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Mastering Apache Spark: Real-Time Big Data Analytics: Build Large-Scale Data Processing Pipelines with Apache Spark - Softcover

 
9798303148406: Mastering Apache Spark: Real-Time Big Data Analytics: Build Large-Scale Data Processing Pipelines with Apache Spark
  • PublisherIndependently published
  • Publication date2024
  • ISBN 13 9798303148406
  • BindingPaperback
  • LanguageEnglish
  • Number of pages187

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Chesterfield, Greyson
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ISBN 13: 9798303148406
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Greyson Chesterfield
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Paperback. Condition: new. Paperback. Unlock the power of big data with Mastering Apache Spark: Real-Time Big Data Analytics! This comprehensive guide is your ultimate resource for building, processing, and analyzing large-scale data using Apache Spark, the fast, flexible, and powerful open-source framework for big data processing. Whether you're a data engineer, scientist, or analyst, this book will teach you how to harness Spark's real-time analytics capabilities to process and analyze massive datasets.Apache Spark is widely used for its speed, ease of use, and scalability. It's the go-to solution for building data pipelines, running machine learning algorithms, and processing streams of real-time data. In this book, you'll learn everything from the fundamentals of Spark to advanced techniques for scaling your big data workflows.What's Inside: Getting Started with Apache Spark: Learn the core concepts behind Apache Spark, including Spark RDDs, DataFrames, and Spark SQL, and how to set up Spark on your system or in the cloud.Real-Time Data Processing: Dive into real-time data processing with Spark Streaming, handling live data streams, and building real-time analytics applications.Building Data Pipelines: Learn how to design and implement scalable data pipelines that can process large volumes of structured and unstructured data.Data Analytics with Spark: Explore how to analyze big data using Spark's powerful libraries, including Spark MLlib for machine learning and Spark GraphX for graph processing.Optimizing Spark Performance: Discover strategies to optimize Spark performance, including partitioning, caching, and using the Catalyst optimizer for SQL queries.Advanced Spark Topics: Get hands-on with advanced topics like Spark on Kubernetes, Spark integration with Hadoop, and deploying Spark on cloud platforms such as AWS and Azure.Batch vs. Stream Processing: Learn when to use batch processing and when to go for stream processing for different use cases in data analytics.Use Cases and Real-World Applications: Explore real-world use cases for Spark in industries like finance, healthcare, e-commerce, and IoT.By the end of this book, you'll be equipped with the knowledge and hands-on experience to build efficient, scalable data pipelines and perform advanced real-time big data analytics using Apache Spark.Ready to master big data with Spark? Grab your copy now and start building powerful, high-performance data solutions that scale with your business needs! Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798303148406

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Taschenbuch. Condition: Neu. Neuware - Unlock the power of big data with Mastering Apache Spark: Real-Time Big Data Analytics! This comprehensive guide is your ultimate resource for building, processing, and analyzing large-scale data using Apache Spark, the fast, flexible, and powerful open-source framework for big data processing. Whether you're a data engineer, scientist, or analyst, this book will teach you how to harness Spark's real-time analytics capabilities to process and analyze massive datasets. Seller Inventory # 9798303148406

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Paperback. Condition: new. Paperback. Unlock the power of big data with Mastering Apache Spark: Real-Time Big Data Analytics! This comprehensive guide is your ultimate resource for building, processing, and analyzing large-scale data using Apache Spark, the fast, flexible, and powerful open-source framework for big data processing. Whether you're a data engineer, scientist, or analyst, this book will teach you how to harness Spark's real-time analytics capabilities to process and analyze massive datasets.Apache Spark is widely used for its speed, ease of use, and scalability. It's the go-to solution for building data pipelines, running machine learning algorithms, and processing streams of real-time data. In this book, you'll learn everything from the fundamentals of Spark to advanced techniques for scaling your big data workflows.What's Inside: Getting Started with Apache Spark: Learn the core concepts behind Apache Spark, including Spark RDDs, DataFrames, and Spark SQL, and how to set up Spark on your system or in the cloud.Real-Time Data Processing: Dive into real-time data processing with Spark Streaming, handling live data streams, and building real-time analytics applications.Building Data Pipelines: Learn how to design and implement scalable data pipelines that can process large volumes of structured and unstructured data.Data Analytics with Spark: Explore how to analyze big data using Spark's powerful libraries, including Spark MLlib for machine learning and Spark GraphX for graph processing.Optimizing Spark Performance: Discover strategies to optimize Spark performance, including partitioning, caching, and using the Catalyst optimizer for SQL queries.Advanced Spark Topics: Get hands-on with advanced topics like Spark on Kubernetes, Spark integration with Hadoop, and deploying Spark on cloud platforms such as AWS and Azure.Batch vs. Stream Processing: Learn when to use batch processing and when to go for stream processing for different use cases in data analytics.Use Cases and Real-World Applications: Explore real-world use cases for Spark in industries like finance, healthcare, e-commerce, and IoT.By the end of this book, you'll be equipped with the knowledge and hands-on experience to build efficient, scalable data pipelines and perform advanced real-time big data analytics using Apache Spark.Ready to master big data with Spark? Grab your copy now and start building powerful, high-performance data solutions that scale with your business needs! Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798303148406

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