Limit the Use of Data Areas – and Boost Performance

Data areas are a familiar tool for many Power i developers—but in terms of performance, they’re not always your friend. When we analyze customer systems, we’re often surprised by how frequently data areas show up in performance-critical parts of the code. If your application accesses a data area inside the main loop of a program, chances are you're slowing things down more than you realize.

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Why data areas can be costly

Data areas have been around since the System/38 days, and they still follow the same rules: every change is written to disk. That might not sound like much, but if your program is hitting a data area repeatedly—especially in a tight loop—that overhead adds up fast.

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Our tool GiAPA frequently highlights this issue in its reports. One customer job, for example, showed a dramatic performance gain potential simply by replacing the data area with a more efficient object.

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The better alternative: user spaces

Instead of data areas, we recommend using user spaces. Many developers aren’t familiar with them, but they’re essentially large, memory-resident data areas—up to 16 MB in size—that offer much better performance.

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Why are they so fast?

• They don’t write changes to disk each time.
• They can be shared across jobs (given the right authority).
• You can access them directly via a pointer using the API QUSPRTUS, making them up to 756 times faster than data areas.
• Even using the API QUSCHGUS (Change User Space), you’ll see a 6x performance gain compared to traditional data areas.

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User spaces are normal permanent objects. You can save and restore them like any other object, and they can significantly reduce the resource usage of your programs.

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How to identify data area hotspots

GiAPA automatically flags inefficient data area usage by analyzing the call stacks of CPU-intensive jobs. You can also identify data area activity yourself:

• Use DSPPGMREF to list which programs reference data areas.
• Use *DSPJOB OPTION(PGMSTK) and press F5 repeatedly to see which programs are active.
• Frequent entries like QCLRTVDA, QWCCCHVC, QWCCCRVC, QWCCDSVC, QWCRDTAA or QWCSRTVR can be signs of performance bottlenecks due to data area use.

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Final tip

If you’re aiming for better system performance and still rely on data areas, especially inside loops, now is a great time to explore user spaces. It’s a simple switch that could save you serious CPU—and help your applications scale more efficiently.