Load balancing controls how queries are distributed to nodes in a Cassandra cluster.
Without additional configuration the C/C++ driver defaults to using Datacenter-aware load balancing with token-aware routing. Meaning the driver will only send queries to nodes in the local datacenter (for local consistency levels) and it will use the primary key of queries to route them directly to the nodes where the corresponding data is located.
Round-robin Load Balancing
This load balancing policy equally distributes queries across cluster without consideration of datacenter locality. This should only be used with Cassandra clusters where all nodes are located in the same datacenter.
Datacenter-aware Load Balancing
This load balancing policy equally distributes queries to nodes in the local
datacenter. Nodes in remote datacenters are only used when all local nodes are
unavailable. Additionally, remote nodes are only considered when non-local
consistency levels are used or if the driver is configured to use remote nodes
/* * Use up to 2 remote datacenter nodes for remote consistency levels * or when `allow_remote_dcs_for_local_cl` is enabled. */ unsigned used_hosts_per_remote_dc = 2; /* Don't use remote datacenter nodes for local consistency levels */ cass_bool_t allow_remote_dcs_for_local_cl = cass_false; cass_cluster_set_load_balance_dc_aware(cluster, used_hosts_per_remote_dc, allow_remote_dcs_for_local_cl);
Token-aware routing uses the primary key of queries to route requests directly to the Cassandra nodes where the data is located. Using this policy avoids having to route requests through an extra coordinator node in the Cassandra cluster. This can improve query latency and reduce load on the Cassandra nodes. It can be used in conjunction with other load balancing and routing policies.
/* Enable token-aware routing (this is the default setting) */ cass_cluster_set_token_aware_routing(cluster, cass_true); /* Disable token-aware routing */ cass_cluster_set_token_aware_routing(cluster, cass_false);
Latency-aware routing tracks the latency of queries to avoid sending new queries to poorly performing Cassandra nodes. It can be used in conjunction with other load balancing and routing policies.
/* Disable latency-aware routing (this is the default setting) */ cass_cluster_set_latency_aware_routing(cluster, cass_false); /* Enable latency-aware routing */ cass_cluster_set_latency_aware_routing(cluster, cass_true); /* * Configure latency-aware routing settings */ /* Up to 2 times the best performing latency is okay */ cass_double_t exclusion_threshold = 2.0; /* Use the default scale */ cass_uint64_t scale_ms = 100; /* Retry a node after 10 seconds even if it was performing poorly before */ cass_uint64_t retry_period_ms = 10000; /* Find the best performing latency every 100 milliseconds */ cass_uint64_t update_rate_ms = 100; /* Only consider the average latency of a node after it's been queried 50 times */ cass_uint64_t min_measured = 50; cass_cluster_set_latency_aware_routing_settings(cluster, exclusion_threshold, scale_ms, retry_period_ms, update_rate_ms, min_measured);
This policy ensures that only hosts from the provided whitelist filter will ever be used. Any host that is not contained within the whitelist will be considered ignored and a connection will not be established. It can be used in conjunction with other load balancing and routing policies.
NOTE: Using this policy to limit the connections of the driver to a predefined set of hosts will defeat the auto-detection features of the driver. If the goal is to limit connections to hosts in a local datacenter use DC aware in conjunction with the round robin load balancing policy.
/* Set the list of predefined hosts the driver is allowed to connect to */ cass_cluster_set_whitelist_filtering(cluster, "127.0.0.1, 127.0.0.3, 127.0.0.5"); /* The whitelist can be cleared (and disabled) by using an empty string */ cass_cluster_set_whitelist_filtering(cluster, "");
This policy is the inverse of the whitelist policy where hosts provided in the blacklist filter will be ignored and a connection will not be established.
/* Set the list of predefined hosts the driver is NOT allowed to connect to */ cass_cluster_set_blacklist_filtering(cluster, "127.0.0.1, 127.0.0.3, 127.0.0.5"); /* The blacklist can be cleared (and disabled) by using an empty string */ cass_cluster_set_blacklist_filtering(cluster, "");
Filtering can also be performed on all hosts in a datacenter or multiple datacenters when using the whitelist/blacklist datacenter filtering polices.
/* Set the list of predefined datacenters the driver is allowed to connect to */ cass_cluster_set_whitelist_dc_filtering(cluster, "dc2, dc4"); /* The datacenter whitelist can be cleared/disabled by using an empty string */ cass_cluster_set_whitelist_dc_filtering(cluster, "");
/* Set the list of predefined datacenters the driver is NOT allowed to connect to */ cass_cluster_set_blacklist_dc_filtering(cluster, "dc2, dc4"); /* The datacenter blacklist can be cleared/disabled by using an empty string */ cass_cluster_set_blacklist_dc_filtering(cluster, "");
For certain applications it is of the utmost importance to minimize latency. Speculative execution is a way to minimize latency by preemptively executing several instances of the same query against different nodes. The fastest response is then returned to the client application and the other requests are cancelled. Speculative execution is disabled by default.
Speculative execution will result in executing the same query several times. Therefore, it is important that queries are idempotent i.e. a query can be applied multiple times without changing the result beyond the initial application. Queries that are not explicitly marked as idempotent will not be scheduled for speculative executions.
The following types of queries are not idempotent:
- Mutation of
- Prepending or appending to a
- Use of non-idempotent CQL function e.g.
The driver is unable to determine if a query is idempotent therefore it is up to an application to explicitly mark a statement as being idempotent.
CassStatement* statement = cass_statement_new( "SELECT * FROM table1", 0); cass_statement_set_is_idempotent(statement, cass_true);
Enabling speculative execution
Speculative execution is enabled by connecting a
CassSession with a
CassCluster that has a speculative execution policy enabled. The driver
currently only supports a constant policy, but may support more in the future.
Constant speculative execution policy
The following will start up to 2 more executions after the initial execution with the subsequent executions being created 500 milliseconds apart.
CassCluster* cluster = cass_cluster_new(); cass_int64_t constant_delay_ms = 500; /* Delay before a new execution is created */ int max_speculative_executions = 2; /* Number of executions */ cass_cluster_set_constant_speculative_execution_policy(cluster constant_delay_ms, max_speculative_executions);
To prevent intermediate network devices (routers, switches, etc.) from
disconnecting pooled connections the driver sends a lightweight heartbeat
request (using an
OPTIONS protocol request) periodically. By default the
driver sends a heartbeat every 30 seconds. This can be changed or disabled (0
second interval) using the following:
/* Change the heartbeat interval to 1 minute */ cass_cluster_set_connection_heartbeat_interval(cluster, 60); /* Disable heartbeat requests */ cass_cluster_set_connection_heartbeat_interval(cluster, 0);
Heartbeats are also used to detect unresponsive connections. An idle timeout setting controls the amount of time a connection is allowed to be without a successful heartbeat before being terminated and scheduled for reconnection. This interval can be changed from the default of 60 seconds:
/* Change the idle timeout to 2 minute */ cass_cluster_set_connection_idle_timeout(cluster, 120);
It can be disabled by setting the value to a very long timeout or by disabling heartbeats.
Use a single persistent session
Sessions are expensive objects to create in both time and resources because they maintain a pool of connections to your Cassandra cluster. An application should create a minimal number of sessions and maintain them for the lifetime of an application.
Use token-aware and latency-aware policies
The token-aware load balancing can reduce the latency of requests by avoiding an extra network hop through a coordinator node. When using the token-aware policy requests are sent to one of the nodes which will retrieved or stored instead of routing the request through a proxy node (coordinator node).
The latency-aware load balancing policy can also reduce the latency of requests by routing requests to nodes that historical performing with the lowest latency. This can prevent requests from being sent to nodes that are underperforming.
Use paging when retrieving large result sets
Using a large page size or a very high
LIMIT clause can cause your application
to delay for each individual request. The driver’s paging mechanism can be used
to decrease the latency of individual requests.
Choose a lower consistency level
Ultimately, choosing a consistency level is a trade-off between consistency and
availability. Performance should not be a large deciding factor when choosing a
consistency level. However, it can affect high-percentile latency numbers
because requests with consistency levels greater than
ONE can cause requests
to wait for one or more nodes to respond back to the coordinator node before a
request can complete. In multi-datacenter configurations, consistency levels such as
EACH_QUORUM can cause a request to wait for replication across a slower cross
datacenter network link. More information about setting the consistency level
can be found here.