Z-order Benchmark Tools 1. Kubernetes Tools Spark Block Cleaner Kyuubi Insider Overview Architecture Kyuubi v.s. HiveServer2 Kyuubi v.s. Spark Thrift JDBC/ODBC Server (STS) Contributing Develop Configurations 2.5. Version Compatibility 2.6. Further Readings 3. Kyuubi High Availability Guide 3.1. HA Architecture 3.2. System-side Deployment 3.3. Client-side Usage Configurations 1. Introduction to the Kyuubi Kyuubi service instance will be ready to serve without requiring human intervention. 3.1. HA Architecture Currently, Kyuubi supports load balancing to make the whole system highly available. Load balancing

Z-order Benchmark Tools 1. Kubernetes Tools Spark Block Cleaner Kyuubi Insider Overview Architecture Kyuubi v.s. HiveServer2 Kyuubi v.s. Spark Thrift JDBC/ODBC Server (STS) Contributing Develop Configurations 2.5. Version Compatibility 2.6. Further Readings 3. Kyuubi High Availability Guide 3.1. HA Architecture 3.2. System-side Deployment 3.3. Client-side Usage Configurations 1. Introduction to the Kyuubi Kyuubi service instance will be ready to serve without requiring human intervention. 3.1. HA Architecture Currently, Kyuubi supports load balancing to make the whole system highly available. Load balancing

Z-order Benchmark Tools 1. Kubernetes Tools Spark Block Cleaner Kyuubi Insider Overview Architecture Kyuubi v.s. HiveServer2 Kyuubi v.s. Spark Thrift JDBC/ODBC Server (STS) Contributing Develop Configurations 2.5. Version Compatibility 2.6. Further Readings 3. Kyuubi High Availability Guide 3.1. HA Architecture 3.2. System-side Deployment 3.3. Client-side Usage Configurations 1. Introduction to the Kyuubi Kyuubi service instance will be ready to serve without requiring human intervention. 3.1. HA Architecture Currently, Kyuubi supports load balancing to make the whole system highly available. Load balancing

Functions for Spark SQL Tools 1. Kubernetes Tools Spark Block Cleaner Kyuubi Insider Overview Architecture Kyuubi v.s. HiveServer2 Kyuubi v.s. Spark Thrift JDBC/ODBC Server (STS) Contributing Develop Execution (AQE) is a query re-optimization that occurs during query execution. In terms of technical architecture, the AQE is a framework of dynamic planning and replanning of queries based on runtime statistics communications to assure privacy and data integrity as they go about their business. The Kerberos architecture is centered around a trusted authentication service called the key distribution center, or KDC

Functions for Spark SQL Tools 1. Kubernetes Tools Spark Block Cleaner Kyuubi Insider Overview Architecture Kyuubi v.s. HiveServer2 Kyuubi v.s. Spark Thrift JDBC/ODBC Server (STS) Contributing Develop Execution (AQE) is a query re-optimization that occurs during query execution. In terms of technical architecture, the AQE is a framework of dynamic planning and replanning of queries based on runtime statistics communications to assure privacy and data integrity as they go about their business. The Kerberos architecture is centered around a trusted authentication service called the key distribution center, or KDC

Z-order Benchmark Tools 1. Kubernetes Tools Spark Block Cleaner Kyuubi Insider Overview Architecture Kyuubi v.s. HiveServer2 Kyuubi v.s. Spark Thrift JDBC/ODBC Server (STS) Contributing Develop Execution (AQE) is a query re-optimization that occurs during query execution. In terms of technical architecture, the AQE is a framework of dynamic planning and replanning of queries based on runtime statistics have a constant number of seats and are not allowed to be overloaded. Due to the master-slave architecture of Spark and the resource configured ahead, the overall workload of a single application is predictable

Z-order Benchmark Tools 1. Kubernetes Tools Spark Block Cleaner Kyuubi Insider Overview Architecture Kyuubi v.s. HiveServer2 Kyuubi v.s. Spark Thrift JDBC/ODBC Server (STS) Contributing Develop Execution (AQE) is a query re-optimization that occurs during query execution. In terms of technical architecture, the AQE is a framework of dynamic planning and replanning of queries based on runtime statistics have a constant number of seats and are not allowed to be overloaded. Due to the master-slave architecture of Spark and the resource configured ahead, the overall workload of a single application is predictable

another Kyuubi service instance will be ready to serve without requiring human intervention. HA Architecture Currently, Kyuubi supports load balancing to make the whole system highly available. Load balancing have a constant number of seats and are not allowed to be overloaded. Due to the master-slave architecture of Spark and the resource configured ahead, the overall workload of a single application is predictable Execution (AQE) is a query re-optimization that occurs during query execution. In terms of technical architecture, the AQE is a framework of dynamic planning and replanning of queries based on runtime statistics

another Kyuubi service instance will be ready to serve without requiring human intervention. HA Architecture Currently, Kyuubi supports load balancing to make the whole system highly available. Load balancing have a constant number of seats and are not allowed to be overloaded. Due to the master-slave architecture of Spark and the resource configured ahead, the overall workload of a single application is predictable Execution (AQE) is a query re-optimization that occurs during query execution. In terms of technical architecture, the AQE is a framework of dynamic planning and replanning of queries based on runtime statistics

another Kyuubi service instance will be ready to serve without requiring human intervention. HA Architecture Currently, Kyuubi supports load balancing to make the whole system highly available. Load balancing have a constant number of seats and are not allowed to be overloaded. Due to the master-slave architecture of Spark and the resource configured ahead, the overall workload of a single application is predictable Execution (AQE) is a query re-optimization that occurs during query execution. In terms of technical architecture, the AQE is a framework of dynamic planning and replanning of queries based on runtime statistics