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Erasure Coding

MinIO Erasure Coding is a data redundancy and availability feature that allows MinIO deployments to automatically reconstruct objects on-the-fly despite the loss of multiple drives or nodes in the cluster. Erasure Coding provides object-level healing with less overhead than adjacent technologies such as RAID or replication.

Erasure Coding splits objects into data and parity blocks, where parity blocks support reconstruction of missing or corrupted data blocks. MinIO distributes both data and parity blocks across minio server nodes and drives in an Erasure Set. Depending on the configured parity, number of nodes, and number of drives per node in the Erasure Set, MinIO can tolerate the loss of up to half (N/2) of drives and still retrieve stored objects.

For example, consider a small-scale MinIO deployment consisting of a single Server Pool with 4 minio server nodes. Each node in the deployment has 4 locally attached 1Ti drives for a total of 16 drives.

MinIO creates Erasure Sets by dividing the total number of drives in the deployment into sets consisting of between 4 and 16 drives each. In the example deployment, the largest possible Erasure Set size that evenly divides into the total number of drives is 16.

MinIO uses a Reed-Solomon algorithm to split objects into data and parity blocks based on the size of the Erasure Set. MinIO then uniformly distributes the data and parity blocks across the Erasure Set drives such that each drive in the set contains no more than one block per object. MinIO uses the EC:N notation to refer to the number of parity blocks (N) in the Erasure Set.

The number of parity blocks in a deployment controls the deployment’s relative data redundancy. Higher levels of parity allow for higher tolerance of drive loss at the cost of total available storage. For example, using EC:4 in our example deployment results in 12 data blocks and 4 parity blocks. The parity blocks take up some portion of space in the deployment, reducing total storage. However, the parity blocks allow MinIO to reconstruct the object with only 8 data blocks, increasing resilience to data corruption or loss.

The following table lists the outcome of varying EC levels on the example deployment:

Outcome of Parity Settings on a 16 Drive MinIO Cluster

Parity

Total Storage

Storage Ratio

Minimum Drives for Read Operations

Minimum Drives for Write Operations

EC: 4 (Default)

12 Tebibytes

0.750

12

13

EC: 6

10 Tebibytes

0.625

10

11

EC: 8

8 Tebibytes

0.500

8

9

Erasure Sets

An Erasure Set is a set of drives in a MinIO deployment that support Erasure Coding. MinIO evenly distributes object data and parity blocks among the drives in the Erasure Set.

MinIO calculates the number and size of Erasure Sets by dividing the total number of drives in the Server Pool into sets consisting of between 4 and 16 drives each. MinIO considers two factors when selecting the Erasure Set size:

  • The Greatest Common Divisor (GCD) of the total drives.

  • The number of minio server nodes in the Server Pool.

For an even number of nodes, MinIO uses the GCD to calculate the Erasure Set size and ensure the minimum number of Erasure Sets possible. For an odd number of nodes, MinIO selects a common denominator that results in an odd number of Erasure Sets to facilitate more uniform distribution of erasure set drives among nodes in the Server Pool.

For example, consider a Server Pool consisting of 4 nodes with 8 drives each for a total of 32 drives. The GCD of 16 produces 2 Erasure Sets of 16 drives each with uniform distribution of erasure set drives across all 4 nodes.

Now consider a Server Pool consisting of 5 nodes with 8 drives each for a total of 40 drives. Using the GCD, MinIO would create 4 erasure sets with 10 drives each. However, this distribution would result in uneven distribution with one node contributing more drives to the Erasure Sets than the others. MinIO instead creates 5 erasure sets with 8 drives each to ensure uniform distribution of Erasure Set drives per Nodes.

MinIO generally recommends maintaining an even number of nodes in a Server Pool to facilitate simplified human calculation of the number and size of Erasure Sets in the Server Pool.

Erasure Code Parity (EC:N)

MinIO uses a Reed-Solomon algorithm to split objects into data and parity blocks based on the size of the Erasure Set. MinIO uses parity blocks to automatically heal damaged or missing data blocks when reconstructing an object. MinIO uses the EC:N notation to refer to the number of parity blocks (N) in the Erasure Set.

MinIO uses a hash of an object’s name to determine into which Erasure Set to store that object. MinIO always uses that erasure set for objects with a matching name. For example, MinIO stores all versions of an object in the same Erasure Set.

After MinIO selects an object’s Erasure Set, it divides the object based on the number of drives in the set and the configured parity. MinIO creates:

  • (Erasure Set Drives) - EC:N Data Blocks, and

  • EC:N Parity Blocks.

MinIO randomly and uniformly distributes the data and parity blocks across drives in the erasure set with no overlap. While a drive may contain both data and parity blocks for multiple unique objects, a single unique object has no more than one block per drive in the set. For versioned objects, MinIO selects the same drives for both data and parity storage while maintaining zero overlap on any single drive.

The specified parity for an object also dictates the minimum number of Erasure Set drives (“Quorum”) required for MinIO to either read or write that object:

Read Quorum

The minimum number of Erasure Set drives required for MinIO to serve read operations. MinIO can automatically reconstruct an object with corrupted or missing data blocks if enough drives are online to provide Read Quorum for that object.

MinIO Read Quorum is DRIVES - (EC:N).

Write Quorum

The minimum number of Erasure Set drives required for MinIO to serve write operations. MinIO requires enough available drives to eliminate the risk of split-brain scenarios.

MinIO Write Quorum is (DRIVES - (EC:N)) + 1.

Storage Classes

MinIO supports storage classes with Erasure Coding to allow applications to specify per-object parity. Each storage class specifies a EC:N parity setting to apply to objects created with that class.

MinIO storage classes are distinct from Amazon Web Services storage classes. MinIO storage classes define parity settings per object, while AWS storage classes define storage tiers per object.

MinIO provides the following two storage classes:

STANDARD

The STANDARD storage class is the default class for all objects.

You can configure the STANDARD storage class parity using either:

Starting with RELEASE.2021-01-30T00-20-58Z, MinIO defaults STANDARD storage class based on the number of volumes in the Erasure Set:

Erasure Set Size

Default Parity (EC:N)

5 or Fewer

EC:2

6 - 7

EC:3

8 or more

EC:4

The maximum value is half of the total drives in the Erasure Set.

STANDARD parity must be greater than or equal to REDUCED_REDUNDANCY. If REDUCED_REDUNDANCY is unset, STANDARD parity must be greater than 2

REDUCED_REDUNDANCY

The REDUCED_REDUNDANCY storage class allows creating objects with lower parity than STANDARD.

You can configure the REDUCED_REDUNDANCY storage class parity using either:

The default value is EC:2.

REDUCED_REDUNDANCY parity must be less than or equal to STANDARD. If STANDARD is unset, REDUCED_REDUNDANCY must be less than half of the total drives in the Erasure Set.

REDUCED_REDUNDANCY is not supported for MinIO deployments with 4 or fewer drives.

MinIO references the x-amz-storage-class header in request metadata for determining which storage class to assign an object. The specific syntax or method for setting headers depends on your preferred method for interfacing with the MinIO server.

  • For the mc command line tool, certain commands include a specific option for setting the storage class. For example, the mc cp command has the --storage-class option for specifying the storage class to assign to the object being copied.

  • For MinIO SDKs, the S3Client object has specific methods for setting request headers. For example, the minio-go SDK S3Client.PutObject method takes a PutObjectOptions data structure as a parameter. The PutObjectOptions data structure includes the StorageClass option for specifying the storage class to assign to the object being created.

BitRot Protection

Silent data corruption or bitrot is a serious problem faced by disk drives resulting in data getting corrupted without the user’s knowledge. The reasons are manifold (ageing drives, current spikes, bugs in disk firmware, phantom writes, misdirected reads/writes, driver errors, accidental overwrites) but the result is the same - compromised data.

MinIO’s optimized implementation of the HighwayHash algorithm ensures that it will never read corrupted data - it captures and heals corrupted objects on the fly. Integrity is ensured from end to end by computing a hash on READ and verifying it on WRITE from the application, across the network and to the memory/drive. The implementation is designed for speed and can achieve hashing speeds over 10 GB/sec on a single core on Intel CPUs.