Hadoop Beginner's Guide by Garry Turkington

By Garry Turkington

«Hadoop novices consultant» gets rid of the secret from Hadoop, providing Hadoop and comparable applied sciences with a spotlight on construction operating structures and getting the activity performed, utilizing cloud providers to take action whilst it is sensible. From easy thoughts and preliminary setup via constructing functions and holding the process working because the facts grows, the booklet offers the knowledge had to successfully use Hadoop to unravel genuine global problems.
Starting with the fundamentals of putting in and configuring Hadoop, the booklet explains how you can enhance functions, continue the process, and the way to take advantage of extra items to combine with different platforms.

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Search for JAVA_HOME and uncomment the line, modifying the location to point to your JDK installation, as mentioned earlier. What just happened? These steps ensure that Hadoop is installed and available from the command line. By setting the path and configuration variables, we can use the Hadoop command-line tool. The modification to the Hadoop configuration file is the only required change to the setup needed to integrate with your host settings. As mentioned earlier, you should put the export commands in your shell startup file or a standalone-configuration script that you specify at the start of the session.

Txt [ 38 ] Chapter 2 This is a test. txt This is a test. What just happened? This example shows the use of the fs subcommand to the Hadoop utility. Note that both dfs and fs commands are equivalent). Like most filesystems, Hadoop has the concept of a home directory for each user. These home directories are stored under the /user directory on HDFS and, before we go further, we create our home directory if it does not already exist. We then create a simple text file on the local filesystem and copy it to HDFS by using the copyFromLocal command and then check its existence and contents by using the -ls and -cat utilities.

If the data set doubles, simply use two servers instead of a single double-sized one. If it doubles again, move to four hosts. The obvious benefit of this approach is that purchase costs remain much lower than for scale-up. Server hardware costs tend to increase sharply when one seeks to purchase larger machines, and though a single host may cost $5,000, one with ten times the processing power may cost a hundred times as much. The downside is that we need to develop strategies for splitting our data processing across a fleet of servers and the tools historically used for this purpose have proven to be complex.

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