Configuring data consistency
How up-to-date and synchronized a row of data is on all replicas.
Consistency refers to how up-to-date and synchronized a row of Cassandra data is on all of its replicas. Cassandra extends the concept of eventual consistency by offering tunable consistency―for any given read or write operation, the client application decides how consistent the requested data should be.
In addition to tunable consistency, Cassandra has a number of built-in repair mechanisms to ensure that data remains consistent across replicas.
Tunable consistency for client requests
Consistency levels in Cassandra can be configured to manage response time versus data accuracy. You can configure consistency on a cluster, data center, or individual I/O operation basis. Very strong or eventual consistency among participating nodes can be set globally and also controlled on a per-operation basis (for example insert or update) using Cassandra’s drivers and client libraries.
About write consistency
The consistency level specifies the number of replicas on which the write must succeed before returning an acknowledgment to the client application.
| Level | Description | Usage |
|---|---|---|
| ANY | A write must be written to at least one node. If all replica nodes for the given row key are down, the write can still succeed after a hinted handoff has been written. If all replica nodes are down at write time, an ANY write is not readable until the replica nodes for that row have recovered. | Provides low latency and a guarantee that a write never fails. Delivers the lowest consistency and highest availability compared to other levels. |
| ONE | A write must be written to the commit log and memory table of at least one replica node. | Satisfies the needs of most users because consistency requirements are not stringent. The replica node closest to the coordinator node that received the request serves the request (unless the dynamic snitch determines that the node is performing poorly and routes it elsewhere). |
| TWO | A write must be written to the commit log and memory table of at least two replica nodes. | Similar to ONE. |
| THREE | A write must be written to the commit log and memory table of at least three replica nodes. | Similar to TWO. |
| QUORUM | A write must be written to the commit log and memory table on a quorum of replica nodes. |
Provides strong consistency if you can tolerate some level of failure. |
| LOCAL_ONE | Available in Cassandra 1.2.11 and later. A write must be sent to, and successfully acknowledged by, at least one replica node in the local datacenter. | In a multiple data center clusters, a consistency level of ONE is often desirable, but cross-DC traffic is not. LOCAL_ONE accomplishes this. For security and quality reasons, you can use this consistency level in an offline datacenter to prevent automatic connection to online nodes in other data centers if an offline node goes down. |
| LOCAL_QUORUM | A write must be written to the commit log and memory table on a quorum of replica nodes in the same data center as the coordinator node. Avoids latency of inter-data center communication. | Used in multiple data center clusters with a rack-aware replica placement strategy ( NetworkTopologyStrategy) and a properly configured snitch. Fails when using SimpleStrategy. Use to maintain consistency at locally (within the single data center). |
| EACH_QUORUM | A write must be written to the commit log and memory table on a quorum of replica nodes in all data centers. | Used in multiple data center clusters to strictly maintain consistency at the same level in each data center. For example, choose this level if you want a read to fail when a data center is down and the QUORUM cannot be reached on that data center. |
| ALL | A write must be written to the commit log and memory table on all replica nodes in the cluster for that row. | Provides the highest consistency and the lowest availability of any other level. |
Even at consistency level ONE or LOCAL_QUORUM, the write is still sent to all replicas for the written key, even replicas in other data centers. The consistency level just determines how many replicas are required to respond that they received the write.
About read consistency
The consistency level specifies how many replicas must respond to a read request before returning data to the client application.
Cassandra checks the specified number of replicas for the most recent data, based on the timestamp, to satisfy the read request.
| Level | Description | Usage |
|---|---|---|
| ONE | Returns a response from the closest replica, as determined by the snitch. By default, a read repair runs in the background to make the other replicas consistent. | Provides the highest availability of all the levels if you can tolerate a comparatively high probability of stale data being read. The replicas contacted for reads may not always have the most recent write. |
| TWO | Returns the most recent data from two of the closest replicas. | Similar to ONE. |
| THREE | Returns the most recent data from three of the closest replicas. | Similar to TWO. |
| QUORUM | Returns the record with the most recent timestamp after a quorum of replicas has responded. | Ensures strong consistency if you can tolerate some level of failure. |
| LOCAL_ONE | Available in Cassandra 1.2.11 and later. Returns a response from the closest replica, as determined by the snitch, but only if the replica is within the local data center. | Same usage as described in the table about write consistency levels. |
| LOCAL_QUORUM | Returns the record with the most recent timestamp once a quorum of replicas in the current data center as the coordinator node has reported. Avoids latency of inter-data center communication. | Used in multiple data center clusters with a rack-aware replica placement strategy ( NetworkTopologyStrategy) and a properly configured snitch. Fails when using SimpleStrategy. |
| EACH_QUORUM | Returns the record with the most recent timestamp once a quorum of replicas in each data center of the cluster has responded. | Same as LOCAL_QUORUM |
| ALL | Returns the record with the most recent timestamp after all replicas have responded. The read operation will fail if a replica does not respond. | Provides the highest consistency of all levels and the lowest availability of all levels. |
About the QUORUM levels
The QUORUM level writes to the number of nodes that make up a quorum. A quorum is calculated, and then rounded down to a whole number, as follows:
(replication_factor / 2) + 1
For example, using a replication factor of 3, a quorum is 2 nodes―the cluster can tolerate 1 replica down. Using a replication factor of 6, a quorum is 4―the cluster can tolerate 2 replicas down.
If consistency is top priority, you can ensure that a read always reflects the most recent write by using the following formula:
(nodes_written + nodes_read) > replication_factor
For example, if your application is using the QUORUM consistency level for both write and read operations and you are using a replication factor of 3, then this ensures that 2 nodes are always written and 2 nodes are always read. The combination of nodes written and read (4) being greater than the replication factor (3) ensures strong read consistency.
Configuring client consistency levels
You can use a new cqlsh command, CONSISTENCY , to set the consistency level for the keyspace. The WITH CONSISTENCY clause has been removed from CQL 3 commands in the release version of CQL 3. Programmatically, set the consistency level at the driver level. For example, call execute_cql3_query with the required binary query, the compression settings, and consistency level. The consistency level defaults to ONE for all write and read operations.
About built-in consistency repair features
You can use these built-in repair utilities to ensure that data remains consistent across replicas.