3. Run Anywhere CHAPTER FOUR HIGH PERFORMANCE Kyuubi is built on the Apache Spark, a lightning-fast unified analytics engine. • Concurrent execution: multiple Spark applications work together • Quick manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. usually, Hive metastore as the defacto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to

3. Run Anywhere CHAPTER FOUR HIGH PERFORMANCE Kyuubi is built on the Apache Spark, a lightning-fast unified analytics engine. • Concurrent execution: multiple Spark applications work together • Quick manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. usually, Hive metastore as the defacto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to

against different cluster managers. High Performance Kyuubi is built on the Apache Spark, a lightning-fast unified analytics engine. Concurrent execution: multiple Spark applications work together Quick response: manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. Usually, Hive metastore as the de facto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to

against different cluster managers. High Performance Kyuubi is built on the Apache Spark, a lightning-fast unified analytics engine. Concurrent execution: multiple Spark applications work together Quick response: manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. usually, Hive metastore as the defacto. 3.3. Related Configurations These are the basic open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to

against different cluster managers. High Performance Kyuubi is built on the Apache Spark, a lightning-fast unified analytics engine. Concurrent execution: multiple Spark applications work together Quick response: manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. usually, Hive metastore as the defacto. 3.3. Related Configurations These are the basic open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to

manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. Usually, Hive metastore as the de facto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to connected for a long time. This one-time cost session maintenance model can meet most of the ad-hoc fast response requirements. Kyuubi maintains connections to SparkConext in a loosely coupled fashion.

manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. Usually, Hive metastore as the de facto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to connected for a long time. This one-time cost session maintenance model can meet most of the ad-hoc fast response requirements. 3.10. Overview 183 Kyuubi, Release 1.8.0 Kyuubi maintains connections to

manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. Usually, Hive metastore as the de facto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to connected for a long time. This one-time cost session maintenance model can meet most of the ad-hoc fast response requirements. 3.10. Overview 183 Kyuubi, Release 1.8.0 Kyuubi maintains connections to

manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. Usually, Hive metastore as the de facto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to connected for a long time. This one-time cost session maintenance model can meet most of the ad-hoc fast response requirements. Kyuubi maintains connections to SparkConext in a loosely coupled fashion.

manage the metadata of persistent relational entities, e.g. databases, tables, columns, partitions, for fast access. Usually, Hive metastore as the de facto. Related Configurations These are the basic needs open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop’s storage layer to enable fast analytics on fast data. When you are reading this documentation, we suppose that you are not necessary to connected for a long time. This one-time cost session maintenance model can meet most of the ad-hoc fast response requirements. 3.10. Overview 183 Kyuubi, Release 1.8.0 Kyuubi maintains connections to