management (e.g., adding or dropping partitions).

10. Is Composite Partitioning suitable for all types of data?

Answer: Composite partitioning is particularly useful for large datasets with complex access patterns. It is best suited for situations where:

• Data has multiple attributes that can benefit from different partitioning methods.
• You need to ensure an even distribution of data, especially for parallel processing. However, for simpler datasets with a natural range or list-based access pattern, basic partitioning methods like range or list may be more appropriate.

11. How do I decide which partitioning strategy to use for composite partitioning?

Answer: The choice of partitioning strategy depends on the data access patterns and performance requirements:

• Use range partitioning if your data is naturally ordered by a range (e.g., time periods).
• Use list partitioning if your data can be grouped into predefined categories (e.g., regions, product types).
• Use hash partitioning if you need to ensure even distribution of data and workload across partitions (e.g., if the data distribution is skewed).

12. Can I use Composite Partitioning for time-series data?

Answer: Yes, range partitioning can be used for time-series data, such as partitioning by year, month, or day. To further balance the load, you can hash partition within each time range to evenly distribute data across partitions. This can be particularly helpful for large datasets where you want to optimize query performance and parallelism.

13. What are some common performance issues with Composite Partitioning?

Answer:

• Partition Pruning Limitations: Complex composite partitioning schemes may not allow effective pruning, leading to full-table scans or accessing multiple partitions unnecessarily.
• Overhead: The additional complexity of using multiple partitioning methods can introduce overhead, particularly in terms of storage and query optimization.
• Increased Maintenance Complexity: Composite partitioning can increase the complexity of managing partitions, especially when adding, dropping, or reorganizing partitions.

14. Can I mix different partitioning types within subpartitions?

Answer: No, Oracle only supports two-level composite partitioning. You can combine one partitioning method (e.g., range) with another subpartitioning method (e.g., hash or list), but you cannot mix more than two partitioning schemes in a single table.

15. Can I create composite partitioning on an existing table?

Answer: Yes, you can modify an existing table to use composite partitioning. However, Oracle does not allow directly altering a table’s partitioning strategy to composite partitioning. Instead, you would need to:

• Create a new table with the desired composite partitioning.
• Migrate the data from the old table to the new one.

16. How is data loaded into a composite partitioned table?

Answer: Data is loaded into the composite partitioned table based on the partitioning scheme:

• For range partitions, data is placed into partitions based on the range of the partition key (e.g., date or numeric).
• For list partitions, data is placed into predefined list partitions based on the list of values.
• For hash subpartitions, data is distributed evenly based on the hash value of the partition key.

17. How does composite partitioning help in parallelism?

Answer: Composite partitioning allows parallel execution of queries because partitions and subpartitions can be processed independently. For example, in range-hash partitioning, each range partition can be processed in parallel, and within each range, hash subpartitions can also be processed concurrently.