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By Venkat Ankam

Key Features

  • This ebook relies at the most up-to-date 2.0 model of Apache Spark and 2.7 model of Hadoop built-in with most ordinarily used tools.
  • Learn all Spark stack elements together with newest themes akin to DataFrames, DataSets, GraphFrames, established Streaming, DataFrame established ML Pipelines and SparkR.
  • Integrations with frameworks reminiscent of HDFS, YARN and instruments reminiscent of Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall.

Book Description

Big information Analytics ebook goals at supplying the basics of Apache Spark and Hadoop. All Spark parts – Spark middle, Spark SQL, DataFrames, info 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 advantages of in-memory speeds. DataFrames API, information resources API and new facts set API are defined for development huge info analytical purposes. Real-time info analytics utilizing Spark Streaming with Apache Kafka and HBase is roofed to aid construction streaming functions. New dependent streaming idea is defined with an IOT (Internet of items) use case. computer studying options 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 net established notebooks similar to Jupyter, Apache Zeppelin and knowledge move instrument Apache NiFi to research and visualize data.

What you are going to learn

  • Find out and enforce the instruments and strategies of huge facts analytics utilizing Spark on Hadoop clusters with good selection of instruments used with Spark and Hadoop
  • Understand the entire Hadoop and Spark atmosphere components
  • Get to grasp the entire Spark parts: Spark middle, Spark SQL, DataFrames, DataSets, traditional and established Streaming, MLLib, ML Pipelines and Graphx
  • See batch and real-time facts analytics utilizing Spark center, Spark SQL, and standard and established Streaming
  • Get to grips with information technology and laptop 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 massive facts applied sciences, operating with shoppers to layout and strengthen scalable large information functions. Having labored with a number of consumers globally, he has large event in huge facts 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 proportion wisdom with the community.

Venkat has introduced hundreds of thousands of trainings, shows, and white papers within the titanic facts sphere. whereas this can be his first try out at writing a publication, 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 established Streaming
  6. Notebooks and Dataflows with Spark and Hadoop
  7. Machine studying with Spark and Hadoop
  8. Building advice structures with Spark and Mahout
  9. Graph Analytics with GraphX
  10. Interactive Analytics with SparkR

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Big Data Analytics by Venkat Ankam


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