Load balancing

Quick overview

Which nodes the driver talks to, and in which order they are tried.

  • basic.load-balancing-policy in the configuration.
  • defaults to DefaultLoadBalancingPolicy (opinionated best practices).
  • can have per-profile policies.

A Cassandra cluster is typically composed of multiple nodes; the load balancing policy (sometimes abbreviated LBP) is a central component that determines:

  • which nodes the driver will communicate with;
  • for each new query, which coordinator to pick, and which nodes to use as failover.

It is defined in the configuration:

datastax-java-driver.basic.load-balancing-policy {
  class = DefaultLoadBalancingPolicy


Node distance

For each node, the policy computes a distance that determines how connections will be established:

  • LOCAL and REMOTE are “active” distances, meaning that the driver will keep open connections to this node. Connection pools can be sized independently for each distance.
  • IGNORED means that the driver will never attempt to connect.

Typically, the distance will reflect network topology (e.g. local vs. remote datacenter), although that is entirely up to each policy implementation. It can also change over time.

Query plan

Each time the driver executes a query, it asks the policy to compute a query plan, in other words a list of nodes. The driver then tries each node in sequence, moving down the plan according to the retry policy and speculative execution policy.

The contents and order of query plans are entirely implementation-specific, but policies typically return plans that:

  • are different for each query, in order to balance the load across the cluster;
  • only contain nodes that are known to be able to process queries, i.e. neither ignored nor down;
  • favor local nodes over remote ones.

Default policy

In previous versions, the driver provided a wide variety of built-in load balancing policies; in addition, they could be nested into each other, yielding an even higher number of choices. In our experience, this has proven to be too complicated: it’s not obvious which policy(ies) to choose for a given use case, and nested policies can sometimes affect each other’s effects in subtle and hard to predict ways.

In driver 4+, we are taking a more opinionated approach: we provide a default load balancing policy, that we consider the best choice for most cases. You can still write a custom implementation if you have special requirements.

Local only

The default policy only connects to a single datacenter. The rationale is that a typical multi-region deployment will collocate one or more application instances with each Cassandra datacenter:

Text Diagram

In previous driver versions, you could configure application-level failover, such as: “if all the Cassandra nodes in DC1 are down, allow app1 to connect to the nodes in DC2”. We now believe that this is not the right place to handle this: if a whole datacenter went down at once, it probably means a catastrophic failure happened in Region1, and the application node is down as well. Failover should be cross-region instead (handled by the load balancer in this example).

Therefore the default policy does not allow remote nodes; it only ever assigns the LOCAL or IGNORED distance. You must provide a local datacenter name, either in the configuration:

datastax-java-driver.basic.load-balancing-policy {
  local-datacenter = datacenter1

Or programmatically when building the session:

CqlSession session = CqlSession.builder()

If both are provided, the programmatic value takes precedence.

For convenience, the local datacenter name may be omitted if no contact points were provided: in that case, the driver will connect to, and use that node’s datacenter. This is just for a better out-of-the-box experience for users who have just downloaded the driver; beyond that initial development phase, you should provide explicit contact points and a local datacenter.

Finding the local datacenter

To check which datacenters are defined in a given cluster, you can run nodetool status. It will print information about each node in the cluster, grouped by datacenters. Here is an example:

$ nodetool status
Datacenter: DC1
|/ State=Normal/Leaving/Joining/Moving
--  Address    Load       Tokens  Owns  Host ID  Rack
UN  <IP1>      1.5 TB     256     ?     <ID1>    rack1
UN  <IP2>      1.5 TB     256     ?     <ID2>    rack2
UN  <IP3>      1.5 TB     256     ?     <ID3>    rack3

Datacenter: DC2
|/ State=Normal/Leaving/Joining/Moving
--  Address    Load       Tokens  Owns  Host ID  Rack
UN  <IP4>      1.5 TB     256     ?     <ID4>    rack1
UN  <IP5>      1.5 TB     256     ?     <ID5>    rack2
UN  <IP6>      1.5 TB     256     ?     <ID6>    rack3

To find out which datacenter should be considered local, you need to first determine which nodes the driver is going to be co-located with, then choose their datacenter as local. In case of doubt, you can also use cqlsh; if cqlsh is co-located too in the same datacenter, simply run the command below:

cqlsh> select data_center from system.local;



The default policy is token-aware by default: requests will be routed in priority to the replicas that own the data being queried.

Providing routing information

First make sure that token metadata is enabled.

Then your statements need to provide:

Depending on the type of statement, some of this information may be computed automatically, otherwise you have to set it manually. The examples below assume the following CQL schema:

CREATE TABLE testKs.sensor_data(id int, year int, ts timestamp, data double,
                                PRIMARY KEY ((id, year), ts));

For simple statements, routing information is never computed automatically:

SimpleStatement statement =
        "SELECT * FROM testKs.sensor_data WHERE id = 1 and year = 2016");

// No routing info available:
assert statement.getRoutingKeyspace() == null;
assert statement.getRoutingKey() == null;

// Set the keyspace manually (skip this if using a per-query keyspace):
statement = statement.setRoutingKeyspace("testKs");

// Set the routing key manually: serialize each partition key component to its target CQL type
statement = statement.setRoutingKey(
    TypeCodecs.INT.encodePrimitive(1, session.getContext().getProtocolVersion()),
    TypeCodecs.INT.encodePrimitive(2016, session.getContext().getProtocolVersion()));


For bound statements, the keyspace is always available; the routing key is only available if all components of the partition key are bound as variables:

// All components bound: all info available
PreparedStatement pst1 =
    session.prepare("SELECT * FROM testKs.sensor_data WHERE id = :id and year = :year");
BoundStatement statement1 = pst1.bind(1, 2016);

assert statement1.getRoutingKeyspace() != null;
assert statement1.getRoutingKey() != null;

// 'id' hard-coded, only 'year' is bound: only keyspace available
PreparedStatement pst2 =
    session.prepare("SELECT * FROM testKs.sensor_data WHERE id = 1 and year = :year");
BoundStatement statement2 = pst2.bind(2016);

assert statement2.getRoutingKeyspace() != null;
assert statement2.getRoutingKey() == null;

For batch statements, the routing information of each child statement is inspected; the first non-null keyspace is used as the keyspace of the batch, and the first non-null routing key as its routing key (the idea is that all children should have the same routing information, since batches are supposed to operate on a single partition). If no child has any routing information, you need to provide it manually.

Policy behavior

When the policy computes a query plan, it first inspects the statement’s routing information. If there isn’t any, the query plan is a simple round-robin shuffle of all connected nodes.

If the statement has routing information, the policy uses it to determine the replicas that hold the corresponding data. Then it returns a query plan containing the replicas shuffled in random order, followed by a round-robin shuffle of the rest of the nodes.

Optional node filtering

Finally, the default policy accepts an optional node filter that gets applied just after the test for inclusion in the local DC. If a node doesn’t pass this test, it will be set at distance IGNORED and the driver will never try to connect to it. This is a good way to exclude nodes on some custom criteria.

You can pass the filter through the configuration:

datastax-java-driver.basic.load-balancing-policy {
  class = DefaultLoadBalancingPolicy
  local-datacenter = datacenter1
  filter-class = com.acme.MyNodeFilter

The filter class must implement java.util.function.predicate<Node>, and have a public constructor that takes a DriverContext argument: public MyNodeFilter(DriverContext context).

Sometimes it’s more convenient to pass the filter programmatically; you can do that with SessionBuilder.withNodeFilter:

List<Node> whiteList = ...
CqlSession session = CqlSession.builder()

If a programmatic filter is provided, the configuration option is ignored.

Custom implementation

You can use your own implementation by specifying its fully-qualified name in the configuration.

Study the LoadBalancingPolicy interface and the default implementation for the low-level details.

Using multiple policies

The load balancing policy can be overridden in execution profiles:

datastax-java-driver {
  basic.load-balancing-policy {
    class = DefaultLoadBalancingPolicy
  profiles {
    custom-lbp {
      basic.load-balancing-policy {
        class = CustomLoadBalancingPolicy
    slow {
      request.timeout = 30 seconds

The custom-lbp profile uses a dedicated policy. The slow profile inherits the default profile’s. Note that this goes beyond configuration inheritance: the driver only creates a single DefaultLoadBalancingPolicy instance and reuses it (this also occurs if two sibling profiles have the same configuration).

For query plans, each request uses its declared profile’s policy. If it doesn’t declare any profile, or if the profile doesn’t have a dedicated policy, then the default profile’s policy is used.

For node distances, the driver remembers the last distance suggested by each policy for each node. Then it uses the “closest” distance for any given node. For example:

  • for node1, policy1 suggests distance LOCAL and policy2 suggests REMOTE. node1 is set to LOCAL;
  • policy1 changes its suggestion to IGNORED. node1 is set to REMOTE;
  • policy1 changes its suggestion to REMOTE. node1 stays at REMOTE.