Data Sharing - Concurrent Access
In the z/OS environment, data sharing with concurrent access refers to the capability for multiple independent applications, address spaces, or even different z/OS systems (in a sysplex) to read from and write to the same data resources simultaneously while maintaining data integrity and consistency. This is crucial for high-availability, scalability, and workload balancing in enterprise computing.
Key Characteristics
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- Integrity Maintenance: Employs sophisticated mechanisms like locking, serialization, logging, and recovery protocols to prevent data corruption and ensure transactional atomicity even with simultaneous updates.
- Concurrency Control: Allows multiple users or applications to access data concurrently, maximizing throughput and resource utilization by minimizing the need for exclusive access.
- Sysplex Exploitation: Often leverages the IBM
Coupling Facility (CF)for shared memory structures, global locking, and cache coherency across multiple z/OS images in aParallel Sysplex. - Resource Management: Requires specialized resource managers (e.g.,
DB2 Data Sharing,IMS Data Sharing,VSAM Record Level Sharing (RLS)) to coordinate access and manage contention across systems. - Performance Optimization: Aims to minimize serialization delays and contention, often utilizing techniques like
page locking,row locking, orrecord lockingto ensure optimal application performance. - Recovery Capabilities: Includes robust logging and recovery mechanisms to restore data consistency and integrity in the event of system or application failures.
Use Cases
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- Online Transaction Processing (OLTP): Multiple CICS regions or IMS Message Processing Programs (MPPs) concurrently updating the same DB2 or IMS databases to process high volumes of transactions (e.g., banking transactions, airline reservations).
- Batch and Online Coexistence: Allowing batch jobs to read or update data while online applications are simultaneously accessing the same data, often with careful coordination to avoid conflicts.
- Disaster Recovery and High Availability: In a
Parallel Sysplex, data sharing enables applications to failover seamlessly to another z/OS system accessing the same shared data, ensuring continuous operation. - Workload Balancing: Distributing application workloads across multiple z/OS images, all accessing a common set of data, to optimize resource utilization and improve response times.
- Data Warehousing Updates: Concurrent loading of new data into a data warehouse while analytical queries are being executed against existing data.
Related Concepts
Data sharing with concurrent access is fundamental to the Parallel Sysplex architecture, relying heavily on the Coupling Facility for inter-system communication and global resource serialization. It is intrinsically linked to database management systems like DB2 for z/OS (via DB2 Data Sharing Groups) and IMS (via IMS Data Sharing), as well as advanced VSAM access methods like VSAM Record Level Sharing (RLS). This capability directly supports high availability, scalability, and workload management strategies across the mainframe enterprise.
- Optimize Locking Granularity: Design applications and database schemas to use the smallest possible locking granularity (e.g., row-level or page-level locking in DB2) to minimize contention and maximize concurrency.
- Design for Concurrency: Structure applications and database schemas to reduce hot spots and potential deadlocks, ensuring transactions are short and efficient.
- Monitor Contention: Regularly monitor
DB2orIMSstatistics for lock contention, deadlocks, and latch waits to identify and resolve performance bottlenecks proactively. - Utilize Coupling Facility Effectively: Properly size and configure
Coupling Facilitystructures (e.g.,cache structures,lock structures,list structures) to support the workload and ensure optimal performance. - Implement Robust Recovery: Ensure comprehensive logging and backup strategies are in place, along with thoroughly tested recovery procedures, to safeguard shared data.