The Hortonworks Blog

More from Saptak Sen

If you’re excited to get started with the new features in Hortonworks Data Platform 2.1, then we’ve included 4 tutorials for you try out – Sandbox-style.

You can download the HDP 2.1 Technical Preview here, and then get stuck into these great tutorials.

Interactive Query with Apache Hive and Apache Tez

OK, so you’re not going to get huge performance out of a one-node VM, but you can try out Hive on Tez, and see the performance gains versus MapReduce, and also try out features such as Vectorized Query, and the host of new SQL features.…

In this post, we will explore how to quickly and easily spin up our own VM with Vagrant and Apache Ambari. Vagrant is very popular with developers as it lets one mirror the production environment in a VM while staying with all the IDEs and tools in the comfort of the host OS.

If you’re just looking to get started with Hadoop in a VM, then you can simply download the Hortonworks Sandbox.…

In this post, we’ll walk through the process of deploying an Apache Hadoop 2 cluster on the EC2 cloud service offered by Amazon Web Services (AWS), using Hortonworks Data Platform.

Both EC2 and HDP offer many knobs and buttons to cater to your specific, performance, security, cost, data size, data protection and other requirements. I will not discuss most of these options in this blog as the goal is to walk through one particular path of deployment to get started.…

Microsoft and Hortonworks have been working together for over two years now with the goal of bringing the power of Big Data to a billion people. As a result of that work, today we announced the General Availability of HDP 2.0 for Windows with the full power of YARN.

There are already over half a billion Excel users on this planet.

So, we have put together a short tutorial on the Hortonworks Sandbox where we walk through the end-to-end data pipeline using HDP and Microsoft Excel in the shoes of a data analyst at a financial services firm where she:

  • Cleans and aggregates 10 years of raw stock tick data from NYSE
  • Enriches the data model by looking up additional attributes from Wikipedia
  • Creates an interactive visualization on the model

You can find the tutorial here.…

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