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Chapitre 2. LVM-VDO requirements

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VDO on LVM has certain requirements on its placement and your system resources.

2.1. VDO memory requirements

Each VDO volume has two distinct memory requirements:

The VDO module

VDO requires a fixed 38 MB of RAM and several variable amounts:

  • 1.15 MB of RAM for each 1 MB of configured block map cache size. The block map cache requires a minimum of 150MB RAM.
  • 1.6 MB of RAM for each 1 TB of logical space.
  • 268 MB of RAM for each 1 TB of physical storage managed by the volume.
The UDS index

The Universal Deduplication Service (UDS) requires a minimum of 250 MB of RAM, which is also the default amount that deduplication uses. You can configure the value when formatting a VDO volume, because the value also affects the amount of storage that the index needs.

The memory required for the UDS index is determined by the index type and the required size of the deduplication window:

Index typeDeduplication windowNote

Dense

1 TB per 1 GB of RAM

A 1 GB dense index is generally sufficient for up to 4 TB of physical storage.

Sparse

10 TB per 1 GB of RAM

A 1 GB sparse index is generally sufficient for up to 40 TB of physical storage.

Note

The minimal disk usage for a VDO volume using default settings of 2 GB slab size and 0.25 dense index, requires approx 4.7 GB. This provides slightly less than 2 GB of physical data to write at 0% deduplication or compression.

Here, the minimal disk usage is the sum of the default slab size and dense index.

The UDS Sparse Indexing feature is the recommended mode for VDO. It relies on the temporal locality of data and attempts to retain only the most relevant index entries in memory. With the sparse index, UDS can maintain a deduplication window that is ten times larger than with dense, while using the same amount of memory.

Although the sparse index provides the greatest coverage, the dense index provides more deduplication advice. For most workloads, given the same amount of memory, the difference in deduplication rates between dense and sparse indexes is negligible.

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