Basic DB2 Buffering and Memory Guidelines

One of the most important areas for tuning DB2 subsystem performance is memory usage. DB2 for z/OS uses memory for buffer pools, the EDM pool, RID pool and sort pools to cache data and structures in memory. The better memory is allocated to these structures, the better DB2 will perform.

When allocating DB2 buffer pools, keep these rules of thumb in mind:

Don't allocate everything to a single buffer pool (e.g., BP0); use a multiple buffer pool strategy.

Explicitly specify a buffer pool for every table space and index.

Isolate the DB2 Catalog in BP0; put user and application DB2 objects into other buffer pools.

Consider separating indexes from table spaces with each in their own dedicated buffer pools.

Consider isolating heavily hit data into its own buffer pool to better control performance.

Consider isolating sorts into a single buffer pool and tuning for mostly sequential access (e.g. BP7).

Consider separating DB2 objects into separate buffer pools that have been configured for sequential verses random access.

Forget about trying to follow a cookie-cutter approach to buffer pool management. Every shop must create and optimize a buffer pool strategy for its own data and application mix. DB2 offers the following buffer pool tuning "knobs" that can be used to configure virutal buffer pools to the type of processing they support:

DWQT –this value is the deferred write threshold; it is expressed as a percentage of the virtual buffer pool that might be occupied by unavailable pages. When this threshold is reached DB2 will start to schedule write I/Os to externalize data. The default is 50%, which is likely to be too high for most shops.

VDWQT – this value is the vertical deferred write threshold; it is basically the same as DWQT, but for individual data sets. The default is 10%, which once again is quite likely to be too high for many shops.

VPSEQT – this value is the sequential steal threshold; it is a expressed as a percentage of the virtual buffer pool that can be occupied by sequentially accessed pages. Tune buffer pools for sequential access such as scans and sorting by modifying VPSEQT to a larger value. The default is 80%.

VPPSEQT – this value is the sequential steal threshold for parallel operations; the default value is 50%.

VPXPSEQT – this value is assisting parallel sequential threshold; it is basically the VPPSEQT for opertaions from another DB2 subsystem in the data sharing group.

These parameters can be changed using the ALTER BUFFERPOOL command. Additionally, hiperpools can be created to back up DB2 virtual buffer pools with additional memory. DB2 provides several tuning knobs for hiperpools, too, including HPSIZE to adjust the size of hiperpools and HPSEQT to adjust the hiperpool sequential steal threshold.

With the advent of DB2 V8, we will have more memory at our disposal for DB2's use. This next version of DB2 will be able to surmount the limitation of 2GB real storage that was imposed due to S/390's 31-bit addressing. Theoretically, with 64-bit addressing DB2 could have up to 16 exabytes of virtual storage addressability to be used by a single DB2 address space. Now there is some room for growth!

In addition to buffer pools, DB2 uses memory for the EDM pool. The EDM pool is used for caching internal structures used by DB2 programs. This includes DBDs, SKCTs, CTs, SKPTs, and PTs. It also includes the authorization cache for plans and packages, as well as the cache for dynamic SQL mini-plans. As a general rule of thumb, shoot for an 80 percent hit rate with the EDM pool; this means that only one out every five times should a structure need to be loaded from disk into the EDM pool.

Finally, remember that buffer and EDM pool tuning are in-depth subjects that cannot be adequately covered in a high-level tip such as this. So, study those IBM DB2 manuals - and learn by doing. Additionally, there is much more to proper DB2 system performance tuning than memory tuning. Other system elements requiring attention include allied agent setup (CICS, TSO, etc.), network configuration, locking, logging, and Parallel Sysplex configuration and management for DB2 data-sharing shops.

Stages 3 and 4

All good DB2 developers and DBAs know about Stage 1 and Stage 2 predicates, right? But have you ever heard of Stage 3 and Stage 4 predicates? Well, you’re about to!

First of all, let’s do a quick review to catch those readers who don’t know what Stage 1 and 2 are. You may have heard about sargable and nonsargable, and if so, Stage 1 is sargable and Stage 2 is nonsargable. If not, don’t worry about those terms, they are obsolete.

A predicate that can be evaluated in the Data Manager (DM) component of DB2, that is at the earliest stage of query execution, is called a Stage 1 predcicate. Stage 2 predicates need to be passed up to the Relational Data System (RDS) to process. So Stage 1 predicates are more efficient than Stage 2 predicates because the Data Manager component of DB2 is at a level closer to the data than the Relational Data System. Stage 1 predicates, being evaluated earlier in the data retrieval process, avoid the overhead of passing data from component to component of DB2. For this reason, developers are encourage to use Stage 1 predicates rather than Stage 2 predicates to optimize performance.

What makes a predicate Stage 2 instead of Stage 1? Well, it is all in the type of predicate you code and how you write your SQL. There is a list of Stage 1 and Stage 2 predicates in Chapter 12 of the DB2 Performance and Tuning manual. (The same chart also tells you whether a predicates is indexable or not.) Whenever you move from one release of DB2 to another one of the first things you should do is consult this manual to see if any predicates have changed from Stage 2 to Stage 1… and you should make sure all of your developers have a copy of that chart taped to their cubicle wall!

OK, so what is all of this about Stage 3 and Stage 4, then? Well, it is a way of thinking about some bad SQL practices. Instead of coding a SQL predicate some programmers choose to bring all (or most) of the data into their program and then filter it using IF-THEN or CASE statements. You can think of these as Stage 3 predicates because it is one more place that the data must be passed to before it can be determined whether the data is needed.

Stage 4? That is when you use a black box (see the link for an explanation if you don't know what a black box is)... Instead of filtering the data in the DM or the RDS or even in your program, you have to work with another program altogether – the black box – to return the right data.

So just remember 1… 2… 3… 4… and that is the order of efficiency for those types of predicates. 1 is better than 2 is better than 3 is better than 4…