Tag Archives: resource management

Quicker Insight into Apache Solr and Collection Health

Categories: CDH Cloudera Manager How-to Search

Successful cluster administration can be very difficult without a real-time view of the state of the cluster. Solr itself does not provide aggregated views about its state or any historical usage data, which is necessary to understand how the service is used and how it is performing. Knowing the throughput and capacities not only helps detect errors and troubleshoot issues, but is also useful for capacity planning.

Questions may arise, such as:

  • What is the size of my cluster and each collection?

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Resource Management for Apache Impala (incubating)

Categories: CDH Cloudera Manager Hadoop Impala Ops and DevOps Use Case

Apache Impala (incubating) includes several features that allow you to restrict or allocate resources so as to maximize stability and performance for your Impala workloads. You can limit both CPU and memory resources used by Impala to manage and prioritize jobs on CDH clusters. This blog post describes the techniques a typical Impala deployment can use to manage its resources.

Static Service Pools

Static service pools isolate services from one another, so that a high load on one service has limited impact on other services.

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Untangling Apache Hadoop YARN, Part 3: Scheduler Concepts

Categories: YARN

In Parts 1 and 2, we covered the basics of YARN resource allocation. In this installment, we’ll provide an overview of cluster scheduling and introduce the Fair Scheduler, one of the scheduler choices available in YARN.

A standalone computer can have several CPU cores, each running a single process, but there can be as many as a few hundred processes running simultaneously. The scheduler is a part of the desktop’s operating system that assigns a process to a CPU core to run for a short period of time.

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Untangling Apache Hadoop YARN, Part 2: Global Configuration Basics

Categories: YARN

A new installment in the series about the tangled ball of thread that is YARN

In Part 1 of this series, we covered the fundamentals of clusters of YARN. In Part 2, you’ll learn about other components than can run on a cluster and how they affect YARN cluster configuration.

Ideal YARN Allocation

As shown in the previous post, a YARN cluster can be configured to use up all the resources on the cluster.

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How-to: Build a Machine-Learning App Using Sparkling Water and Apache Spark

Categories: CDH Data Science Guest How-to Spark

Thanks to Michal Malohlava, Amy Wang, and Avni Wadhwa of H20.ai for providing the following guest post about building ML apps using Sparkling Water and Apache Spark on CDH.

The Sparkling Water project is nearing its one-year anniversary, which means Michal Malohlava, our main contributor, has been very busy for the better part of this past year. The Sparkling Water project combines H2O machine-learning algorithms with the execution power of Apache Spark.

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