Offline analysis of HDFS metadata


HDFS is part of the core Hadoop ecosystem and serves as a storage layer for the Hadoop computational frameworks like Spark, MapReduce. Like other distributed file systems, HDFS is based on an architecture where namespace is decoupled from the data. The namespace contains the file system metadata which is maintained by dedicated server called namenode and the data itself resides on other servers called datanodes.

This blogpost is about dumping HDFS metadata into Impala/Hive table for examination and offline analysis using SQL semantics

Experiences of Using Alluxio with Spark


Alluxio refers to itself as an "Open Source Memory Speed Virtual Distributed Storage" platform. It sits between the storage and processing framework layers in the distributed computing ecosystem and claims to heavily improve performance when multiple jobs are reading/writing from/to the same data. This post will cover some of the basic features of Alluxio and will compare its performance for accessing data against caching in Spark.

Tool to visualise block distribution on Hadoop (HDFS) cluster

Distributed systems always bring new challenges for administrators and users. This is the case with HDFS, the default distributed file system that Hadoop uses for storing data.

In order to face these challenges, tools to facilitate administration and usage of these systems are developed. At CERN, a Hadoop service is provided and we have developed and deployed on our clusters some tools, today we present one of these tools.

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