Kyuubi Architecture

Kyuubi is an enhanced edition of the Apache Spark's primordial Thrift JDBC/ODBC Server. It is mainly designed for directly running SQL towards a cluster with all components including HDFS, YARN, Hive MetaStore, and itself secured. The main purpose of Kyuubi is to realize an architecture that can not only speed up SQL queries using Spark SQL Engine, and also be compatible with the HiveServer2's behavior as much as possible. Thus, Kyuubi use the same protocol of HiveServer2, which can be found at HiveServer2 Thrift API as the client-server communication mechanism, and a user session level SparkContext instantiating/registering/caching/recycling mechanism to implement multi-tenant functionality.

kyuubi_architecture

Unified Interface

Because Kyuubi use the same protocol of HiveServer2, it supports all kinds of JDBC/ODBC clients, and user applications written based on this Thrift API as shown in the picture above. Cat Tom can use various types of clients to create connections with the Kyuubi Server, and each connection is bound to a SparkSession instance which also contains a independent HiveMetaStoreClient to interact with Hive MetaStore Server. Tom can set session level configurations for each connection without affecting each other.

Runtime Resource Resiliency

Kyuubi does not occupy any resources from the Cluster Manager(Yarn) during startup, and will give all resources back to Yarn if there is not any active session interacting with a SparkContext. And also with the ability of Spark Dynamic Resource Allocation, it also allows us to dynamically allocating resources within a SparkContext a.k.a a Yarn Application.

Kyuubi Dynamic Resource Requesting

• Session Level Resource Configurations
  Kyuubi supports all Spark/Hive/Hadoop configurations, such as spark.executor.cores/memory, to be set in the connection string which will be used to initialize SparkContext.
• Example

  jdbc:hive2://<host>:<port>/;hive.server2.proxy.user=tom#spark.yarn.queue=theque;spark.executor.instances=3;spark.executor.cores=3;spark.executor.memory=10g
  

Kyuubi Dynamic SparkContext Cache

Kyuubi implements a SparkSessionCacheManager to control SparkSession/SparkContext for instantiating, registering, caching, reusing, and recycling. Different user has one and only one SparkContext instance in Kyuubi Server after it connects to the server for the first time, which will be cached in SparkSessionCacheManager for the whole connection life time and a while after all connections closed.

impersonation

Spark Dynamic Resource Allocation

Spark provides a mechanism to dynamically adjust the resources your application occupies based on the workload. It means that your application may give resources back to the cluster if they are no longer used and request them again later when
there is demand. This feature is particularly useful if multiple applications share resources in your Spark cluster.

Please refer to Dynamic Resource Allocation to see more.

Please refer to Dynamic Allocation Configuration to learn how to configure.

With these features, Kyuubi allows us to use computing resources more efficiently.

Security

Authentication

Please refer to the Authentication/Security Guide in the online documentation for an overview on how to enable security for Kyuubi.

Authorization

Kyuubi can be integrated with Spark Authorizer to offer row/column level access control. Kyuubi does not explicitly support spark-authorizer plugin yet, here is an example you may refer to Spark Branch Authorized

authorization

High Availability

ha

Multiple Kyuubi Server instances can register themselves with ZooKeeper when spark.kyuubi.ha.enabled=true and then the clients can find a Kyuubi Server through ZooKeeper. When a client requests a server instance, ZooKeeper randomly returns a selected registered one. This feature offers:

• High Availability
• Load Balancing
• Rolling Upgrade

HA Configurations

Kyuubi Internal

Kyuubi's internal is very simple to understand, which is shown as the picture below. We may take about it more detailly later.

kyuubi_internal