Deploy in Cluster Mode

Kylin instances are stateless services, and runtime state information is stored in the HBase metastore. For load balancing purposes, you can enable multiple Kylin instances that share a metastore, so that each node shares query pressure and backs up each other, improving service availability. The following figure depicts a typical scenario for Kylin cluster mode deployment:

Kylin Node Configuration

If you need to cluster multiple Kylin nodes, make sure they use the same Hadoop cluster, HBase cluster. Then do the following steps in each node's configuration file $KYLIN_HOME/conf/kylin.properties:

1. Configure the same kylin.metadata.url value to configure all Kylin nodes to use the same HBase metastore.
2. Configure the Kylin node list kylin.server.cluster-servers, including all nodes (the current node is also included). When the event changes, the node receiving the change needs to notify all other nodes (the current node is also included).
3. Configure the running mode kylin.server.mode of the Kylin node. Optional values include all, job, query. The default value is all. The job mode means that the service is only used for job scheduling, not for queries; the query pattern means that the service is only used for queries, not for scheduling jobs; the all pattern represents the service for both job scheduling and queries.

Note: By default, only one instance can be used for the job scheduling (ie., kylin.server.mode is set to all or job).

Enable Job Engine HA

Since v2.0, Kylin supports multiple job engines running together, which is more extensible, available and reliable than the default job scheduler.

To enable the distributed job scheduler, you need to set or update the configs in the kylin.properties, there are two configuration options:

kylin.job.scheduler.default=2
kylin.job.lock=org.apache.kylin.storage.hbase.util.ZookeeperJobLock

Then please add all job servers and query servers to the kylin.server.cluster-servers.

Use CuratorScheduler

Since v3.0.0-alpha, kylin introduces the Leader/Follower mode multiple job engines scheduler based on Curator. Users can modify the following configuration to enable CuratorScheduler:

kylin.job.scheduler.default=100
kylin.server.self-discovery-enabled=true

For more details about the kylin job scheduler, please refer to Apache Kylin Wiki

Installing a load balancer

To send query requests to a cluster instead of a single node, you can deploy a load balancer such as Nginx, F5 or cloudlb, etc., so that the client communicate with the load balancer instead of a specific Kylin instance.

Read and write separation deployment

For better stability and optimal performance, it is recommended to perform a read-write separation deployment, deploying Kylin on two clusters as follows:

• A Hadoop cluster used for Cube build, which can be a large cluster shared with other applications;
• An HBase cluster used for SQL query. Usually this cluster is configured for Kylin. The number of nodes does not need to be as many as Hadoop clusters. HBase configuration can be optimized for Kylin Cube read-only features.

This deployment strategy is the best deployment solution for the production environment. For how to perform read-write separation deployment, please refer to Deploy Apache Kylin with Standalone HBase Cluster .