Book Image

Apache Spark for Data Science Cookbook

By : Padma Priya Chitturi
Book Image

Apache Spark for Data Science Cookbook

By: Padma Priya Chitturi

Overview of this book

Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark’s selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark’s data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work.
Table of Contents (17 chapters)
Apache Spark for Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Creating Pandas DataFrames over Spark


A DataFrame is a distributed collection of data organized into named columns. It is equivalent to a table in a relational database or a DataFrame in R/Python Python with rich optimizations. These can be constructed from a wide variety of sources, such as structured data files (JSON and parquet files), Hive tables, external databases, or from existing RDDs.

PySpark is the Python API for Apache Spark which is designed to scale to huge amounts of data. This recipe shows how to make use of Pandas over Spark.

Getting ready

To step through this recipe, you will need a running Spark cluster either in pseudo distributed mode or in one of the distributed modes, that is, standalone, YARN, or Mesos. Also, have Python and IPython installed on the Linux machine, that is, Ubuntu 14.04.

How to do it…

  1. Invoke ipython console -profile=pyspark  as follows:

          In [4]: from pyspark import SparkConf, SparkContext, SQLContext
          In [5]: import pandas as pd
    
  2. Creating...