sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust the respon- siveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. 6.9. Overview 107 Kyuubi, Release 1.3.0 Client Concurrency The compilation

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust the respon- siveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. 6.9. Overview 107 Kyuubi, Release 1.3.0 Client Concurrency The compilation

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. 2.1.1. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust ad-hoc responsiveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. Client Concurrency The compilation and optimization for queries in both

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. 1.1. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust ad-hoc responsiveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. Client Concurrency The compilation and optimization for queries in both

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. 66 Chapter 6. High Availability Kyuubi, Release 1.4.1-incubating The Basics of Dynamic Resource respon- siveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. 6.9. Overview 125 Kyuubi, Release 1.4.1-incubating Client Concurrency

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. 66 Chapter 6. High Availability Kyuubi, Release 1.3.0 The Basics of Dynamic Resource Allocation respon- siveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. 6.9. Overview 125 Kyuubi, Release 1.3.0 Client Concurrency The compilation

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust the respon- siveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. 6.9. Overview 151 Kyuubi, Release 1.5.0-incubating Client Concurrency

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. 2.1.1. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust ad-hoc responsiveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. Client Concurrency The compilation and optimization for queries in both

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust the respon- siveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. 6.9. Overview 151 Kyuubi, Release 1.5.1-incubating Client Concurrency

sharing. On the other hand, we need to enable Spark’s DRA feature for the engines’ executors’ elastic scaling. 2.1.1. The Basics of Dynamic Resource Allocation Spark provides a mechanism to dynamically adjust ad-hoc responsiveness through the way of engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data as it does not create any Engine when it starts. It’s cheap to add Kyuubi HA nodes, so horizontal scaling is not overly burdensome. Client Concurrency The compilation and optimization for queries in both