Getting Started With Spark

I discuss getting up and running with Databricks Community Edition:

There are a couple of notes with these clusters:

  1. These are not powerful clusters.  Don’t expect to crunch huge data sets with them.  Notice that the cluster has only 6 GB of RAM, so you can expect to get maybe a few GB of data max.

  2. The cluster will automatically terminate after one hour without activity.  The paid version does not have this limitation.

  3. You interact with the cluster using notebooks rather than opening a command prompt.  In practice, this makes interacting with the cluster a little more difficult, as a good command prompt can provide features such as auto-complete.

Databricks Community Edition has a nice interface, is very easy to get up and running and—most importantly—is free.  Read the whole thing.

Related Posts

Flint: Time Series With Spark

Li Jin and Kevin Rasmussen cover the concepts of Flint, a time-series library built on Apache Spark: Time series analysis has two components: time series manipulation and time series modeling. Time series manipulation is the process of manipulating and transforming data into features for training a model. Time series manipulation is used for tasks like data […]

Read More

ElasticMapReduce And RStudio

Tanzir Musabbir demonstrates how to set up Amazon ElasticMapReduce to include an RStudio edge node: RStudio Server provides a browser-based interface for R and a popular tool among data scientists. Data scientist use Apache Spark cluster running on  Amazon EMR to perform distributed training. In a previous blog post, the author showed how you can install RStudio Server on Amazon […]

Read More

Categories

June 2016
MTWTFSS
« May Jul »
 12345
6789101112
13141516171819
20212223242526
27282930