project despite that the Spark Thrift JDBC/ODBC server already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavy- weight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10

project despite that the Spark Thrift JDBC/ODBC server already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavy- weight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10

sql-engine.html#running-the-thrift-jdbcodbc-server] already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavyweight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10

sql-engine.html#running-the-thrift-jdbcodbc-server] already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavyweight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10

project despite that the Spark Thrift JDBC/ODBC server already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavy- weight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10

project despite that the Spark Thrift JDBC/ODBC server already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavy- weight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10

project despite that the Spark Thrift JDBC/ODBC server already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE redundancy. 60 Chapter 6. High Availability Kyuubi, Release 1.5.0-incubating Key Benefits • High concurrency – By adding or removing Kyuubi server instances can easily scale up or down to meet the need of lightweight workloads, while for some heavyweight workloads, it should probably not have enough concurrency capacity resulting in poor performance. 76 Chapter 6. High Availability Kyuubi, Release 1.5.0-incubating

sql-engine.html#running-the-thrift-jdbcodbc-server] already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavyweight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10

project despite that the Spark Thrift JDBC/ODBC server already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE redundancy. 60 Chapter 6. High Availability Kyuubi, Release 1.5.1-incubating Key Benefits • High concurrency – By adding or removing Kyuubi server instances can easily scale up or down to meet the need of lightweight workloads, while for some heavyweight workloads, it should probably not have enough concurrency capacity resulting in poor performance. 76 Chapter 6. High Availability Kyuubi, Release 1.5.1-incubating

sql-engine.html#running-the-thrift-jdbcodbc-server] already exists. 1. Supports multi-client concurrency and authentication 2. Supports one Spark application per account(SPA). 3. Supports QUEUE/NAMESPACE lightweight workloads, while for some heavyweight workloads, it should probably not have enough concurrency capacity resulting in poor performance. When the engine has executor idled, we should release this case, we would prefer that such an enormous task be done more slowly in a limited amount of concurrency. The following Spark configurations consist of sizing for the DRA. spark.dynamicAllocation.minExecutors=10