In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.
Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications.
"synopsis" may belong to another edition of this title.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 47735010
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 47735010-n
Seller: California Books, Miami, FL, U.S.A.
Condition: New. Seller Inventory # I-9781800615045
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 47735010
Quantity: 2 available
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Hardback. Condition: New. In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications. Seller Inventory # LU-9781800615045
Quantity: Over 20 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 47735010-n
Quantity: 2 available
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 275 pages. 9.25x6.25x1.00 inches. In Stock. Seller Inventory # x-1800615043
Quantity: 2 available
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications. Seller Inventory # 9781800615045
Quantity: 1 available
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. PROGRAMMING BIG DATA APPLICATIONS | Talia Domenico | Buch | Englisch | 2024 | WSPC (Europe) | EAN 9781800615045 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 127384384
Quantity: 5 available
Seller: Rarewaves.com UK, London, United Kingdom
Hardback. Condition: New. In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications. Seller Inventory # LU-9781800615045
Quantity: Over 20 available