Partitioners
A partitioner determines how data is distributed across the nodes in the cluster (including replicas).
A partitioner is a function for deriving a token representing a row from its partition key, typically by hashing. Each row of data is then distributed across the cluster by the value of the token. Any IPartitioner may be used, including your own, as long as it is in the classpath.
The default Murmur3Partitioner
uses tokens to help assign equal portions of data to each node and evenly distribute data from all the tables throughout the ring or other grouping, such as a keyspace.
This is true even if the tables use different partition keys, such as user names or timestamps.
Because each part of the hash range receives an equal number of rows on average, the read and write requests to the cluster are evenly distributed and load balancing is simplified.
For more information, see Consistent hashing.
Whether or not you need assign tokens to each node depends on the type of architecture:
-
Virtual nodes: Use either the allocation algorithm or the random selection algorithm to specify the number of tokens distributed to nodes within the datacenter. All systems in the datacenter must use the same algorithm.
-
Single-token architecture: To ensure data is evenly divided across the nodes in the cluster, you must enter values in the
initial_token
parameter in the cassandra.yaml file for each node. To determine the token value, see Calculating tokens for single-token architecture nodes.
Types of partitioners
Be aware that partitioners are not compatible with each other. Data partitioned with one partitioner cannot be easily converted to the other partitioner. |
DataStax Enterprise supplies the following partitioners:
Murmur3Partitioner
(default)-
Uniformly distributes data across the cluster based on MurmurHash hash values. This hashing function creates a 64-bit hash value of the partition key with a possible range from -263 to +263-1. This partitioner is the right choice for new clusters in almost all cases and is 3 to 5 times more performant than the
RandomPartitioner
.When using this partitioner, you can page through all rows using the token function in a CQL query.
RandomPartitioner
-
This partitioner is included for backwards compatibility. It uniformly distributes data evenly across the nodes using an MD5 hash value of the row key. The possible range of hash values is from 0 to 2127 -1. Because it uses a cryptographic hash, which isn’t required by the database, it takes longer to generate the hash value than the
Murmur3Partitioner
.When using this partitioner, you can page through all rows using the token function in a CQL query.
ByteOrderedPartitioner
-
This partitioner is included for backwards compatibility. This partitioner orders rows lexically by key bytes. It is not recommended because it requires significant administrative overhead to load balance the cluster, sequential writes can cause hot spots, and balancing for one table can result in uneven distribution for another table in the same cluster.
DataStax recommends using the default partitioner, Murmur3Partitioner
.
You can change the partitioner in the cassandra.yaml
file.