Oracle DBA

Sequences are a fundamental feature in Oracle databases, commonly used for generating unique identifiers such as primary keys. However, in a Real Application Clusters (RAC) environment, sequence behavior introduces certain performance and ordering challenges that require careful configuration. This blog provides insights into sequence configurations, gaps, and their performance impact in a RAC setup.

1. Sequence Setup Options

Oracle sequences offer different configuration options, each impacting performance and behavior differently:

a. CACHE + NOORDER (Default)

• Behavior: Each RAC instance caches distinct sets of numbers in the shared pool. Sequence numbers are not globally ordered.
• Performance Impact: Least impact on RAC performance due to reduced inter-instance communication.
• Consideration: Larger gaps may occur when the shared pool is refreshed (e.g., instance shutdown), similar to single-instance databases.

b. CACHE + ORDER

• Behavior: Each instance caches the same set of numbers, ensuring sequence numbers are globally ordered.
• Performance Impact: Better than NOCACHE sequences but introduces gaps when the shared pool is flushed or an instance shuts down.

c. NOCACHE + NOORDER

• Behavior: Sequence numbers are generated without caching, and global ordering is not guaranteed.
• Performance Impact: Higher than CACHE + NOORDER. Suitable for cases with legal requirements for minimal gaps.

d. NOCACHE + ORDER

• Behavior: Ensures globally ordered sequence numbers with no gaps (except during specific scenarios).
• Performance Impact: Highest performance overhead in RAC due to the need for inter-instance synchronization.

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2. Gaps in Sequences

Gaps can occur in sequences, even in non-RAC databases, under the following conditions:

• Transaction Rollbacks:
  1. User A gets NEXTVAL as 111.
  2. User B gets NEXTVAL as 112 and commits.
  3. User A’s session fails or transaction is rolled back.
  4. User C gets the next value 113, leaving a gap (111 unused).
• Shared Pool Flush:
  • Cached sequence values are invalidated whenever the shared pool is flushed, which applies to both RAC and single-instance databases.

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3. Performance Impact of CACHE vs. NOCACHE

Caching:

• The dictionary cache is updated only once for every cache size increment (e.g., 20 values). These cached values are distributed to sessions requesting NEXTVAL.
• Cached sequences significantly improve throughput because they avoid frequent locking and updates to the dictionary cache.

Non-Caching:

• Each NEXTVAL request requires a dictionary cache update, leading to a row cache lock wait.
• Throughput decreases significantly due to serialization and locking overhead, especially in RAC environments.

CACHE + ORDER in RAC:

• DFS Lock Handle Wait: Sessions requesting NEXTVAL must acquire an exclusive instance-level lock (SV lock), causing some sessions to wait.
• Scalability: Sequence throughput does not scale with additional RAC nodes due to the increased overhead of synchronization mechanisms.

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4. Recommendations for Optimizing Sequences in RAC

1. Use CACHE + NOORDER (Default):
   • Best performance for most use cases, especially when global ordering is not required.
2. Minimize Gaps:
   • Avoid using sequences for applications that cannot tolerate gaps. Use alternative methods, such as storing sequence numbers in database tables, though this introduces its own performance trade-offs.
3. Enable Caching:
   • Always enable caching for sequences unless legal requirements demand otherwise. A larger cache size reduces the frequency of dictionary cache updates.
4. Optimize for Ordering:
   • Use CACHE + ORDER only if globally ordered sequences are necessary. Be prepared for higher performance overhead.
5. Avoid NOCACHE + ORDER in RAC:
   • This configuration introduces the highest performance overhead and should be used only when absolutely necessary.
6. Monitor Performance:
   • Use views like V$SEQUENCES to track whether sequences are cached and optimize configurations accordingly.

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Summary

The configuration of sequences in a RAC environment directly impacts database performance, scalability, and application requirements. While caching and NOORDER configurations minimize performance overhead, ORDER configurations introduce synchronization challenges, particularly in RAC. Understanding these trade-offs is key to designing an efficient and scalable system.

By carefully selecting sequence configurations based on business requirements, you can achieve an optimal balance between performance and functionality in a RAC environment.