Hot
In mainframe computing, "hot" refers to data, code, or system resources that are subject to exceptionally high access frequency or intense utilization. Identifying and managing "hot" components is critical for optimizing performance, minimizing resource contention, and ensuring system responsiveness within z/OS and its subsystems.
Key Characteristics
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- High Access Frequency: Data blocks, records, programs, or system services that are consistently read, written, or executed many times per second or minute.
- Performance Bottleneck Potential: If not properly managed or optimized, hot spots can become significant bottlenecks, leading to increased response times and reduced throughput.
- Resource Contention: Frequently accessed resources are prone to contention for CPU cycles, I/O channels, memory, locks, and buffer pool pages.
- Dynamic Nature: What is "hot" can change over time based on workload patterns, peak usage periods, and application behavior.
- Monitoring Target: "Hot" components are prime targets for performance monitoring and analysis using tools like RMF, SMF, DB2 PM, CICS PA, and IMS PA.
Use Cases
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- Database Buffer Pools: Frequently accessed DB2 table spaces or IMS segments are identified as "hot" and kept resident in buffer pools to minimize physical I/O operations.
- CICS Transaction Programs: High-volume CICS transactions and their associated application programs (e.g., order entry, inquiry) are "hot" and require efficient design and resource allocation.
- VSAM KSDS Records: Specific records within a VSAM Key-Sequenced Data Set (KSDS) that are frequently updated or queried, leading to high I/O activity on those control intervals.
- Shared Data Areas: Common control blocks or data structures in shared memory (e.g., ECSA, CSA) accessed by multiple address spaces or tasks.
- JCL Procedures/Libraries: Frequently invoked JCL PROCs or members within PDS/PDSE libraries that are constantly accessed by the system for job execution.
Related Concepts
"Hot" data and resources are central to performance tuning and capacity planning. They are often managed through caching mechanisms and buffer pools (e.g., DB2 buffer pools, CICS data tables) to reduce I/O and improve access times. Identifying "hot" spots is a primary goal of workload analysis and helps in configuring Workload Manager (WLM) policies to prioritize critical workloads. Effective concurrency control and locking strategies are essential to prevent contention and deadlocks on "hot" resources.
- Monitor and Analyze: Regularly use z/OS performance monitors (RMF, SMF) and subsystem-specific tools (DB2 PM, CICS PA, IMS PA) to identify and track "hot" data, programs, and resources.
- Optimize Data Placement: Place "hot" data on the fastest available storage (e.g., SSDs) and ensure it resides in appropriately sized and configured buffer pools or caches.
- Code Optimization: Review and optimize the code paths of frequently executed programs to reduce CPU cycles, I/O operations, and memory footprint.
- Reduce Contention: Design applications to minimize contention on "hot" resources by implementing fine-grained locking, partitioning data, or using optimistic concurrency where appropriate.
- Capacity Planning: Ensure that the system has sufficient CPU, memory, and I/O capacity to handle peak loads for "hot" workloads without degradation.