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CDH 5 and Cloudera Manager 5 Requirements and Supported Versions In an enterprise data hub, Cloudera Manager and CDH interact with several products such as Apache Accumulo, Apache Impala, Hue, Cloudera Search, and Cloudera Navigator. This guide provides information about which major and minor release version of a product is supported with which release version of CDH and Cloudera Manager. Compatib
CDH 6 includes Apache Kafka as part of the core package. The documentation includes improved contents for how to set up, install, and administer your Kafka ecosystem. For more information, see the Cloudera Enterprise 6.0.x Apache Kafka Guide. We look forward to your feedback on both the existing and new documentation. Apache Kafka is optimized for small messages. According to benchmarks, the best
© 2021 Cloudera, Inc. All rights reserved. Apache Hadoop and associated open source project names are trademarks of the Apache Software Foundation. For a complete list of trademarks, click here. If this documentation includes code, including but not limited to, code examples, Cloudera makes this available to you under the terms of the Apache License, Version 2.0, including any required notices. A
Minimum Required Role: Configurator (also provided by Cluster Administrator, Full Administrator) Hive on Spark provides better performance than Hive on MapReduce while offering the same features. Running Hive on Spark requires no changes to user queries. Specifically, user-defined functions (UDFs) are fully supported, and most performance-related configurations work with the same semantics. This t
This overview provides an abstract description of a YARN cluster and the goals of YARN tuning. A YARN cluster is composed of host machines. Hosts provide memory and CPU resources. A vcore, or virtual core, is a usage share of a host CPU. Tuning YARN consists primarily of optimally defining containers on your worker hosts. You can think of a container as a rectangular graph consisting of memory and
This section describes how to manually calculate YARN and MapReduce memory allocation settings based on the node hardware specifications. YARN takes into account all of the available resources on each machine in the cluster. Based on the available resources, YARN negotiates resource requests from applications (such as MapReduce) running in the cluster. YARN then provides processing capacity to eac
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