Big Data Analytics with Hadoop and Spark by Shikha Mehta (.ePUB)+
File Size: 43.6 MB
Big Data Analytics with Hadoop and Spark: A hands-on guide to big data engineering and scalable analytics by Shikha Mehta
Requirements: .ePUB, .PDF reader, 43.6 MB | True EPUB, PDF (conv)
Overview: Technologies like Hadoop and Spark, powered by the Cloudera platform, have become essential for storing, processing, and analyzing Big Data across various industries, including finance, healthcare, e-commerce, and research in today’s data-driven world. This book systematically navigates the entire ecosystem, starting with Big Data fundamentals, security, and HDFS architecture before mastering MapReduce through weather and stock data case studies. Readers will gain hands-on experience with the Cloudera framework, learning high-level scripting with Pig Latin and structured data warehousing using HiveQL’s Metastore and partitions. Additionally, it explores NoSQL versatility with HBase and MongoDB’s CAP theorem, followed by Scala programming and Spark’s high-speed in-memory engine. You will learn to optimize queries with the Catalyst optimizer and process complex Parquet or JSON files using Spark SQL DataFrames. The book also covers machine learning pipelines with spark.ml for professional-grade classification and clustering applications. By the end of this book, readers will be able to develop strong conceptual clarity and practical expertise in Big Data analytics. This will enable them to confidently design, implement, and manage scalable data processing solutions, preparing them to solve real-world data challenges and take on professional roles in Big Data engineering and analytics. This book is ideal for students, researchers, and academicians. It empowers aspiring Big Data engineers, data scientists, and software engineers. Readers should possess basic programming knowledge and database fundamentals to master Hadoop and Spark for professional-grade data science and faculty-level instruction.
Genre: Non-Fiction > Tech & Devices
Free Download links: