The Challenges of Managing Dynamic SQL in Db2 for z/OS

In the world of Db2 for z/OS, SQL performance tuning is one of the most critical — and often most complicated — DBA responsibilities. While static SQL has long been the bread and butter of traditional mainframe applications, the growing use of dynamic SQL—driven by modern applications, APIs, and distributed workloads—has changed the tuning game.

Dynamic SQL brings with it agility and flexibility but also introduces a new layer of complexity that can hinder performance if not well managed. With this in mind, we’ll look at why dynamic SQL can be so challenging, what DBAs can do to get ahead of performance problems, and how a product like Infotel’s DB/IQ QA can help simplify and streamline the process.

Understanding the Challenges of Dynamic SQL

Unlike static SQL, which is precompiled and bound into Db2 packages before execution, dynamic SQL is compiled at runtime. This means that Db2 must parse, optimize, and generate an access path on the fly every time a dynamic SQL statement is issued (unless it’s reused from the dynamic statement cache).

While this provides flexibility to handle variable application logic or user-driven queries, it can come at a cost:

• Increased overhead at runtime due to repeated optimization and compilation steps.
• Access path volatility, especially if RUNSTATS are out-of-date or if the query text varies slightly (e.g., literals vs. parameter markers).
• Limited visibility into execution patterns compared to static SQL, making it harder for DBAs to detect inefficient queries or identify tuning opportunities.
• Dynamic Statement Cache (DSC) inefficiency, where similar queries with different literals can prevent reuse and add to CPU consumption.

Add to that the explosion of dynamic SQL from JDBC, ODBC, mobile applications, and REST APIs, and it’s clear that DBAs need better tools and strategies to rein in the chaos.

Tuning Dynamic SQL: What Works?

Managing dynamic SQL requires a shift in mindset from traditional static SQL monitoring and tuning. Because dynamic statements are compiled at execution time, you can’t rely on pre-existing packages or EXPLAIN output alone. Instead, tuning efforts must often be reactive or, ideally, proactive with real-time monitoring and historical trend analysis.

Here are several effective strategies and best practices for tuning dynamic SQL in Db2 for z/OS:

1. Leverage Parameter Markers to Promote Cache Reuse

Db2’s Dynamic Statement Cache (DSC) is critical for minimizing the overhead of dynamic SQL. When an incoming SQL statement exactly matches one already in the cache, Db2 reuses the compiled access path, saving CPU and improving response time.

However, literal values embedded in SQL (e.g., WHERE REGION = ‘NE’) cause each unique combination to be treated as a different statement—even if the structure is the same. A helpful technique can be to use parameter markers.

Instead of:

 SELECT * FROM CUSTOMER WHERE REGION = ‘NE’;

Use:

 SELECT * FROM CUSTOMER WHERE REGION = ?;

This small change allows Db2 to match statements more easily, greatly improving cache hit ratios and reducing redundant compilation work.

2. Enable Query Concentration

Introduced in Db2 11, Query Concentration automates the process of literal substitution at runtime. When enabled (via CONCENTRATE STATEMENTS WITH LITERALS), Db2 internally replaces literals with parameter markers and treats similar statements as equivalent for cache purposes.

This feature is especially useful for applications that generate dynamic SQL using literals (as is common with many frameworks). By enabling query concentration, DBAs can increase DSC efficiency without requiring application code changes.

3. Monitor the Dynamic Statement Cache

Regularly reviewing the dynamic statement cache is essential to identify:

• High-frequency dynamic queries
• Statements with poor performance metrics (e.g., high GETPAGEs, CPU, elapsed time)
• Inefficient access paths due to volatile predicates or missing indexes

The following techniques can be helpful:

• Start and monitor IFCID 316 and 317 (via SMF records or performance monitors)
• Use the DISPLAY DYNAMIC CACHE command
• Issue performance SQL queries against the cache tables (SYSIBM.SYSDYNSTAT)
• Utilize third-party tools like Infotel DB/IQ QA for deeper insights

From this analysis, you can isolate performance hotspots and develop tuning plans.

4. Promote Host Variables and Prepared Statements

From an application development perspective, encouraging use of host variables in COBOL, or prepared statements in Java/JDBC, promotes not only parameterization but also reuse of SQL execution plans.

Prepared statements enable a single SQL statement to be compiled once and reused multiple times in the same session, reducing runtime overhead.

5. Use EXPLAIN STMTCACHE ALL to Review Access Paths

Since dynamic SQL is compiled at execution, traditional EXPLAIN statements won’t capture access paths unless you explicitly extract them from the cache. Db2 provides support for this using EXPLAIN STMTCACHE ALL.

Or for specific statements: EXPLAIN STMTCACHE STMTID <stmt-id>;

This lets you analyze which indexes are being used, whether tablespace scans are occurring, and whether suboptimal access paths are hurting performance.

6. Track Long-Term Trends for Dynamic Workloads

Point-in-time analysis is useful, but many dynamic SQL tuning issues are intermittent or triggered by changes in data distribution or statistics. DBAs should track dynamic query performance over time, ideally at the normalized SQL level (where literals are removed), to detect regression patterns and prevent recurring problems.

This is where tools like Infotel DB/IQ QA really shine. Such tools can provide historical visibility across dynamic SQL workloads, allowing DBAs to proactively detect emerging performance trends.

7. Use Profile Tables for Optimizer Guidance

For dynamic SQL that can’t easily be rewritten or parameterized, Db2 optimization profile tables (e.g. DSN_PROFILE_TABLE) allow you to guide access path selection using static statistics. This lets you apply run-time control to influence optimizer behavior, which can be especially useful for third-party or legacy applications that have no subject matter experts.

8. Coordinate with Application Developers

A strong DevOps or agile environment demands collaboration. DBAs should work with developers to:

• Encourage best practices for coding optimal SQL
• Ensure that frameworks use parameterization where possible
• Establish SQL code review checkpoints in the CI/CD pipeline

Education, paired with performance data, is often the best way to eliminate repeat offenders in poorly performing dynamic SQL.

But even with all of these tactics, tracking the behavior of dynamic SQL across time, users, and systems can be arduous and time-consuming unless you have the right visibility.

Enter Infotel DB/IQ QA: Bringing Clarity to Dynamic SQL

Infotel DB/IQ QA is a performance analytics tool purpose-built to monitor and manage SQL performance, with deep support for dynamic SQL on Db2 for z/OS. It offers a comprehensive and granular view of SQL activity, for both static and dynamic SQL. As such, DB/IQ QA can make it significantly easier for DBAs to identify issues and take corrective action.

Let’s take a look at the many capabilities of DB/IQ QA and how it can help DBAs manage the performance of applications with dynamic SQL.

SQL Capture and Normalization

DB/IQ QA continuously captures all SQL statements, including those executed dynamically, and normalizes similar statements by converting literals to parameter markers. This normalization allows the tool to group together “similar” queries, making it easier to see patterns and understand which variations are consuming the most resources.

Performance Metrics and Trending

DB/IQ QA collects key performance indicators for each SQL statement (for example, CPU time, GETPAGEs, rows processed, and elapsed time). You can view historical trends for each normalized dynamic SQL pattern to track regressions or the impact of tuning efforts over time.

Workload Profiling and Problem Detection

Using built-in rules and thresholds, DB/IQ QA can automatically flag inefficient dynamic SQL, such as statements with unusually high CPU or I/O, or those causing unnecessary catalog access. These alerts help DBAs prioritize where to focus tuning efforts.

Integration with Optimization Tools

DB/IQ QA doesn’t just report problems, it can help to resolve them. By exporting identified SQL to optimization tools, it enables rapid root-cause analysis. In some environments, DB/IQ QA has been used to support continuous SQL performance tuning in DevOps pipelines.

Dynamic Cache Visibility

DB/IQ QA enhances visibility into the reuse patterns of the dynamic statement cache, identifying which statements benefit from the DSC and which don’t. This can help DBAs to refine application coding practices accordingly.

Conclusion: Wisely Embrace the Dynamic World

Dynamic SQL isn’t going away—in fact, it’s becoming more prevalent as agile development and hybrid workloads become the norm. But with the flexibility of dynamic SQL comes responsibility. DBAs must adapt and develop new ways of monitoring and tuning dynamic workloads in real-time and across the application lifecycle.

Tools like Infotel DB/IQ QA bring order to chaos by giving DBAs the visibility, control, and insight they need to ensure that dynamic SQL performs efficiently and predictably. Just like long-time DBAs are used to with static SQL.

As dynamic workloads grow more complex, the right tools aren’t just helpful, they’re essential. It is prudent to use tools like DB/IQ QA to help your organization deliver consistent performance in a dynamic Db2 world. For more information on Infotel products please visit https://infotel-software.com.

By Craig Mullins, Mullins Consulting