Seven Databases in Seven Weeks – Hbase Day 1

Hbase is a columnar NoSQL database.
The first day of Hbase was short and clear.
Installing it was easy. No issues whatsoever.
The examples simulated some wiki pages with revisions.
It was fairly easy.

Installation
I found a really easy tutorial on how to install Hbase on Fedora:
http://tutorialforlinux.com/2014/03/18/how-to-getting-started-with-apache-hbase-on-fedora-19-20-21-3264bit-linux-easy-guide/

Hbase will usually work on several (many) servers. It is recommended to run it with at least 5 machines.
However, it’s possible to run it on a single machine for POC / learning purposes. I am using an old, weak laptop, and Hbase works just fine.

JRuby Script
Part of the learning consists of understanding JRuby, as some scripts and exercises use it.

To load a JRuby script into the Hbase shell, run something like:
/opt/hbase-latest/bin/hbase org.jruby.Main PATH-TO-SCRIPT

The example script: put_multiple_columns initially didn’t work. I think it’s due to different versions.
In the book’s forum I found a similar question and an answer for that problem:
http://forums.pragprog.com/forums/202/topics/11494

I uploaded the working script to GitHub: GitHub-put_multiple_columns.rb

Day 1 Material
Under GitHub, some links, material and homework answers.
https://github.com/eyalgo/seven-dbs-in-seven-weeks/tree/master/hbase/day_1

Day 1 Homework
The exercise is more of a JRuby / Ruby and less of Hbase.

def put_many( table_name, row, column_values )
  import 'org.apache.hadoop.hbase.client.HTable'
  import 'org.apache.hadoop.hbase.client.Put'
  import 'org.apache.hadoop.hbase.HBaseConfiguration'

  def jbytes( *args )
    args.map { |arg| arg.to_s.to_java_bytes }
  end

  puts( @hbase )
  conf = HBaseConfiguration.new
  table = HTable.new( conf, table_name )
  p = Put.new( *jbytes( row ) )
  
  column_values.each do |key, value|
    (key_family, key_name) = key.split(':')
    key_name ||= ""
    p.add( *jbytes( key_family, key_name, value ))
  end
  
  table.put( p )
end

Day 2, working with big data looks really interesting…

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