Get up to speed on Apache Spark for building big data applications in Python, Java, or Scala. Recently updated with nearly an hour of new footage on DataFrames in Spark 1.3, this video workshop shows you how to explore data and apply algorithms with MLlib, GraphX, and Spark SQL. You’ll learn Spark and its core APIs by doing hands-on technical exercises with presenter Paco Nathan, host of the popular Just Enough Math video workshop.
With this workshop, you will:
Get going with the newest features of Spark 1.3
Open a Spark shell
Develop Spark apps for typical use cases
Use some machine-learning algorithms
Explore data sets loaded from HDFS or another filesystem
Work with Spark SQL, Spark Streaming, and Spark’s machine-learning library, MLlib
Use Maven, SBT, IPython Notebook, and other tooling
Learn about Spark follow-up courses and certification
Paco Nathan has led innovative data teams building large-scale apps for several years. He’s an expert in distributed systems, machine learning, cloud computing, and functional programming.
Paco Nathan, is known as a "player/coach" data scientist who's led innovative Data teams building large-scale apps for 10+ years. A recognized expert in distributed systems, machine learning, and Enterprise data workflows, Paco is an O'Reilly author, OSS evangelist for Apache Spark with Databricks, and an advisor for Amplify Partners and Galvanize. Paco received his BS Math Sci and MS Comp Sci degrees from Stanford University, and has 25+ years technology industry experience ranging from Bell Labs to early-stage start-ups. Newsletter and "official" web site: http://liber118.com/pxn/.
Comments about oreilly Introduction to Apache Spark:
This video series was the perfect thing to get a newbie up to speed and working with Spark quickly. Don't expect the complete bible of Spark, that's not what this is. You will need to move on to more in depth material if you are going to build a real Spark application, but this is a great quick way to get you started.
Bottom Line Yes, I would recommend this to a friend