Understanding Oracle Buffer Busy Wait

What is Oracle Buffer Busy Wait?

Oracle Buffer Busy Wait is a performance-related issue that occurs within the Oracle Database system when multiple sessions are contending for the same data buffer in the database buffer cache. When a session needs to access a specific data block that is currently locked by another session, it enters a “buffer busy” state, waiting for the required buffer to become available. This condition is known as Oracle Buffer Busy Wait.

Common Causes of Buffer Busy Waits:

1. High Concurrent Activity: Buffer busy waits often occur in systems with a high level of concurrent transactions and data manipulation. As multiple users access and modify data concurrently, contention for the same data blocks in the buffer cache can increase, leading to buffer busy waits.
2. Misconfigured Memory: Inadequate memory allocation or improper memory management settings can exacerbate buffer busy waits. When the database lacks sufficient buffer cache size to accommodate frequent data access, buffer contention arises.
3. Unoptimized SQL Queries: Poorly tuned SQL queries can put unnecessary stress on the buffer cache, causing excessive buffer busy waits. Inefficient queries may access data in a non-sequential manner, leading to frequent buffer evictions and reloads.
4. Hot Blocks: In some scenarios, specific data blocks experience disproportionately high access rates, making them “hot blocks.” As numerous sessions compete for access to these hot blocks, buffer busy waits can become more prevalent.

Impact on Database Performance and User Experience:

Oracle Buffer Busy Waits can have significant consequences on database performance and user experience:

1. Reduced Throughput: The presence of buffer busy waits can hinder the overall throughput of the database. Frequent waits and contention delay data retrieval and update operations, slowing down transaction processing.
2. Increased Response Time: As buffer busy waits prolong the time taken to acquire necessary data blocks, users experience delayed responses from the database, leading to a perceived sluggish system.
3. Resource Utilization: The waiting sessions consume system resources, impacting the performance of other database operations and leading to resource contention.
4. Scalability Concerns: Buffer busy waits can hinder the database’s ability to scale effectively to handle increased user demand and transaction volume.
5. User Frustration: Prolonged wait times can lead to user frustration and dissatisfaction with the application, potentially affecting user retention and business reputation.

Monitoring Tools and Techniques:

Database Monitoring Tools: Oracle provides various monitoring tools to track database performance. Oracle Enterprise Manager (EM) is a comprehensive monitoring and management tool that offers real-time monitoring of database metrics, including buffer busy waits. EM provides graphical representations and alerts for immediate attention to buffer busy wait issues.

Oracle Diagnostics Pack: The Diagnostics Pack includes additional performance monitoring features such as Active Session History (ASH) and Automatic Database Diagnostic Monitor (ADDM). ASH captures detailed information about active sessions, allowing you to pinpoint buffer busy waits in real-time. ADDM analyzes AWR data to provide performance recommendations, including buffer contention-related issues.

Custom Scripts and Queries: Experienced DBAs often create custom scripts or queries to monitor specific performance aspects. These scripts can extract relevant data from dynamic performance views, helping to track buffer busy waits and associated sessions.

Key Performance Indicators (KPIs) to Look for:

1. Buffer Busy Wait Events: Keep an eye on the total count of buffer busy wait events over time. A significant increase in the number of buffer busy waits could indicate contention issues.
2. Average Wait Time: Monitor the average time sessions spend in buffer busy waits. A sudden spike in average wait time may highlight severe buffer contention.
3. Wait Time Distribution: Analyze the distribution of wait times for buffer busy waits. Identify the percentage of short, medium, and long waits, as excessively long waits may demand immediate attention.

Analyzing AWR Reports for Buffer Busy Waits:

 

 

1. Generate AWR Report or Use the DBMS_WORKLOAD_REPOSITORY package to generate an AWR report for the desired time period. Schedule AWR snapshots regularly to capture performance data.
2. Wait Events Section: In the AWR report, focus on the “Wait Events” section. Look for buffer busy wait events and their respective wait times.
3. Top Wait Events: Identify the top buffer busy wait events and note their occurrence and average wait times. Focus on events with the most significant impact on database performance.
4. Affected Sessions and SQL: Analyze the AWR report to identify the sessions and SQL statements contributing to buffer busy waits. Pinpointing the root causes will guide targeted optimizations.
5. Compare Snapshots: If possible, compare AWR reports from different time intervals to identify trends and changes in buffer busy wait behavior.

By using the right monitoring tools, tracking essential KPIs, and analyzing AWR reports, you can proactively identify buffer busy waits and take appropriate actions to improve your Oracle database’s performance.

Optimizing Database Configurations:

Optimizing the database configurations is a crucial step in resolving Oracle Buffer Busy Waits and improving overall database performance. By fine-tuning various parameters and settings, database administrators can create an environment that minimizes buffer contention and ensures smooth data access for users. Here are some essential techniques for optimizing database configurations:

1. Buffer Cache Size: The buffer cache is a critical component of the Oracle Database, responsible for caching frequently accessed data blocks in memory. Adequate buffer cache sizing is vital to reduce disk I/O and buffer busy waits. DBAs should carefully analyze the database workload and consider factors such as the size of frequently accessed tables and indexes, the number of concurrent users, and the available system memory to determine an optimal buffer cache size.
2. Automatic Shared Memory Management (ASMM): Oracle’s Automatic Shared Memory Management (ASMM) feature dynamically manages memory components, including the buffer cache, shared pool, and other memory structures. ASMM allocates memory based on the actual workload, adjusting the sizes of different memory pools to optimize performance. Enabling ASMM simplifies memory management and allows the database to adapt to changing workload patterns, reducing the likelihood of buffer busy waits.
3. Buffer Cache Keep and Recycle Pools: The KEEP and RECYCLE buffer pools are specialized memory areas that can be used to improve buffer utilization. The KEEP pool retains frequently accessed data blocks, preventing them from being aged out of the buffer cache prematurely. The RECYCLE pool, on the other hand, is designed for less-frequently accessed data, reducing contention with hot blocks. By segregating frequently accessed objects from less active ones, buffer contention can be significantly reduced.
4. Block Size Considerations: Oracle allows databases to be created with different block sizes, such as 4KB, 8KB, or 16KB. The choice of block size can impact buffer cache efficiency. For workloads involving large sequential reads, a larger block size might be more appropriate, while smaller block sizes are suited for OLTP workloads with random access patterns. Understanding the access patterns of the database and selecting an optimal block size can lead to improved buffer cache utilization.
5. File Placement and I/O Configuration: Properly distributing data files across multiple storage devices and configuring I/O settings can also impact buffer busy waits. Placing data files on separate disks or disk groups can distribute I/O load and reduce contention. Additionally, utilizing technologies such as RAID can enhance I/O performance and mitigate buffer cache-related issues.
6. Buffer Cache Flushing: Controlling the frequency of buffer cache flushing to disk is essential. Setting the appropriate values for the DB_CACHE_SIZE, DB_BLOCK_WRITES, and DB_BLOCK_BUFFERS parameters can help strike a balance between maintaining data in the cache and flushing it to disk. This can minimize buffer contention and improve overall database performance.

By optimizing database configurations with these techniques, database administrators can significantly reduce buffer busy waits, enhance data access efficiency, and ensure a smoother experience for users interacting with the Oracle Database.

Query Tuning for Buffer Efficiency:

Optimizing SQL queries is a fundamental approach to reduce buffer busy waits and improve the overall efficiency of the Oracle Database. Poorly written or inefficient queries can cause excessive buffer evictions and reloads, leading to increased contention and buffer busy waits. Here are some strategies for query tuning to enhance buffer efficiency:

1. Avoid Full Table Scans: Whenever possible, design queries to utilize indexes rather than performing full table scans. Full table scans can lead to more data blocks being loaded into the buffer cache, potentially evicting other important data and causing buffer contention.
2. Use Appropriate Joins: Choose the most suitable join methods (e.g., nested loop, hash join, merge join) based on the size of the tables and the selectivity of the join conditions. Efficient joins reduce the amount of data loaded into the buffer cache during query execution.
3. Limit Result Set Size: Limit the number of rows returned in query results by using the appropriate WHERE clauses and row limiting techniques (e.g., FETCH FIRST, ROWNUM, or OFFSET-FETCH). This reduces the data retrieved and cached in the buffer cache, optimizing memory usage.
4. Effective Indexing Strategies: Identify High-Volume Queries: Monitor the database to identify queries that are executed frequently and have a significant impact on buffer utilization. Focus on indexing such queries to speed up data retrieval and reduce buffer contention.
5. Create Indexes on Columns Frequently Used in WHERE Clauses: Analyze query patterns and create indexes on columns used in WHERE clauses to enable efficient data retrieval. Properly indexed columns speed up query execution and minimize buffer busy waits.
6. Avoid Over-Indexing: While indexes improve query performance, over-indexing can lead to excessive overhead during data modifications (INSERT, UPDATE, DELETE). Strike a balance between the number of indexes and query performance requirements.
7. Caching and Reusing SQL Execution Plans: SQL Plan Management: Enable SQL Plan Management to ensure consistent and optimal execution plans for frequently executed queries. SQL Plan Management captures and stores execution plans, preventing unstable or inefficient plans that could contribute to buffer busy waits.
8. Use Bind Variables: Utilize bind variables in SQL queries to promote plan reuse. With bind variables, the same SQL statement with different parameter values can use a single cached execution plan, reducing the overhead of parsing and optimizing queries.
9. Gather Statistics Regularly: Maintain up-to-date statistics for database objects. Accurate statistics help the Oracle optimizer choose efficient execution plans and minimize buffer busy waits.

By fine-tuning SQL queries for buffer efficiency, employing effective indexing strategies, and caching and reusing SQL execution plans, database administrators can significantly reduce buffer busy waits, enhance query performance, and ensure a smoother, more responsive Oracle Database system.

Advanced Techniques for Resolving Buffer Busy Waits

To tackle persistent buffer busy waits and optimize Oracle Database performance, advanced techniques can be employed. These techniques go beyond traditional optimizations and delve into specialized features and practices. Here are some advanced techniques to consider:

1. Database Partitioning: Implementing database partitioning can significantly reduce buffer busy waits, especially in environments with large and rapidly growing data. Partitioning divides tables and indexes into smaller, more manageable segments, allowing for better parallelism and reduced contention for data blocks.
2. In-Memory Column Store: Oracle’s In-Memory Column Store (IMCS) is a powerful feature that stores specific tables or partitions in a compressed columnar format in memory. Queries that frequently access these objects can experience tremendous speed improvements, reducing buffer busy waits for hot data.
3. Application Design Optimization: Collaborate with application developers to optimize the design of queries and data access patterns. Efficiently designed applications can minimize unnecessary data fetches and buffer contention, resulting in reduced buffer busy waits.
4. Asynchronous I/O: Leverage asynchronous I/O to reduce I/O wait times and mitigate buffer busy waits. Asynchronous I/O allows the database to perform other tasks while waiting for I/O operations to complete, optimizing overall system performance.
5. Flash-based Storage Solutions: Consider employing flash-based storage solutions, such as Solid-State Drives (SSDs) or PCIe-based flash cards, to accelerate I/O operations and decrease buffer busy waits caused by slow storage devices.
6. Intelligent Caching Layers: Implement intelligent caching layers within the application to reduce the frequency of database reads. Caching frequently accessed data in the application’s memory can minimize the number of buffer busy waits experienced by the database.
7. SQL Performance Analyzer (SPA): Utilize the SQL Performance Analyzer to evaluate the impact of SQL changes on performance before implementing them in the production environment. SPA helps to identify potential buffer busy wait-related issues early in the development cycle.
8. Automatic Data Optimization (ADO): Automatic Data Optimization enables the automated compression and movement of data based on usage patterns. By optimizing storage and memory usage, ADO can mitigate buffer busy waits.
9. Database Resource Manager (DBRM): Implement the Database Resource Manager to manage and prioritize resource allocation in the database. DBRM can ensure that critical queries get higher priority, reducing buffer contention for important data.
10. Optimize Buffer Cache Size: Based on the advisory’s recommendations and considering the available system resources, adjust the buffer cache size (DB_CACHE_SIZE parameter) to a value that offers an optimal balance between memory usage and buffer cache hit ratios.

By adopting these advanced techniques, database administrators can fine-tune the Oracle Database environment, effectively resolving buffer busy waits, and maximizing overall performance and user experience. It is essential to carefully analyze the specific requirements and characteristics of the database workload before implementing these advanced techniques to achieve the best results.

Resolving Buffer Busy Waits – A Performance Case Study

Performance Problem: Buffer Busy Waits due to High Touch Count of Blocks and Asynchronous I/O

Scenario: In a large Oracle Database environment, a critical application experienced frequent buffer busy waits, causing delays in data retrieval and transaction processing. Upon investigation, it was observed that certain tables with a high touch count of blocks were contributing to the buffer contention. Additionally, the I/O subsystem was not efficiently utilizing Asynchronous I/O, further aggravating the buffer busy wait issue.

Resolution Steps:

Identifying Tables with High Touch Count: To identify tables with a high touch count of blocks, we executed the following diagnostic SQL query:

This query retrieves the top tables with the highest number of buffer busy waits based on touch count of blocks. It helps to pinpoint the tables responsible for buffer contention.

Implementing Asynchronous I/O: To optimize I/O performance and mitigate buffer busy waits, we focused on configuring Asynchronous I/O for the database. This is achieved by setting the disk_asynch_io parameter to TRUE:

By enabling Asynchronous I/O, we reduced I/O wait times, allowing the database to perform other tasks while waiting for I/O operations to complete, which positively impacted buffer cache performance.

Caching Frequently Accessed Data: To further improve buffer cache efficiency, we implemented an intelligent caching layer in the application. Frequently accessed data was cached in the application’s memory, reducing the need for frequent buffer reloads and buffer busy waits.

 

By combining diagnostic SQL queries, optimizing Asynchronous I/O, caching frequently accessed data, and leveraging database partitioning, we successfully resolved buffer busy waits in the critical application. The improvements resulted in enhanced system responsiveness and a smoother user experience.

Conclusion

Ensuring peak performance of your Oracle database is paramount for delivering a seamless user experience and achieving business objectives. Throughout this article, we delved into the root causes of Oracle Buffer Busy Waits and explored a range of strategies to address this performance bottleneck. By implementing these recommended techniques, you can alleviate buffer contention and optimize your database’s efficiency.

In a data-driven world, where responsiveness and reliability are crucial, a well-optimized Oracle database can set your organization apart from the competition. Smooth data access, faster transaction processing, and reduced buffer busy waits lead to improved productivity and enhanced customer satisfaction.

Stay proactive in monitoring your database, fine-tuning configurations, and optimizing SQL queries. Embrace advanced features like Oracle Exadata Smart Flash Cache, Flashback Technology, and Asynchronous I/O to further enhance performance.

Remember, the performance of your Oracle database directly impacts the success of your business. Invest time and effort in resolving Oracle Buffer Busy Waits, and witness the transformative impact on your organization’s productivity and competitiveness.

With a finely-tuned Oracle database, you can confidently navigate the data challenges of today and tomorrow, empowering your organization to thrive in an ever-evolving digital landscape. Take action now to optimize your Oracle database and reap the rewards of peak performance.

FAQ

Q1. What Causes Buffer Busy Waits in Oracle?
Buffer Busy Waits in Oracle occur when multiple sessions compete for access to the same data blocks in the buffer cache. The buffer cache is a critical part of the SGA (System Global Area) that holds frequently accessed data, reducing the need for disk I/O. Buffer Busy Waits are often caused by the following factors:
High Concurrent Activity: When multiple sessions concurrently access the same data blocks, contention for buffer cache resources increases, leading to buffer busy waits.
Inefficient SQL Queries: Poorly tuned SQL queries that access data in a non-sequential manner or require frequent reloads of data blocks can contribute to buffer contention.
Hot Blocks: Certain data blocks might experience disproportionately high access rates, becoming “hot blocks.” As multiple sessions compete for access to these hot blocks, buffer busy waits can occur.
Inadequate Memory Allocation: If the buffer cache size is not sufficient to accommodate the workload’s data access patterns, buffer contention and waits may ensue

Q2. How to Avoid Buffer Busy Waits in Oracle?
To avoid buffer busy waits and optimize Oracle Database performance, consider implementing the following measures:
Query Tuning: Optimize SQL queries to access data efficiently and minimize the need for buffer reloads. Use tools like EXPLAIN PLAN and SQL Tuning Advisor to improve query execution plans.
Proper Memory Management: Allocate sufficient memory to the buffer cache (DB_CACHE_SIZE) to reduce buffer contention and waits. Leverage the DB_CACHE_ADVICE parameter to determine the optimal buffer cache size.
Database Partitioning: Consider partitioning large tables to distribute data across smaller segments, reducing contention for specific data blocks.Asynchronous I/O: Enable Asynchronous I/O to reduce I/O wait times and free up sessions waiting for data block access.
Flashback Technology: Utilize Flashback Query and Flashback Transaction Query to analyze historical versions of data and trace the root causes of buffer busy waits.
Advanced Techniques: Explore advanced features like Oracle Exadata Smart Flash Cache, In-Memory Column Store and Database Resource Manager to further enhance performance and reduce waits.

Q3. What Causes GC Buffer Busy Wait in Oracle?
GC Buffer Busy Wait in Oracle occurs in a Real Application Clusters (RAC) environment when a session in one instance wants to access a data block that is already locked by a session in another instance. This type of wait arises due to inter-instance contention for a shared buffer in the Global Cache Service (GCS).
GC Buffer Busy Waits are typically caused by:
High Inter-Instance Activity: When multiple instances in a RAC environment frequently access the same data blocks, inter-instance contention increases, leading to GC Buffer Busy Waits.
Slow Network Communication: Slow network communication between RAC instances can exacerbate buffer contention and increase wait times.
Unbalanced RAC Load: Instances with imbalanced workloads might result in some instances experiencing higher buffer contention, leading to more GC Buffer Busy Waits.

Q4. Oracle Buffer Busy Waits Insert?
Oracle Buffer Busy Waits can occur during insert operations when multiple sessions try to access the same data block simultaneously. If one session is inserting data into a block, other sessions that require access to the same block for reading or writing may experience buffer busy waits.
To resolve buffer busy waits during insert operations, consider implementing the following measures:
Optimize Insert Statements: Make sure the insert statements are efficient and perform bulk inserts when possible to minimize block contention.
Partitioning: Implement table partitioning to distribute insert activity across multiple segments, reducing contention for specific data blocks.
Parallel Insert: Use parallel DML (Data Manipulation Language) to distribute the insert workload across multiple parallel processes, reducing contention.
Asynchronous I/O: Enable Asynchronous I/O to reduce I/O wait times and improve buffer access times.

Q5. What Is Buffer Gets in Oracle?
Buffer Gets in Oracle refers to the number of times Oracle Database reads a data block into the buffer cache from disk or from another cache. Buffer gets are an essential performance metric as they represent the frequency of data block access, which affects database efficiency and response times.
A high number of buffer gets for a SQL statement indicates frequent data block access, which may be either beneficial (for frequently accessed data) or detrimental (for poorly tuned queries causing excessive data block reloads).
Buffer gets can be analyzed using tools like Oracle’s AWR (Automatic Workload Repository) reports and performance monitoring views such as V$SQLSTATS and V$SEGMENT_STATISTICS. Proper tuning of SQL queries and memory management can help optimize buffer gets and overall database performance.

Q6. How Busy Is Too Busy?
The “busy” level in Oracle depends on the workload, system capacity, and performance requirements. What may be considered too busy for one database or application might be acceptable for another. However, several indicators can help assess if the system is excessively busy:
High Wait Times: Long wait times for critical resources like buffer access, I/O, or locks may indicate excessive workload.
High CPU Utilization: If the CPU is continuously operating near its maximum capacity, it could imply that the system is under significant load.
High Buffer Busy Waits: Frequent buffer busy waits may indicate contention for buffer cache resources, affecting performance.
Long Response Times: If end-users experience significant delays in query execution or transaction processing, the system might be too busy.To determine an appropriate “busy” level, administrators should establish performance baselines, monitor performance metrics regularly, and compare them against predefined thresholds. Proper capacity planning and workload management are essential to ensure optimal system performance.

Q7. How Do You Resolve ‘GC Buffer Busy’ Waits Due to Right Hand Growth Index?
To resolve ‘GC buffer busy’ waits due to right-hand growth index in a Real Application Clusters (RAC) environment, consider the following steps:
Monitor and Identify: Use RAC-specific monitoring tools (e.g., gv$session, gv$active_session_history) to identify sessions experiencing ‘GC buffer busy’ waits due to index contention.
Spread Data: Spread data across nodes to reduce contention. Consider using partitioning to distribute data across instances.
Use Reverse Key Index: If applicable, consider using a reverse key index to distribute inserts and reduce right-hand index growth.
Tune Index Parameters: Review index parameters like PCTFREE and PCTUSED to optimize index maintenance.
Parallel DML: Use parallel DML for large data inserts or updates to spread the load across instances.
Lock Partitioning: Implement lock partitioning to reduce index contention.
Balance Load: Ensure a balanced workload across RAC instances to avoid excessive contention.
Resolving ‘GC buffer busy’ waits due to right-hand growth index requires a combination of careful index tuning, data distribution, and RAC-specific performance optimization techniques.

Q8. What is View X$KCBWDS ?
The view X$KCBWDS is an undocumented view in Oracle that provides information about buffer busy waits. It keeps track of buffer busy waits by the Cache Buffers LRU (Least Recently Used) Chain Latch, which protects the LRU and LRUW (Least Recently Used Write) working sets within the buffer cache.
The “Latch Free” wait event is associated with latch contention, which occurs when multiple sessions compete for access to a latch. Latches are lightweight serialization mechanisms used to protect shared data structures in the SGA.
Analyzing the X$KCBWDS view helps identify buffer busy waits associated with the Cache Buffers LRU Chain Latch and assess latch contention. Resolving latch contention involves tuning memory settings, optimizing SQL queries, and ensuring a balanced workload to reduce contention.

Q9. What is “GC Buffer Busy Acquire” Waits?
When multiple sessions in different RAC instances concurrently access the same segment’s header block in an ASSM tablespace, contention for the segment header block can occur, leading to ‘GC Buffer Busy Acquire’ waits.
The ‘GC Buffer Busy Acquire’ wait event indicates that a session in one RAC instance is trying to acquire a Global Cache (GC) buffer for a segment header block that is currently held by another instance.
To reduce ‘GC Buffer Busy Acquire’ waits:
Implement Proper Instance Affinity: Ensure that sessions access the data that belongs to their local instance as much as possible, reducing inter-instance contention.
Partitioning: Consider table or index partitioning to distribute data across smaller segments and reduce contention for specific segment header blocks.
Optimize Space Management: Monitor space usage in ASSM tablespaces and manage space efficiently to reduce the frequency of segment header block contention.
Instance Load Balancing: Ensure a balanced workload distribution across RAC instances to minimize contention.
Addressing ‘GC Buffer Busy Acquire’ waits requires a combination of instance affinity, space management optimization, and load balancing to reduce contention for segment header blocks in ASSM tablespaces.