Thread: [PERFORM] Suggestions for a HBA controller (6 x SSDs + madam RAID10)

Random points/suggestions:

*) mdadm is the way to go.   I think you'll get bandwidth constrained on most modern hba unless they are really crappy.  On reasonably modern hardware storage is rarely the bottleneck anymore (which is a great place to be).  Fancy raid controllers may actually hurt performance -- they are obsolete IMNSHO.

*) Small point, but you'll want to crank effective_io_concurrency (see: https://www.postgresql.org/message-id/CAHyXU0yiVvfQAnR9cyH%3DHWh1WbLRsioe%3DmzRJTHwtr%3D2azsTdQ%40mail.gmail.com). It only affects certain kinds of queries, but when it works it really works.    Those benchmarks were done on my crapbox dell workstation!

*) For very high transaction rates, you can get a lot of benefit from disabling synchronous_commit if you are willing to accommodate the risk.  I do not recommend disabling fsync unless you are prepared to regenerate the entire database at any time.

*) Don't assume indefinite linear scaling as you increase storage capacity -- the database itself can become the bottleneck, especially for writing.   To improve write performance, classic optimization strategies of trying to intelligently bundle writes around units of work still apply.  If you are expecting high rates of write activity your engineering focus needs to be here for sure (read scaling is comparatively pretty easy).

*) I would start doing your benchmarking with pgbench since that is going to most closely reflect measured production performance.  

If this is the case your stack performance is going to be based on data structure design.  Make liberal use of:

*) natural keys 

*) constraint exclusion for partition selection

*) BRIN index is amazing (if you can work into it's limitations)

*) partial indexing

*) covering indexes.  Don't forget to vacuum your partitions before you make them live if you use them

If your data is going to get really big and/or query activity is expected to be high, keep an eye on your scale out strategy.   Going monolithic to bootstrap your app is the right choice IMO but start thinking about the longer term if you are expecting growth.  I'm starting to come out to the perspective that lift/shift scaleout using postgres fdw without an insane amount of app retooling could be a viable option by postgres 11/12 or so.  For my part I scaled out over asynchronous dblink which is a much more maintenance heavy strategy (but works fabulous although I which you could asynchronously connect).

Disclaimer: I’ve done extensive testing (FIO and postgres) with a few different RAID controllers and HW RAID vs mdadm. We (micron) are crucial but I don’t personally work with the consumer drives.

 

Verify whether you have your disk write cache enabled or disabled. If it’s disabled, that will have a large impact on write performance. 

Is this the *exact* string you used? `fio --filename=/dev/sdx --direct=1 --rw=randrw --refill_buffers --norandommap --randrepeat=0 --ioengine=libaio --bs=4k --rwmixread=100 --iodepth=16 --numjobs=16 --runtime=60 --group_reporting --name=4ktest`

 

With FIO, you need to multiply iodepth by numjobs to get the final queue depth its pushing. (in this case, 256). Make sure you’re looking at the correct data.

Few other things:

-          Mdadm will give better performance than HW RAID for specific benchmarks.

-          Performance is NOT linear with drive count for synthetic benchmarks.

-          It is often nearly linear for application performance.

-          HW RAID can give better performance if your drives do not have a capacitor backed cache (like the MX300) AND the controller has a battery backed cache. *Consumer drives can often get better performance from HW RAID*. (otherwise MDADM has been faster in all of my testing)

-          Mdadm RAID10 has a bug where reads are not properly distributed between the mirror pairs. (It uses head position calculated from the last IO to determine which drive in a mirror pair should get the next read. It results in really weird behavior of most read IO going to half of your drives instead of being evenly split as should be the case for SSDs).  You can see this by running iostat while you’ve got a load running and you’ll see uneven distribution of IOs. FYI, the RAID1 implementation has an exception where it does NOT use head position for SSDs. I have yet to test this but you should be able to get better performance by manually striping a RAID0 across multiple RAID1s instead of using the default RAID10 implementation.

-          Don’t focus on 4k Random Read. Do something more similar to a PG workload (64k 70/30 R/W @ QD=4 is *reasonably* close to what I see for heavy OLTP).

I’ve tested multiple controllers based on the LSI 3108 and found that default settings from one vendor to another provide drastically different performance profiles. Vendor A had much better benchmark performance (2x IOPS of B) while vendor B gave better application performance (20% better OLTP performance in Postgres). (I got equivalent performance from A & B when using the same settings). 

You might need to increase the number of jobs here. The primary reason for this parameter is to improve scaling when you’re single thread CPU bound. With numjob=1 FIO will use only a single thread and there’s only so much a single CPU core can do.

I was a little unclear on the disk cache part. It’s a setting, generally in the RAID controller / HBA. It’s also a filesystem level option in Linux (hdparm) and Windows (somewhere in device manager?). The reason to disable the disk cache is that it’s NOT protected against power loss protection on the MX300. So by disabling it you can ensure 100% write consistency at the cost of write performance. (using fully power protected drives will let you keep disk cache enabled)

> Why 64k and QD=4? I thought of 8k and larger QD. Will test as soon as possible and report here the results :)

 

It’s more representative of what you’ll see at the application level. (If you’ve got a running system, you can just use IOstat to see what your average QD is. (iostat -x 10, and it’s the column: avgqu-sz. Change from 10 seconds to whatever interval works best for your environment)

> Do you have some HBA card to suggest? What do you think of LSI SAS3008? I think it’s the same as the 3108 without RAID On Chip feature. Probably I will buy a Lenovo HBA card with that chip. It seems blazing fast (1mln IOPS) compared to the actual embedded RAID controller (LSI 2008).

 

I’ve been able to consistently get the same performance out of any of the LSI based cards. The 3008 and 3108 both work great, regardless of vendor. Just test or read up on the different configuration parameters (read ahead, write back vs write through, disk cache)