Tag Archives: Hadoop Distributed File System

How Improved Short-Circuit Local Reads Bring Better Performance and Security to Hadoop

Categories: Hadoop HDFS

One of the key principles behind Apache Hadoop is the idea that moving computation is cheaper than moving data — we prefer to move the computation to the data whenever possible, rather than the other way around. Because of this, the Hadoop Distributed File System (HDFS) typically handles many “local reads” reads where the reader is on the same node as the data:

Initially, local reads in HDFS were handled the same way as remote reads: the client connected to the DataNode via a TCP socket and transferred the data via DataTransferProtocol.

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Processing Rat Brain Neuronal Signals Using an Apache Hadoop Computing Cluster – Part I

Categories: General Guest Hadoop Hive Use Case

Introduction

In this three-part series of posts, we will share our experiences tackling a scientific computing challenge that may serve as a useful practical example for those readers considering Apache Hadoop and Apache Hive as an option to meet their growing technical and scientific computing needs. This first part describes some of the background behind our application and the advantages of Hadoop that make it an attractive framework in which to implement our solution. Part II dives into the technical details of the data we aimed to analyze and of our solution.

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Apache HBase Write Path

Categories: CDH General HBase

Apache HBase is the Hadoop database, and is based on the Hadoop Distributed File System (HDFS). HBase makes it possible to randomly access and update data stored in HDFS, but files in HDFS can only be appended to and are immutable after they are created.  So you may ask, how does HBase provide low-latency reads and writes? In this blog post, we explain this by describing the write path of HBase —

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NameNode Recovery Tools for the Hadoop Distributed File System

Categories: HDFS

Warning: The procedure described below can cause data loss. Contact Cloudera Support before attempting it.

Most system administrators have had to deal with a bad hard disk at some point. One moment, the hard disk is a mechanical marvel; the next, it is an expensive paperweight.

The HDFS (Hadoop Distributed File System) community has been steadily working to diminish the impact of disk failures on overall system availability. In this article,

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How Treato Analyzes Health-related Social Media Big Data with Hadoop and HBase

Categories: CDH Guest Hadoop HBase Use Case

This is a guest post by Assaf Yardeni, Head of R&D for Treato, an online social healthcare solution, headquartered in Israel.

Three years ago I joined Treato, a social healthcare analysis firm to help treato.com scale up to its present capability. Treato is a new source for healthcare information where health-related user generated content (UGC) from the Internet is aggregated and organized into usable insights for patients,

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