Best practices for rack and node setup for EC

In a Cloudera Private Cloud Base deployment, when setting up a cluster to take advantage of EC, consider the number of racks and nodes in your setup.

Ideally, the number of racks exceed the data-stripe width to account for downtime and outages. If there are fewer racks than the data-stripe width, HDFS spreads data blocks across multiple nodes to maintain fault tolerance at the node level. When distributing blocks to racks, HDFS attempts to distribute the blocks evenly across all racks. Because of this behavior, Cloudera recommends setting up each rack with a similar number of DataNodes. Otherwise, racks with fewer DataNodes may be filled up faster than racks with more DataNodes.

To achieve node-level fault tolerance, the number of nodes needs to equal the data-stripe width. For example, in order for a RS-6-3-1024k policy to be node failure tolerant, you need at least nine nodes. Note that the write will fail if the number of DataNodes is less than the policy's number of data blocks. The write will succeed but show a warning message if the number of DataNodes is less than the policy's number of data blocks + parity blocks. For example, with RS(6,3), if there are six to eight DataNodes, the write will succeed but show a warning message. If there are less than six DataNodes, the write fails.

For rack-level fault tolerance, there must be enough number of racks such that each rack contains at most the same number of blocks as the erasure coding parity blocks. The number of racks is calculated as (data stripe width) / (number of parity blocks). For example, with RS(6,3), the minimum number of racks must be (6+3)/3 = 3. Cloudera recommends at least nine racks, which leads to one data or parity block on each rack. Ideally, the number of racks exceeds the sum of the number of data and parity blocks.

A policy with a wide data-stripe width like RS-6-3-1024k comes with a tradeoff though. Data must be read from six blocks, increasing the overall network load. Choose your EC policy based on your network settings and expected storage efficiency. Note, the larger the cluster and colder the data, the more appropriate it is to use EC policies with large data-stripe widths. Larger data-stripe widths have the benefit of a better storage efficiency.