Deduplication

How Deduplication Works

ZFS deduplication is a feature that eliminates duplicate copies of data at the block level to save disk space. When deduplication is enabled, ZFS compares the checksum of each data block being written against the checksums of all previously written blocks. If a match is found, ZFS stores a reference to the existing block instead of writing the data again.

ZFS uses cryptographic checksums (usually SHA-256) to detect duplicates. Each time data is written, ZFS checks whether a block with the same checksum already exists in the deduplication table (dedup table or DDT). If the block is unique, it is written to disk, and its checksum is added to the DDT. If the block already exists, only a reference is added, and no additional data is written to the disk.

Enabling deduplication is done at the dataset level, as follows:

zfs set dedup=on mypool/mydataset

However, it's important to note that ZFS deduplication is memory-intensive, as the entire deduplication table must be kept in memory to avoid significant performance penalties. If the DDT grows too large to fit in RAM, ZFS must read from the disk, severely impacting performance.

Pros and Cons of Deduplication

Pros of Deduplication:

1. Space Savings: The primary benefit of deduplication is reduced storage usage, especially in environments with many identical blocks of data. This is particularly useful in backup systems, virtual machine storage, and other environments where duplicate data is common.

2. Efficient Backup and Virtualization: For environments where multiple copies of similar or identical data are stored (e.g., VM images, databases, or backups), deduplication can result in significant space savings. As many identical blocks are not rewritten, storage requirements are reduced.

3. Snapshot Efficiency: Deduplication can work well with ZFS snapshots by reducing storage usage even further. Blocks that are deduplicated across snapshots reduce storage costs because only unique data across snapshots is stored.

Cons of Deduplication:

1. Memory Usage: One of the biggest drawbacks of deduplication is its high memory requirement. For optimal performance, a large amount of RAM is necessary to store the deduplication table (DDT). ZFS's deduplication is most efficient when the DDT fits entirely in memory, with the rule of thumb being about 5 GB of RAM per 1 TB of deduplicated data.

2. Performance Impact: If the deduplication table exceeds available memory, ZFS will need to access the DDT from disk, significantly slowing down both read and write operations. This performance penalty can make deduplication impractical in environments where memory is limited or where performance is a higher priority than space savings.

3. Complexity: Deduplication adds complexity to data management. The size of the DDT grows with the amount of unique data in the pool, which can make long-term performance tuning and planning difficult.

4. Irreversibility: Once data has been written with deduplication enabled, the deduplication process cannot be undone unless the data is copied to a non-deduplicated dataset. This can complicate storage management if deduplication is enabled without careful planning.