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Zeppelin has the option to change the storage options of its notebook system to allow you to use AWS S3. I’m not sure how long this has been around but I know it isn’t particularly new. However, I wanted to make a note of it as more users of cluster environments are spinning up resources to […]
This is a follow-up to my post from last year Apache Zeppelin on OSX – Ultra Quick Start but without building from source. Today I tested the latest version of Zeppelin (0.5.6) and, using their distributed binaries, was instantly able to launch Zeppelin and run both Scala and Python jobs on my Macbook. This was with zero configuration, […]
Spark Analysis on a Large File GeoNames.org has free gazetteer data by country or for the world, provided in tab-separated text files. In this post I show you how to do some simple analysis using DataFrames in Spark. As the global file is 280M compressed and 1.2G uncompressed. This size of file makes it difficult to […]
A few different errors have popped during my initiation into Apache Zeppelin, here are a few of them, summarised with workarounds if you need them. Tutorial Failure Due To Spark Versions Default Zeppelin comes with Spark 1.1 (though it may be updated by the time you read this). The current Zeppelin tutorial assumes Spark 1.3 or greater […]
My latest notebook aims to mimic the original Scala-based Spark SQL tutorial with one that uses Python instead. Above you can see the two parallel translations side-by-side. Python Spark SQL Tutorial Code Here is the resulting Python data loading code. The SQL code is identical to the Tutorial notebook, so copy and paste if you need it. I […]
This is my short video (14 min) showing how to build and launch the Apache Zeppelin notebook platform – a web UI for interactive query and analysis. This is all done running locally via OSX on a Macbook. In this video we focus on using the tutorial notebook that comes with Zeppelin and discuss each step – including interactive querying and charting – […]
The Zeppelin project provides a powerful web-based notebook platform for data analysis and discovery. Behind the scenes it supports Spark distributed contexts as well as other language bindings on top of Spark. This post is a very simple introduction to show the first few steps to get started. You’ll find all you need to know […]
