By Venkat Ankam

Key Features

  • This ebook is predicated at the newest 2.0 model of Apache Spark and 2.7 model of Hadoop built-in with most typically used tools.
  • Learn all Spark stack elements together with most modern subject matters comparable to DataFrames, DataSets, GraphFrames, based Streaming, DataFrame dependent ML Pipelines and SparkR.
  • Integrations with frameworks resembling HDFS, YARN and instruments resembling Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall.

Book Description

Big information Analytics e-book goals at offering the basics of Apache Spark and Hadoop. All Spark elements – Spark middle, Spark SQL, DataFrames, facts units, traditional Streaming, based Streaming, MLlib, Graphx and Hadoop middle parts – HDFS, MapReduce and Yarn are explored in better intensity with implementation examples on Spark + Hadoop clusters.

It is relocating clear of MapReduce to Spark. So, merits of Spark over MapReduce are defined at nice intensity to harvest merits of in-memory speeds. DataFrames API, info resources API and new information set API are defined for construction mammoth information analytical purposes. Real-time information analytics utilizing Spark Streaming with Apache Kafka and HBase is roofed to assist construction streaming functions. New established streaming notion is defined with an IOT (Internet of items) use case. laptop studying recommendations are coated utilizing MLLib, ML Pipelines and SparkR and Graph Analytics are lined with GraphX and GraphFrames elements of Spark.

Readers also will get a chance to start with internet dependent notebooks equivalent to Jupyter, Apache Zeppelin and information stream software Apache NiFi to research and visualize data.

What you are going to learn

  • Find out and enforce the instruments and strategies of huge info analytics utilizing Spark on Hadoop clusters with big range of instruments used with Spark and Hadoop
  • Understand all of the Hadoop and Spark surroundings components
  • Get to grasp all of the Spark parts: Spark center, Spark SQL, DataFrames, DataSets, traditional and dependent Streaming, MLLib, ML Pipelines and Graphx
  • See batch and real-time information analytics utilizing Spark middle, Spark SQL, and traditional and based Streaming
  • Get to grips with information technology and computing device studying utilizing MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall.

About the Author

Venkat Ankam has over 18 years of IT adventure and over five years in gigantic info applied sciences, operating with shoppers to layout and enhance scalable gigantic info functions. Having labored with a number of consumers globally, he has super adventure in massive info analytics utilizing Hadoop and Spark.

He is a Cloudera qualified Hadoop Developer and Administrator and likewise a Databricks qualified Spark Developer. he's the founder and presenter of some Hadoop and Spark meetup teams globally and likes to percentage wisdom with the community.

Venkat has added 1000s of trainings, displays, and white papers within the mammoth information sphere. whereas this can be his first test at writing a e-book, many extra books are within the pipeline.

Table of Contents

  1. Big facts Analytics at 10,000 foot view
  2. Getting begun with Apache Hadoop and Apache Spark
  3. Deep Dive into Apache Spark
  4. Big facts Analytics with Spark SQL, DataFrames, and Datasets
  5. Real-Time Analytics with Spark Streaming and dependent Streaming
  6. Notebooks and Dataflows with Spark and Hadoop
  7. Machine studying with Spark and Hadoop
  8. Building suggestion platforms with Spark and Mahout
  9. Graph Analytics with GraphX
  10. Interactive Analytics with SparkR

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