analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL succeeded; numTasks: 1; Took: 13 msec 2021-10-28 13:56:27.663 INFO scheduler.StatsReportListener: task runtime:(count: 1, mean: 8.000000, stdev: 0.000000, max: 8.000000, min: 8.000000) 2021-10-28 13:56:27 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 2021-10-28 13:56:27.668 INFO scheduler.StatsReportListener: task result size:(count: 1, mean: 1402.000000, stdev: 0.000000, max: 1402.000000, min: 1402.000000) 2021-10-28

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL succeeded; numTasks: 1; Took: 13 msec 2021-10-28 13:56:27.663 INFO scheduler.StatsReportListener: task runtime:(count: 1, mean: 8.000000, stdev: 0.000000, max: 8.000000, min: 8.000000) 2021-10-28 13:56:27 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 2021-10-28 13:56:27.668 INFO scheduler.StatsReportListener: task result size:(count: 1, mean: 1402.000000, stdev: 0.000000, max: 1402.000000, min: 1402.000000) 2021-10-28

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL succeeded; numTasks: 1; Took: 13 msec 2021-10-28 13:56:27.663 INFO scheduler.StatsReportListener: task runtime:(count: 1, mean: 8.000000, stdev: 0.000000, max: 8.000000, min: 8.000000) 2021-10-28 13:56:27 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 2021-10-28 13:56:27.668 INFO scheduler.StatsReportListener: task result size:(count: 1, mean: 1402.000000, stdev: 0.000000, max: 1402.000000, min: 1402.000000) 2021-10-28

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL succeeded; numTasks: 1; Took: 13 msec 2021-10-28 13:56:27.663 INFO scheduler.StatsReportListener: task runtime:(count: 1, mean: 8.000000, stdev: 0.000000, max: 8.000000, min: 8.000000) 2021-10-28 13:56:27 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 2021-10-28 13:56:27.668 INFO scheduler.StatsReportListener: task result size:(count: 1, mean: 1402.000000, stdev: 0.000000, max: 1402.000000, min: 1402.000000) 2021-10-28

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL succeeded; numTasks: 1; Took: 13 msec 2021-10-28 13:56:27.663 INFO scheduler.StatsReportListener: task runtime:(count: 1, mean: 8.000000, stdev: 0.000000, max: 8.000000, min: 8.000000) 2021-10-28 13:56:27 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 2021-10-28 13:56:27.668 INFO scheduler.StatsReportListener: task result size:(count: 1, mean: 1402.000000, stdev: 0.000000, max: 1402.000000, min: 1402.000000) 2021-10-28

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL succeeded; numTasks: 1; Took: 13 msec 2021-10-28 13:56:27.663 INFO scheduler.StatsReportListener: task runtime:(count: 1, mean: 8.000000, stdev: 0.000000, max: 8.000000, min: 8.000000) 2021-10-28 13:56:27 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 2021-10-28 13:56:27.668 INFO scheduler.StatsReportListener: task result size:(count: 1, mean: 1402.000000, stdev: 0.000000, max: 1402.000000, min: 1402.000000) 2021-10-28

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL succeeded; numTasks: 1; Took: 13 msec 2021-10-28 13:56:27.663 INFO scheduler.StatsReportListener: task runtime:(count: 1, mean: 8.000000, stdev: 0.000000, max: 8.000000, min: 8.000000) 2021-10-28 13:56:27 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 0.0 B 2021-10-28 13:56:27.668 INFO scheduler.StatsReportListener: task result size:(count: 1, mean: 1402.000000, stdev: 0.000000, max: 1402.000000, min: 1402.000000) 2021-10-28

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL How To Use Spark Dynamic Resource Allocation (DRA) in Kyuubi 2.2. How To Use Spark Adaptive Query Execution (AQE) in Kyuubi 1. Deploy Kyuubi engines on Yarn 1.1. Requirements When you want to deploy Kyuubi’s principal should not use now. Instead, you can schedule a periodically kinit process via crontab task on the local machine that hosts Kyuubi server or simply use Kyuubi Kinit 2. Deploy Kyuubi engines

analytics engine. Concurrent execution: multiple Spark applications work together Quick response: long-running Spark applications without startup cost Optimal execution plan: fully supports Spark SQL How To Use Spark Dynamic Resource Allocation (DRA) in Kyuubi 2. How To Use Spark Adaptive Query Execution (AQE) in Kyuubi 1. Deploy Kyuubi engines on Yarn 1.1. Requirements When you want to deploy Kyuubi’s principal should not use now. Instead, you can schedule a periodically kinit process via crontab task on the local machine that hosts Kyuubi server or simply use Kyuubi Kinit 2. Deploy Kyuubi engines

achieve this goal: State-of-the-art query engines Multiple application for high throughput Sharable execution runtime for low latency Server-side global and continuous optimization Auxiliary performance plugins A server that serves clients and manages engines. An engine that is used to instantiate query execution environments. Here we use Spark for demonstration. These essential components are JVM-based applications Guide How To Use Spark Dynamic Resource Allocation (DRA) in Kyuubi How To Use Spark Adaptive Query Execution (AQE) in Kyuubi Solution for Big Result Sets Deploy Kyuubi On Kubernetes Requirements If you