𝗔 𝗦𝗶𝗺𝗽𝗹𝗲 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲 𝘁𝗼 𝗘𝗻𝘀𝘂𝗿𝗲 𝗢𝗻𝗹𝘆 𝗢𝗻𝗲 𝗝𝗼𝗯 𝗥𝘂𝗻𝘀 𝗮𝘁 𝗮 𝗧𝗶𝗺𝗲 𝗶𝗻 𝗮 𝗚𝗿𝗼𝘂𝗽 𝗼𝗳 𝗣𝗮𝗿𝗮𝗹𝗹𝗲𝗹 𝗝𝗼𝗯𝘀

While reviewing our batch processing cycle, I noticed that several jobs contained the following DD statement in their final job step:

//ENQUEUE DD DSN=DUMMY.ENQUEUE.DSN,DISP=OLD

Interestingly, the dataset referenced by this DD statement was completely empty and was not accessed or processed by any program within the job. This raised the question: Why was this dataset included in multiple jobs?

After further analysis, I discovered that this was being used as a simple serialization mechanism. Although these jobs could potentially be scheduled to run in parallel, they were intentionally prevented from doing so to avoid database contention issues.

 

How It Works

The key lies in the DISP=OLD parameter. When a job is selected for execution, z/OS allocates all datasets required by a job step before the step begins execution. Because the dataset DUMMY.ENQUEUE.DSN is requested with DISP=OLD, the system reserves it for exclusive use.

As a result:

• The first job that acquires the dataset proceeds normally.
• Any other job that also requests the same dataset with DISP=OLD must wait until the dataset is released.
• Since the DD statement is present in the last step of each job, the dataset remains allocated until that step completes, effectively ensuring that only one job from the group runs at a time.

This creates a simple enqueue mechanism using dataset allocation.

 

Alternative Approaches

 

Mainframe Job schedulers provide built-in facilities for managing job dependencies, resource constraints, and mutual exclusion requirements. These features are usually more flexible and easier to maintain than relying on dataset allocation techniques.

 

However, the application developers chose to implement serialization using DISP=OLD on a dummy dataset. This may have been due to historical reasons, or perhaps a lack of awareness of the scheduler's resource management capabilities.