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020 _a9789811305504
024 7 _a10.1007/978-981-13-0550-4
_2doi
040 _bspa
_dES-MaUEC
_cES-MaUEC
050 4 _aQA76.9.B45 2019 EB
090 4 _aQA76.9.B45
245 0 0 _aBig Data Processing Using Spark in Cloud
_cedited by Mamta Mittal, Valentina E. Balas, Lalit Mohan Goyal, Raghvendra Kumar.
264 1 _aSingapore
_bSpringer Singapore :
_bImprint: Springer
_c2019.
300 _a1 recurso en línea (XIII, 264 páginas)
_b89 ilustraciones, 62 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 0 _aEngineering (Springer-11647)
490 0 _aStudies in Big Data
_x2197-6503
_v43
505 0 _aConcepts of Big Data and Apache Spark -- Big Data Analysis in Cloud and Machine Learning -- Security Issues and Challenges related to Big Data -- Big Data Security Solutions in Cloud -- Data Science and Analytics -- Big Data Technologies -- Data Analysis with Casandra and Spark -- Spin up the Spark Cluster -- Learn Scala -- IO for Spark -- Processing with Spark -- Spark Data Frames and Spark SQL -- Machine Learning and Advanced Analytics -- Parallel Programming with Spark -- Distributed Graph Processing with Spark -- Real Time Processing with Spark -- Spark in Real World -- Case Studies.
520 3 _aThe 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.
988 _aPrimersemestre_2019_Engineering
650 7 _2embne
_9495511
_aDatos masivos
650 7 _2embne
_aInformática en la nube
_9666069
700 1 _aBalas, Valentina E.
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aGoyal, Lalit Mohan.
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKumar, Raghvendra.
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMittal, Mamta.
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
776 0 8 _iPrinted edition:
_z9789811305498
776 0 8 _iPrinted edition:
_z9789811305511
776 0 8 _iPrinted edition:
_z9789811344480
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-13-0550-4
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _aSI
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_dz
_feng
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_b07/2019
_ejf
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