2013-01: Finding the right SSD (solid state disk) candidates


A while back IBM introduced support for SSDs (solid state disks) on the mainframe. They have been around for years known as Flash memory, SD Cards, USB sticks, or Thumb drives and have been fantastic in their flexibility and speed of use.

As a PC user, I have loads of them and recently actually “retired” all of my sticks that were under 4GB (I remember my first 128 MB stick with happy memories!). The reason we love these little babies is that they are small, very fast and take no power. The downside is that they are slow (if you have just USB 1.1 or 2), expensive, and they do not last forever. I read a paper that stated after about 5000 rewrites the data could start to “lose its cohesion” which reminded me more of a transporter pattern buffer failure in Star Trek than losing a Word or Excel file from my stick – but I digress…


Where’s the beef?

Well the marketing hype is that SSDs will dramatically increase your I/O speed, increase throughput and make everyone very happy and put the HDD (Hard Disk Drive or “spinning drive”) into the Vinyl retirement home within a few years just like the CD has done. Now of course there is a lot of truth in all this hype. Think about what we as DBAs do a lot of the time…We try to increase performance and we do this by attempting to reduce CPU and I/O. Why do we try and reduce I/O? Because it is so slow! That’s why DB2 has gotten HUGE bufferpools over the years so that it can, with luck, avoid an I/O as to catch the right block, as it merrily spins around and around. That is actually quite tricky!


Advantages of the SSD

The major difference is, of course, that SSDs do not spin and so have no rotation and seek time for the physical head to “find” the right block, and naturally the extra, incredible bonus of more than one access at the same time! A disk head can only be in one place at one time but a SSD is just memory and can be read in parallel! A lot of people forget this little fact but it makes a dramatic difference to I/O times.


Technical performances

With normal HDDs ranging in size from 146GB up to 900 GB spinning around, between 15000 rpm for the 146GB to 450 GB ones, and 10000 rpm for the bigger ones, the random read time for a 4k page is about 6ms. When you use a SDD, that plummets down to around 1ms, so that is 6 times faster on its own. But do not forget the overlapping data access on a SDD. A HDD at 15000 rpm can do about 200 4k random page reads a second whereas SDD can do 5000 4k random page reads a second!


SDDs really win when it comes to Random page reads, but they also give a boost with DB2 List prefetch when the number of pages to be read is 15% of the total or less – the lower the percentage the better the performance when compared to HDD access. When you add striping of data into the mix the results just get better.



OK – Sounds too good to be true? Well it is all true but it COSTS!!! That’s why today you either buy a machine with intelligent software for “Tiering” the data between SDD, HDD, and SATA (That is the third type of mainframe HDD which is 1 or 2 Terabytes but even slower than the HDDs as they revolve at 7200 rpm!). The downside for “Tiering” is that the controller does the work and you have nearly no idea where the data is and what to check for. Better, in my opinion, is an SMS class that allocates the data either to SDD or “other”.


Identifying the right candidates

OK, that’s the introduction, now onto the real topic “Which data?”

Simply put, any data that fits this list of properties is a candidate.


From top to bottom are the best indicators, and the more indicators that match the better it will be!

  1. Random read – As a random page read is about 1ms, any random big hitter will benefit
  2. Low cache hit ratio – If this object is also not often hit in the disk cache
  3. High I/O rate – If this object gets a lot of traffic or IO/Sec/GB
  4. High read percentage – if users hit this object and read lots of it
  5. High read only disconnect time – Use SMF records 42 – 6 and 74 – 5


All of these things play a role in the decision of where your data should live. Finding out the numbers can be a bit tricky depending on what monitors, traces etc. you have at your disposal. But there are some pretty good things available for nearly nothing or free. The DISPLAY BUFFERPOOL command, when a table is isolated, can give very good information about the Random – Sequential access ratios and usage as well as all the normal monitors out there of course!


Once you have found your typically large object(s) that are randomly accessed, you then face another interesting question: Does CLUSTERing play a role anymore? Of course the idea is that “two rows are next to each other” and so one getpage gets both rows but on SDD you really have absolutely no idea where the data physically is (There are algorithms for data placement to increase the lifespan of the SDD and stop bad data etc., all of which, “move” the data around) and so the answer is: “Not really”. Which is why, in SOFTWARE ENGINEERINGs RealTimeDBAExpert (RTDX) product, we have these extra lines available for the decision about whether or not to REORG:


MIN PAGES 64   0No REORG if object is smaller
PCT CHANGEDPercentage changed rows
PCT UNCLUSTINS10  10Sensitive-  > _______ SSD mult. 2
-2for objects > _______ pages
PCT HASH OVERPercentage hash overflow usage
MASS DELETES  0    0 Number of mass deletes


Here you can see two thresholds have been created for DB2 10 NF. First is the “Sensitive > _______” which uses the new columns in the Real-Time Statistics tables in DB2 10 NF to recommend a REORG due to unclustered data if the number of accesses, which are sensitive to sequential sequence, exceeds this value. And then, if the data is on an SSD, use a multiplier of the threshold because the need to REORG for CLUSTERing is much less. RTDX defaults to two, which in this case, would simply double the 10% to 20% before recommending a REORG. This whole system reduces the need for REORGs and their huge use of I/O and CPU dramatically of course!


What other side effects are there? Well, if you start to think about it a bit, you come to the conclusion that an SSD is really just a BUFFERPOOL dressed up like a HDD. This implies the chance to resize your actual bufferpools for non-SDD usage and, of course, to potentially resize your SDD data attributes (PCTFREE, FREESPACE etc.) as the notion of “data placement” is basically *gone* with SDDs.

A last couple of points though

  1. Leave indexes on HDD.
  2. Leave mainly sequentially accessed objects on HDD.


Feel free to send me your comments and ask questions.

Roy Boxwell
Senior Architect