Big Data Analytics with Hadoop 3
Build highly effective analytics solutions to gain valuable insight into your big data
1st Edition
Published on 23. September 2024
482 pages
978-1-78862-495-4 (ISBN)
Description
Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3Key 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 DescriptionApache 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 forBig 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.
- 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 DescriptionApache 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 forBig 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.
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Other editions
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Sridhar Alla
Big Data Analytics with Hadoop 3
Book
05/2018
Packt Publishing
€52.60
Shipment within 3-4 weeks
Person
Alla Sridhar :
Sridhar?Alla?is the co-founder and CTO of Blue Whale Consulting and is expert at helping companies (big and small) define their vision for systems and capabilities that will allow them to establish a strategic execution plan to deal with the ever-growing data collected to support analytics and product teams. He has very experienced at dealing with all aspects of data collection, security, governance, and processing as part of end-to-end big data analytics and machine learning initiatives (including predictive modeling, deep learning, and ML automation). Sridhar?is a published book author and an avid presenter at numerous conferences, including Strata, Hadoop World, and Spark Summit.? He also has several patents filed with the US PTO on large-scale computing and distributed systems.? He has over 18 years' experience writing code in Scala, Java, C, C++, Python, R, and Go, and has extensive hands-on knowledge of Spark, Flink, TensorFlow, Keras, Hadoop, Cassandra, HBase, MongoDB, Riak, Redis, Zeppelin, Mesos, Docker, Kafka, ElasticSearch, Solr, H2O, machine learning, text analytics, distributed computing, and high-performance computing. Sridhar lives with his wife and daughter in New Jersey and in his spare time loves blogging and coaching organizations on next-generation advancements in technology and their alignment with business goals.
Sridhar?Alla?is the co-founder and CTO of Blue Whale Consulting and is expert at helping companies (big and small) define their vision for systems and capabilities that will allow them to establish a strategic execution plan to deal with the ever-growing data collected to support analytics and product teams. He has very experienced at dealing with all aspects of data collection, security, governance, and processing as part of end-to-end big data analytics and machine learning initiatives (including predictive modeling, deep learning, and ML automation). Sridhar?is a published book author and an avid presenter at numerous conferences, including Strata, Hadoop World, and Spark Summit.? He also has several patents filed with the US PTO on large-scale computing and distributed systems.? He has over 18 years' experience writing code in Scala, Java, C, C++, Python, R, and Go, and has extensive hands-on knowledge of Spark, Flink, TensorFlow, Keras, Hadoop, Cassandra, HBase, MongoDB, Riak, Redis, Zeppelin, Mesos, Docker, Kafka, ElasticSearch, Solr, H2O, machine learning, text analytics, distributed computing, and high-performance computing. Sridhar lives with his wife and daughter in New Jersey and in his spare time loves blogging and coaching organizations on next-generation advancements in technology and their alignment with business goals.
Content
Table of Contents - Introduction to Hadoop
- Overview of Big Data Analytics
- Big Data Processing with MapReduce
- Scientific Computing and Big Data Analysis with Python and Hadoop
- Statistical Big Data Computing with R and Hadoop
- Batch analytics with Apache Spark
- Real time analytics with Apache Spark
- Batch analytics with Apache Flink
- Stream Processing with Apache Flink
- Visualizing Big Data
- Introduction to Cloud Computing
- Using Amazon Web Services
- Overview of Big Data Analytics
- Big Data Processing with MapReduce
- Scientific Computing and Big Data Analysis with Python and Hadoop
- Statistical Big Data Computing with R and Hadoop
- Batch analytics with Apache Spark
- Real time analytics with Apache Spark
- Batch analytics with Apache Flink
- Stream Processing with Apache Flink
- Visualizing Big Data
- Introduction to Cloud Computing
- Using Amazon Web Services
