The Quick and Dirty Deduplication Analyzer

The best thing about being me… There are so many “me”s.

— Agent Smith, The Matrix Reloaded

One of our customers reported less than optimal space savings on XtremIO running Oracle. In order to test various scenarios with Oracle I was in search of a deduplication analysis method or tool – only to find out that there was nothing available that qualified.

TL;DR: QDDA is an Open Source tool I wrote to analyze Linux files, devices or data streams for duplicate blocks and compression estimates. It can quickly give you an idea of how much storage savings you could get using a modern All-Flash Array like XtremIO. It is safe to use on production systems and allows quick analysis of various test scenarios giving direct results, and even works with files/devices that are in use. No registration or uploading of your confidential data is required.

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Oracle ASM vs ZFS on XtremIO

zfs-asm-plateBackground

In my previous post on ZFS I showed how ZFS causes fragmentation for Oracle database files. At the end I promised (sort of) to also come back on topic around how this affects database performance. In the meantime I have been busy with many other things, but ZFS issues still sneak up on me frequently. Eventually, I was forced to take another look at this because of two separate customers asking for ZFS comparisons agaisnt ASM at the same time.

The account team for one of the two customers asked if I could perform some testing on their lab environment to show the performance difference between Oracle on ASM and on ZFS. As things happen in this business, things were already rolling before I could influence the prerequisites and the suggested test method. Promises were already made to the customer and I was asked to produce results yesterday.

Without knowledge on the lab environment, customer requirements or even details on the test environment they had set up. Typical day at the office.

In addition to that, ZFS requires a supported host OS – so Linux is out of the question (the status on kernel ZFS for Linux is still a bit unclear and certainly it would not be supported with Oracle). I had been using FreeBSD in my post on fragmentation – because that was my platform of choice at that point (my Solaris skills are, at best, rusty). Of course Oracle on FreeBSD is a no-go so back then, I used NFS to run the database on Linux and ZFS on BSD. Which implicitly solves some of the potential issues whilst creating some new ones, but alas.

Solaris x86

slob-rules-kenteken
This time the idea was to run Oracle on Solaris (x86) that had both ZFS and ASM configured. How to perform a reasonable comparison that also shows the different behavior was unclear and when asking that question to the account team, the conference call line stayed surprisingly silent. All that they indicated up front is that the test tool on Oracle should be SLOB.

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Getting the Best Oracle performance on XtremIO

XtremIO+Stack+NB+copy
(Blog repost from Virtual Storage Zone – Thanks to @cincystorage)

UPDATE: I’ll say it again because there seems to be some confusion: THIS IS A REPOST!

Original content is from the Virtual Storage Zone blog (not mine). Just reposted here because it’s interesting and related to Oracle, performance and EMC storage. Enjoy…

XtremIO is EMC’s all-flash scale out storage array designed to delivery the full performance of flash. The array is designed for 4k random I/O, low latency, inline data reduction, and even distribution of data blocks.  This even distribution of data blocks leads to maximum performance and minimal flash wear.  You can find all sorts of information on the architecture of the array, but I haven’t seen much talking about archive maximum performance from an Oracle database on XtremIO.

The nature of XtremIO ensures that’s any Oracle workload (OLTP, DSS, or Hybrid) will have high performance and low latency, however we can maximize performance with some configuration options.  Most of what I’ll be talking about is around RAC and ASM on Redhat Linux 6.x in a Fiber Channel Storage Area Network.

Read the full blogpost here.