How do I partition data for parallel processing?

Divide input files by logical ranges (customer ID, date ranges, regions) and process each partition independently.

What are the benefits of concurrent processing?

Faster execution, better resource utilization, improved throughput, and reduced batch window requirements.

COBOL Concurrent Processing

Q: What is concurrent processing?

Running multiple COBOL programs or job steps simultaneously to improve throughput and reduce overall execution time.

Concurrent processing runs multiple COBOL programs or job steps simultaneously to improve throughput and reduce execution time. Design for data partitioning, synchronization, and resource management.

Data Partitioning Strategy

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       *> Partition customers by ID ranges
       IF CUSTOMER-ID >= 1 AND CUSTOMER-ID <= 100000
           MOVE 'PART1' TO PARTITION-ID
           PERFORM PROCESS-PARTITION-1
       ELSE IF CUSTOMER-ID >= 100001 AND CUSTOMER-ID <= 200000
           MOVE 'PART2' TO PARTITION-ID
           PERFORM PROCESS-PARTITION-2
       ELSE IF CUSTOMER-ID >= 200001 AND CUSTOMER-ID <= 300000
           MOVE 'PART3' TO PARTITION-ID
           PERFORM PROCESS-PARTITION-3
       END-IF.

Divide data into logical partitions based on business rules. Each partition can be processed independently by separate jobs. Use consistent partitioning logic across all programs to ensure data integrity.

Parallel Job Execution

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       *> JCL example for parallel execution
       //STEP1 EXEC PGM=CUSTPROC,PARM='PARTITION=1'
       //STEP2 EXEC PGM=CUSTPROC,PARM='PARTITION=2'
       //STEP3 EXEC PGM=CUSTPROC,PARM='PARTITION=3'
       //STEP4 EXEC PGM=MERGEPROC  *> Merge results after parallel steps

Use JCL to run multiple instances of the same program with different parameters. Each step processes a different data partition. Include a final step to merge or consolidate results.

Workload Distribution

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       *> Distribute work by processing time
       IF RECORD-TYPE = 'A'  *> Complex processing
           PERFORM COMPLEX-PROCESSING
           ADD 1 TO COMPLEX-COUNT
       ELSE IF RECORD-TYPE = 'B'  *> Simple processing
           PERFORM SIMPLE-PROCESSING
           ADD 1 TO SIMPLE-COUNT
       END-IF.

Balance workload by distributing complex and simple records across different processors. Monitor processing times and adjust distribution ratios based on actual performance.

Synchronization Points

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       *> Wait for all partitions to complete
       PERFORM CHECK-COMPLETION UNTIL ALL-PARTITIONS-DONE
       IF ALL-PARTITIONS-DONE
           PERFORM MERGE-RESULTS
           PERFORM FINAL-VALIDATION
       ELSE
           DISPLAY 'Waiting for partition completion...'
           PERFORM WAIT-INTERVAL
       END-IF.

Implement synchronization to ensure all parallel processes complete before proceeding. Use checkpoints, completion flags, or file-based signals to coordinate between jobs.

Resource Management

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       *> Limit concurrent database connections
       IF DB-CONNECTION-COUNT < MAX-CONNECTIONS
           PERFORM ESTABLISH-CONNECTION
           ADD 1 TO DB-CONNECTION-COUNT
       ELSE
           PERFORM WAIT-FOR-CONNECTION
       END-IF.

Manage shared resources like database connections, temporary files, and memory. Implement connection pooling and resource limits to prevent contention and system overload.

Partition data logically to minimize dependencies between processes.
Balance workload across processors for optimal performance.
Synchronize critical points to ensure data consistency.
Monitor resource usage to prevent bottlenecks.
Test with realistic data volumes and concurrent loads.

Concurrent Access

Safe file sharing patterns

Concurrency Control

Locking and isolation strategies