Hao Zhu is a Manager, Hadoop Escalation Group at MapR. Prior to MapR, Hao was Principal Technical Support Engineer at Pivotal, before Pivotal he was an Oracle DBA at eBay. Openkb.info is his personal technical blog.
In this blog post, I will explain the resource allocation configurations for Spark on YARN, describe the yarn-client and yarn-cluster modes, and will include examples. Spark can request two resources in YARN: CPU and memory.
In this blog post, I will discuss best practices for YARN resource management. The fundamental idea of MRv2(YARN) is to split up the two major functionalities—resource management and job scheduling/monitoring, into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM).
This article describes the new Hive transaction feature introduced in Hive 1.0. This new feature adds initial support of the 4 traits of database transactions – atomicity, consistency, isolation and durability at the row level. With this new feature, you can add new rows in Hive while another application reads rows from the same partition without interference.
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