[PDF] Data Analytics Using Spark And Hadoop

Data Analytics Using Spark and Hadoop PDF
Author: Sujee Maniyam
Publisher:
ISBN:
Size: 18.87 MB
Format: PDF, Kindle
Category :
Languages : en
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Data Analytics Using Spark And Hadoop

by Sujee Maniyam, release date 2016, Data Analytics Using Spark And Hadoop Books available in PDF, EPUB, Mobi Format. Download Data Analytics Using Spark And Hadoop books, "Hadoop and Spark are the stars of the Big Data world. This course covers the basics of Spark and how to use Spark and Hadoop together for big data analytics. Designed for developers, architects, and data analysts with a fundamental understanding of Hadoop, it begins with an overview of how Hadoop and Spark are used in today's big data ecosystem before moving into hands-on labs that demonstrate Spark and Spark-Hadoop integration. You'll learn about the Spark shell, RDDs, and DataFrames; how to query data in Hadoop Hive Tables from Spark; and how to develop Spark applications and run them on YARN."--Resource description page.




[PDF] Using Spark In The Hadoop Ecosystem

Using Spark in the Hadoop Ecosystem PDF
Author: Rich Morrow
Publisher:
ISBN:
Size: 49.20 MB
Format: PDF
Category :
Languages : en
Pages :
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Using Spark In The Hadoop Ecosystem

by Rich Morrow, release date 2016, Using Spark In The Hadoop Ecosystem Books available in PDF, EPUB, Mobi Format. Download Using Spark In The Hadoop Ecosystem books, "You're new to Big Data, you've heard about Apache Spark and Apache Hadoop and you want to play. Big Data coach Rich Morrow gets you into the game via sixteen sprints (sixteen hands-on labs) across the Spark-Hadoop ball field. First, you'll create playing areas using Amazon Web Services EMR and Cloudera Quickstart VM. Then you'll install Hadoop, run basic HDFS commands, learn MapReduce, use Flume and Sqoop, run Spark and then run Spark again. You'll play with Spark SQL, learn common MLLib usage, do analysis with Hive, ETL with Pig, and then jog through Hadoop/Cloud use cases, Hbase basics, and enterprise integration. When practice is over, you'll know Spark, it's associated modules, the Hadoop ecosystem, and the when, where, how, and why each technology is used."--Resource description page.




[PDF] Big Data Analytics

Big Data Analytics PDF
Author: Venkat Ankam
Publisher: Packt Publishing Ltd
ISBN: 1785889702
Size: 59.71 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 326
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Big Data Analytics

by Venkat Ankam, release date 2016-09-28, Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Big Data Analytics books, A handy reference guide for data analysts and data scientists to help to obtain value from big data analytics using Spark on Hadoop clusters About This Book This book is based on the latest 2.0 version of Apache Spark and 2.7 version of Hadoop integrated with most commonly used tools. Learn all Spark stack components including latest topics such as DataFrames, DataSets, GraphFrames, Structured Streaming, DataFrame based ML Pipelines and SparkR. Integrations with frameworks such as HDFS, YARN and tools such as Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall. Who This Book Is For Though this book is primarily aimed at data analysts and data scientists, it will also help architects, programmers, and practitioners. Knowledge of either Spark or Hadoop would be beneficial. It is assumed that you have basic programming background in Scala, Python, SQL, or R programming with basic Linux experience. Working experience within big data environments is not mandatory. What You Will Learn Find out and implement the tools and techniques of big data analytics using Spark on Hadoop clusters with wide variety of tools used with Spark and Hadoop Understand all the Hadoop and Spark ecosystem components Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Conventional and Structured Streaming, MLLib, ML Pipelines and Graphx See batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming Get to grips with data science and machine learning using MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall. In Detail Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data. Style and approach This step-by-step pragmatic guide will make life easy no matter what your level of experience. You will deep dive into Apache Spark on Hadoop clusters through ample exciting real-life examples. Practical tutorial explains data science in simple terms to help programmers and data analysts get started with Data Science




[PDF] Big Data Analytics With Hadoop 3

Big Data Analytics with Hadoop 3 PDF
Author: Sridhar Alla
Publisher: Packt Publishing Ltd
ISBN: 1788624955
Size: 17.45 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 482
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Big Data Analytics With Hadoop 3

by Sridhar Alla, release date 2018-05-31, Big Data Analytics With Hadoop 3 Books available in PDF, EPUB, Mobi Format. Download Big Data Analytics With Hadoop 3 books, Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.




[PDF] Data Analytics With Spark Using Python

Data Analytics with Spark Using Python PDF
Author: Jeffrey Aven
Publisher: Addison-Wesley Professional
ISBN: 0134844874
Size: 21.29 MB
Format: PDF
Category : Computers
Languages : en
Pages : 99998
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Data Analytics With Spark Using Python

by Jeffrey Aven, release date 2018-06-18, Data Analytics With Spark Using Python Books available in PDF, EPUB, Mobi Format. Download Data Analytics With Spark Using Python books, Solve Data Analytics Problems with Spark, PySpark, and Related Open Source Tools Spark is at the heart of today’s Big Data revolution, helping data professionals supercharge efficiency and performance in a wide range of data processing and analytics tasks. In this guide, Big Data expert Jeffrey Aven covers all you need to know to leverage Spark, together with its extensions, subprojects, and wider ecosystem. Aven combines a language-agnostic introduction to foundational Spark concepts with extensive programming examples utilizing the popular and intuitive PySpark development environment. This guide’s focus on Python makes it widely accessible to large audiences of data professionals, analysts, and developers—even those with little Hadoop or Spark experience. Aven’s broad coverage ranges from basic to advanced Spark programming, and Spark SQL to machine learning. You’ll learn how to efficiently manage all forms of data with Spark: streaming, structured, semi-structured, and unstructured. Throughout, concise topic overviews quickly get you up to speed, and extensive hands-on exercises prepare you to solve real problems. Coverage includes: • Understand Spark’s evolving role in the Big Data and Hadoop ecosystems • Create Spark clusters using various deployment modes • Control and optimize the operation of Spark clusters and applications • Master Spark Core RDD API programming techniques • Extend, accelerate, and optimize Spark routines with advanced API platform constructs, including shared variables, RDD storage, and partitioning • Efficiently integrate Spark with both SQL and nonrelational data stores • Perform stream processing and messaging with Spark Streaming and Apache Kafka • Implement predictive modeling with SparkR and Spark MLlib




[PDF] Data Analytics With Hadoop

Data Analytics with Hadoop PDF
Author: Benjamin Bengfort
Publisher: "O'Reilly Media, Inc."
ISBN: 1491913762
Size: 26.29 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 288
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Data Analytics With Hadoop

by Benjamin Bengfort, release date 2016-06, Data Analytics With Hadoop Books available in PDF, EPUB, Mobi Format. Download Data Analytics With Hadoop books, Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib




[PDF] Big Data Processing Using Spark In Cloud

Big Data Processing Using Spark in Cloud PDF
Author: Mamta Mittal
Publisher: Springer
ISBN: 9811305501
Size: 65.61 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 264
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Big Data Processing Using Spark In Cloud

by Mamta Mittal, release date 2018-06-16, Big Data Processing Using Spark In Cloud Books available in PDF, EPUB, Mobi Format. Download Big Data Processing Using Spark In Cloud books, The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.




[PDF] Big Data Analytics With Spark

Big Data Analytics with Spark PDF
Author: Mohammed Guller
Publisher: Apress
ISBN: 1484209648
Size: 12.71 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 277
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Big Data Analytics With Spark

by Mohammed Guller, release date 2015-12-29, Big Data Analytics With Spark Books available in PDF, EPUB, Mobi Format. Download Big Data Analytics With Spark books, Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. In addition, this book will help you become a much sought-after Spark expert. Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding. Therefore, there is a critical need for tools that can analyze large-scale data and unlock value from it. Spark is a powerful technology that meets that need. You can, for example, use Spark to perform low latency computations through the use of efficient caching and iterative algorithms; leverage the features of its shell for easy and interactive Data analysis; employ its fast batch processing and low latency features to process your real time data streams and so on. As a result, adoption of Spark is rapidly growing and is replacing Hadoop MapReduce as the technology of choice for big data analytics. This book provides an introduction to Spark and related big-data technologies. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib. Big Data Analytics with Spark is therefore written for busy professionals who prefer learning a new technology from a consolidated source instead of spending countless hours on the Internet trying to pick bits and pieces from different sources. The book also provides a chapter on Scala, the hottest functional programming language, and the program that underlies Spark. You’ll learn the basics of functional programming in Scala, so that you can write Spark applications in it. What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, like Hive, Avro, Kafka and so on. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to know is programming in any language. There is a critical shortage of people with big data expertise, so companies are willing to pay top dollar for people with skills in areas like Spark and Scala. So reading this book and absorbing its principles will provide a boost—possibly a big boost—to your career.




[PDF] Scala And Spark For Big Data Analytics

Scala and Spark for Big Data Analytics PDF
Author: Md. Rezaul Karim
Publisher: Packt Publishing Ltd
ISBN: 1783550503
Size: 37.88 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 786
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Scala And Spark For Big Data Analytics

by Md. Rezaul Karim, release date 2017-07-25, Scala And Spark For Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Scala And Spark For Big Data Analytics books, Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book Learn Scala's sophisticated type system that combines Functional Programming and object-oriented concepts Work on a wide array of applications, from simple batch jobs to stream processing and machine learning Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn Understand object-oriented & functional programming concepts of Scala In-depth understanding of Scala collection APIs Work with RDD and DataFrame to learn Spark's core abstractions Analysing structured and unstructured data using SparkSQL and GraphX Scalable and fault-tolerant streaming application development using Spark structured streaming Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML Build clustering models to cluster a vast amount of data Understand tuning, debugging, and monitoring Spark applications Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist.




[PDF] Hadoop Real World Solutions Cookbook

Hadoop Real World Solutions Cookbook PDF
Author: Tanmay Deshpande
Publisher: Packt Publishing Ltd
ISBN: 1784398004
Size: 23.13 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 290
View: 3090

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Hadoop Real World Solutions Cookbook

by Tanmay Deshpande, release date 2016-03-31, Hadoop Real World Solutions Cookbook Books available in PDF, EPUB, Mobi Format. Download Hadoop Real World Solutions Cookbook books, Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout About This Book Implement outstanding Machine Learning use cases on your own analytics models and processes. Solutions to common problems when working with the Hadoop ecosystem. Step-by-step implementation of end-to-end big data use cases. Who This Book Is For Readers who have a basic knowledge of big data systems and want to advance their knowledge with hands-on recipes. What You Will Learn Installing and maintaining Hadoop 2.X cluster and its ecosystem. Write advanced Map Reduce programs and understand design patterns. Advanced Data Analysis using the Hive, Pig, and Map Reduce programs. Import and export data from various sources using Sqoop and Flume. Data storage in various file formats such as Text, Sequential, Parquet, ORC, and RC Files. Machine learning principles with libraries such as Mahout Batch and Stream data processing using Apache Spark In Detail Big data is the current requirement. Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost. Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many more such ecosystem tools. This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. This book provides detailed practices on the latest technologies such as YARN and Apache Spark. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business. Style and approach An easy-to-follow guide that walks you through world of big data. Each tool in the Hadoop ecosystem is explained in detail and the recipes are placed in such a manner that readers can implement them sequentially. Plenty of reference links are provided for advanced reading.