Unless instructed by authorized Microsoft Support Personnel, do not attempt to manually modify the chunk store. Doing so may result in data corruption or loss.
How does Data Deduplication differ from other optimization products? There are several important differences between Data Deduplication and other common storage optimization products:.
To optimize a volume, Single Instance Store identified files that were completely identical and replaced them with logical links to a single copy of a file that's stored in the SIS common store. Unlike Single Instance Store, Data Deduplication can get space savings from files that are not identical but share many common patterns and from files that themselves contain many repeated patterns. With NTFS compression, each file is optimized individually via compression at write-time.
This is better than NTFS compression because files may have both internal duplication which is addressed by NTFS compression and have similarities with other files on the volume which is not addressed by NTFS compression. Additionally, Data Deduplication has a post-processing model, which means that new or modified files will be written to disk unoptimized and will be optimized later by Data Deduplication.
How does Data Deduplication differ from archive file formats like zip, rar, 7z, cab, etc.? Archive file formats, like zip, rar, 7z, cab, etc. Like Data Deduplication, duplicated patterns within files and duplicated patterns across files are optimized. However, you have to choose the files that you want to include in the archive. Access semantics are different, too. To access a specific file within the archive, you have to open the archive, select a specific file, and decompress that file for use.
Data Deduplication operates transparently to users and administrators and requires no manual kick-off. Additionally, Data Deduplication preserves access semantics: optimized files appear unchanged after optimization.
Although Data Deduplication provides reasonable defaults for Recommended workloads , you might still want to tweak Data Deduplication settings to get the most out of your storage. Additionally, other workloads will require some tweaking to ensure that Data Deduplication does not interfere with the workload. Can I manually run a Data Deduplication job? Yes, all Data Deduplication jobs may be run manually. This may be desirable if scheduled jobs did not run due to insufficient system resources or because of an error.
Additionally, the Unoptimization job can only be run manually. Can I monitor the historical outcomes of Data Deduplication jobs? Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support. Feedback will be sent to Microsoft: By pressing the submit button, your feedback will be used to improve Microsoft products and services. Privacy policy. This topic explains how to install Data Deduplication , evaluate workloads for deduplication, and enable Data Deduplication on specific volumes.
If you're planning to run Data Deduplication in a Failover Cluster, every node in the cluster must have the Data Deduplication server role installed. KB contains a roll up of fixes for Data Deduplication, including important reliability fixes, and we strongly recommend installing it when using Data Deduplication with Windows Server Data Deduplication can effectively minimize the costs of a server application's data consumption by reducing the amount of disk space consumed by redundant data.
Before enabling deduplication, it is important that you understand the characteristics of your workload to ensure that you get the maximum performance out of your storage. There are two classes of workloads to consider:. If you are running a recommended workload, you can skip this section and go to Enable Data Deduplication for your workload. To determine whether a workload works well with deduplication, answer the following questions. If you're unsure about a workload, consider doing a pilot deployment of Data Deduplication on a test dataset for your workload to see how it performs.
Does my workload's dataset have enough duplication to benefit from enabling deduplication? DDPEval can evaluate the potential for optimization against directly connected volumes including local drives or Cluster Shared Volumes and mapped or unmapped network shares.
Running DDPEval. All Rights Reserved. What performance do I have for my workload? Data Deduplication optimizes files as a periodic job, rather than when the file is written to disk. As a result, it is important to examine is a workload's expected read patterns to the deduplicated volume.
Because Data Deduplication moves file content into the Chunk Store and attempts to organize the Chunk Store by file as much as possible, read operations perform best when they are applied to sequential ranges of a file. Database-like workloads typically have more random read patterns than sequential read patterns because databases do not typically guarantee that the database layout will be optimal for all possible queries that may be run.
Because the sections of the Chunk Store may exist all over the volume, accessing data ranges in the Chunk Store for database queries may introduce additional latency. High performance workloads are particularly sensitive to this extra latency, but other database-like workloads might not be. Dec 20, Jan 9, The link is not working. Jul 4, May 13, Jun 13, Jul 1, Mar 3, Sep 6, Apr 13, Apr 30, Feb 18, Apr 17, Aug 13, Mar 14, Feb 27, Jan 10, Apr 24,
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