• AWS,  EMR,  Hadoop,  YARN

    Hadoop YARN – Collecting Utilization Metrics from Multiple Clusters

    When you run many Hadoop clusters it is useful to automatically collect metrics from all clusters in a single place (Hive table i.e.).

    This allows you to perform any advanced and custom analysis of your clusters workload and not be limited to the features provided by Hadoop Administration UI tools that often offer only per cluster view so it is hard to see the whole picture of your data platform.

  • Hadoop,  Memory,  YARN

    YARN Memory Under-Utilization Running Low-Memory Instances (c4.xlarge i.e.)

    Analyzing a Hadoop cluster I noticed that it runs 2 GB and 4 GB containers only, and does not allocate the entire available memory to applications always leaving about 150 GB of free memory.

    The clusters run Apache Pig and Hive applications, and the default settings (they are also inherited by Tez engine used by Pig and Hive):

    -- from mapred-site.xml
    mapreduce.map.memory.mb            1408
    mapreduce.reduce.memory.mb         2816
    yarn.app.mapreduce.am.resource.mb  2816