Capacity vs. Performance: De-duplication

      5 Comments on Capacity vs. Performance: De-duplication

This is the 3rd part of a multi-part discussion on capacity vs performance in SAN environments.  My previous post discussed the use of thin provisioning to increase storage utilization.  Today we are going to focus on a newer technology called Data De-Duplication.

Data De-Duplication can be likened to an advanced form of compression.  It is a way to store large amounts of data with the least amount of physical disk possible.

De-duplication technology was originally targeted at lowering the cost of disk-based backup.  DataDomain (recently acquired by EMC Corp) was a pioneer in this space.  Each vendor has their own implementation of de-duplication technology but they are generally similar in that they take raw data, look for similarities in relatively small chunks of that data and remove the duplicates.  The diagram below is the simplest one I could find on the web.  You can see that where there were multiple C, D, B, etc blocks in the original data, the final “de-duplicated” data has only one of each.  The system then stores metadata (essentially pointers) to track what the original data looked like for later reconstruction.

Image from eWeek Article

The first and most widely used implementations of de-dupe technology were in the backup space where much of the same data is being backed up during each backup cycle and many days of history (retention) must be maintained.  Compression ratios using de-duplication alone can easily exceed 10:1 in backup systems.  The neat thing here is that when the de-duplication technology works at the block-level (rather than file-level) duplicate data is found across completely disparate data-sets.  There is commonality between Exchange email, Microsoft Word, and SQL data for example.  In a 24 hour period, backing up 5.7TB of data to disk, the de-dupe ratio in my own backup environment is 19.2X plus an additional 1.7X of standard compression on the post de-dupe’d data, consuming only 173.9GB of physical disk space.  The entire set of backed up data, totaling 106TB currently stored on disk, consumes only 7.5TB of physical disk.  The benefits are pretty obvious as you can see how we can store large amounts of data in much less physical disk space.

There are numerous de-duplication systems available for backup applications — DataDomain, Quantum DXi, EMC DL3D, NetApp VTL, IBM Diligent, and several others.  Most of these are “target-based” de-duplication systems because they do all the work at the storage layer with the primary benefit being better use of disk space.  They also integrate easily into most traditional backup environments.  There are also “source-based” de-duplication systems — EMC Avamar and Symantec PureDisk are two primary examples.  These systems actually replace your existing backup application entirely and perform their work on the client machine that is being backed up.  They save disk space just like the other systems but also reduce bandwidth usage during the backup which is extremely useful when trying to get backups of data across a slow network connection like a WAN.

So now you know why de-duplication is good, and how it helps in a backup environment.. But what about using it for primary storage like NAS/SAN environments?  Well it turns out several vendors are playing in that space as well.  NetApp was the first major vendor to add de-duplication to primary storage with their A-SIS (Advanced Single Instance Storage) product.  EMC followed with their own implementation of de-duplication on Celerra NAS.  They are entirely different in their implementation but attempt to address the same problem of ballooning storage requirements.

EMC Celerra de-dupe performs file-level single-instancing to eliminate duplicate files in a filesystem, and then uses a proprietary compression engine to reduce the size of the files themselves.  Celerra does not deal with portions of files.  In practice, this feature can significantly reduce the storage requirements for a NAS volume.  In a test I performed recently for storing large amounts of Syslog data, Celerra de-dupe easily saved 90% of the disk space consumed by the logs and it hadn’t actually touched all of the files yet.

NetApp’s A-SIS works at a 4KB block size and compares all data within a filesystem regardless of the data type.  Besides NAS shares, A-SIS also works on block volumes (ie: FiberChannel and iSCSI LUNs) where EMC’s implementation does not.  Celerra has an advantage when working with files which contain high amounts of duplication in very small block sizes (like 50 bytes) since NetApp looks at 4KB chunks.  Celerra’s use of a more traditional compression engine saves more space in the syslog scenario but NetApp’s block level approach could save more space than Celerra when dealing with lots of large files.

The ability to work on traditional LUNs presents some interesting opportunities, especially in a VMWare/Hyper-V environment.  As I mentioned in my previous post, virtual environments have lots of redundant data since there are many systems potentially running the same operating system sharing the disk subsystem.  If you put 10 Windows virtual machines on the same LUN, de-duplication will likely save you tons of disk space on that LUN.  There are limitations to this that prevent the full benefits from being realized.  VMWare best practices require you to limit the number of virtual machine disks sharing the same SAN lun for performance reasons (VMFS locking issues) and A-SIS can only de-dupe data within a LUN but not across multiple LUNs.  So in a large environment your savings are limited.  NetApp’s recommendation is to use NFS NAS volumes for VMWare instead of FC or iSCSI LUNs because you can eliminate the VMFS locking issue and place many VMs on a single very large NFS volume which can then be de-duplicated.  Unfortunately there are limits on certain VMWare features when using NFS so this may not be an option for some applications or environments.  Specifically, VMWare Site Recovery Manager which coordinates site-to-site replication and failover of entire VMWare environments does not currently support NFS as of this writing.

When it comes to de-duplication’s impact on performance it’s kind of all over the map.  In backup applications, most target based systems either perform the work in memory while the data is coming in or as a post-process job that runs when the backups for that day have completed.  In either case, the hardware is designed for high throughput and performance is not really a problem.  For primary data, both EMC and NetApp’s implementations are post-process and do not generally impact write performance.  However, EMC has limitations on the size of files that can be de-duplicated before a modification to a compressed file causes a significant delay.  Since they also limit de-duplication to files that have not been accessed or modified for some period of time, the problem is minimal in most environments.  NetApp claims to have little performance impact to either read or writes when using A-SIS.  This has much to do with the architecture of the NetApp WAFL filesystem and how A-SIS interacts with it but it would take an entirely new post to describe how that all works.  Suffice it to say that NetApp A-SIS is useful in more situations than EMC’s Celerra De-duplication.

Where I do see potential problems with performance regardless of the vendor is in the same situation as thin provisioning.  If your application requires 1000 IOPS but you’ve only got 2 disks in the array because of the disk space savings from thin-provisioning and/or de-duplication, the application performance will suffer.  You still need to service the IOPS and each disk has a finite number of IOPS (100-200 generally for FC/SCSI).  Flash/SSD changes the situation dramatically however.

Right now I believe that de-duplication is extremely useful for backups, but not quite ready for prime-time when it comes to primary storage.  There are just too many caveats to make any general recommendations.  If you happen to purchase an EMC Celerra or NetApp FAS/IBM nSeries that supports de-duplication, make sure to read all the best-practices documentation from the vendor and make a decision on whether your environment can use de-duplication effectively, then experiment with it in a lab or dev/test environment.  It could save you tons of disk space and money or it could be more trouble than it’s worth.  The good thing is that it’s pretty much a free option from EMC and NetApp depending on the hardware you own/purchase and your maintenance agreements.

5 thoughts on “Capacity vs. Performance: De-duplication

  1. Michael McMorrow

    Hi! This is an excellent blog entry. One question. You say, “…and A-SIS can only de-dupe data within a LUN but not across multiple LUNs.”. I can’t find any documentation that supports this statement. However, based on my own testing, I believe that you are correct. Can you point me to any documentation that supports your statement? Thank you!

    1. storagesavvy

      NetApp document TR-3505 describes deduplication in OnTap pretty well. They never really state that “deduplication only works within a single volume” but they imply it with statements like “Deduplication is enabled on a per flexible volume basis” on page 7 and “It operates on the active file system of the flexible volume” on page 4.

  2. Michael McMorrow

    I think we’re using different terminology. I know that deduplication works at the volume (FlexVol) level. LUNs are created within FlexVols. I thought you were referring to an instance in which multiple LUNs are created within a single FlexVol. I guess you were using the term LUN and Volume interchangably. Does that sound right? Thanks for the quick reply, and for the reference to the documentation.

    1. storagesavvy

      No problem..

      If there are multiple LUNs in a single FlexVol, deduplication should work across all of the LUNs in that FlexVol. LUNs are treated the same as files in a NetApp volume (FlexVol). Depending on the use case you may want to have only 1 LUN per FlexVol (or if your data exceeds the maximum size of a FlexVol you would have to). Since deduplication only works on files/LUNs inside a particular FlexVol, the efficiency may fall as you grow.

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