Hadoop Ecosystem Workshop

Details

We're delighted to welcome you to Hadoop Ecosystem Workshop by Ran Silberman from Tikal (http://www.tikalk.com/hebrew/).

Hadoop and HDFS are the pillars of today’s big data systems. They are the cornerstone for every big data project today.
But in order to use them properly and efficiently, it needs to know their ecosystem.
Today there are dozens of system that together build a huge ecosystem for hadoop and HDFS.

In this session we will cover Hadoop ecosystem in general and dive into some examples.
During the workshop session the students will have a taste of Hadoop in practice: They will install a small hadoop cluster, write some MapReduce code and run it.
Then they will play with some systems that work with Hadoop, for example:
Hue, Hive, Impala, Avro, Parquet, Scalding and more.

This session is intended for people that have some basic understanding about Hadoop, but want to learn more and be able to choose the proper tools for their needs.

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Prerequisites:
The attendees will need to prepare a laptop for the session with the following:
We will use Cloudera QuickStart VM in the workshop.

Check the compatibility for the environment as defined here: http://www.cloudera.com/content/cloudera/en/documentation/core/v5-2-x/topics/cloudera_quickstart_vm.html. Note: Although the above link mentions that 4GM RAM is enough, it is highly recommended to have 16GB - Otherwise the system will work VERY slowly.

In order to run Cloudera Hadoop quickstart, you need either VirtualBox or VMWare Player:

Download from Cloudera the image for VMWare or VirtualBox from: http://www.cloudera.com/content/cloudera/en/downloads/quickstart_vms/cdh-5-4-x.html.
Download VMPlayer to run the VM from: https://my.vmware.com/web/vmware/free#desktop_end_user_computing/vmware_player/4_0

Or download VirtualBox from http://www.oracle.com/technetwork/server-storage/virtualbox/overview/index.html

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See you soon, in the meantime, welcome to join the

community's YouTube channel (https://www.youtube.com/channel/UCV7lV9Lq2sc7t0QEKS4xH7A/videos)