Spark cookbook : over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLib, and GraphX libraries /

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If you are a data engineer, an application developer, or a data scientist who would like to leverage the power of Apache Spark to get better insights from big data, then this is the book for you.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Yadav, Rishi (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2015.
Colección:Quick answers to common problems.
Temas:
Spark (Electronic resource : Apache Software Foundation)
Big data.
Data mining > Computer programs.
Données volumineuses.
Exploration de données (Informatique) > Logiciels.
COMPUTERS > Computer Literacy.
COMPUTERS > Computer Science.
COMPUTERS > Data Processing.
COMPUTERS > Hardware > General.
COMPUTERS > Information Technology.
COMPUTERS > Machine Theory.
COMPUTERS > Reference.
Big data
Acceso en línea:Texto completo
Texto completo

MARC

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100 1 |a Yadav, Rishi,  |e author. 
245 1 0 |a Spark cookbook :  |b over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLib, and GraphX libraries /  |c Rishi Yadav. 
246 3 0 |a Over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLib, and GraphX libraries 
246 3 |a Over sixty recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLib, and GraphX libraries 
264 1 |a Birmingham, UK :  |b Packt Publishing,  |c 2015. 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Quick answers to common problems 
588 0 |a Online resource; title from cover (Safari, viewed August 13, 2015). 
500 |a Includes index. 
505 0 |a Cover -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: Getting Started with Apache Spark -- Introduction -- Installing Spark from binaries -- Building the Spark source code with Maven -- Launching Spark on Amazon EC2 -- Deploying on a cluster in standalone mode -- Deploying on a cluster with Mesos -- Deploying on a cluster with YARN -- Using Tachyon as an off-heap storage layer -- Chapter 2: Developing Applications with Spark -- Introduction 
505 8 |a Exploring the Spark shellDeveloping Spark applications in Eclipse with Maven -- Developing Spark applications in Eclipse with SBT -- Developing a Spark application in IntelliJ IDEA with Maven -- Developing a Spark application in IntelliJ IDEA with SBT -- Chapter 3: External Data Sources -- Introduction -- Loading data from the local filesystem -- Loading data from HDFS -- Loading data from HDFS using a custom InputFormat -- Loading data from Amazon S3 -- Loading data from Apache Cassandra -- Loading data from relational databases -- Chapter 4: Spark SQL 
505 8 |a IntroductionUnderstanding Catalyst optimizer -- Creating HiveContext -- Inferring schema using case classes -- Programmatically specifying the schema -- Loading and saving data using the Parquet format -- Loading and saving data using the JSON format -- Loading and saving data from relational databases -- Loading and saving data from an arbitrary source -- Chapter 5: Spark Streaming -- Introduction -- Word count using Streaming -- Streaming Twitter data -- Streaming using Kafka -- Chapter 6: Getting Started with Machine Learning using MLlib -- Introduction 
505 8 |a Creating vectorsCreating a labeled point -- Creating matrices -- Calculating summary statistics -- Calculating correlation -- Doing hypothesis testing -- Creating machine learning pipelines using ML -- Chapter 7: Supervised Learning with MLlib Regression -- Introduction -- Using linear regression -- Understanding cost function -- Doing linear regression with lasso -- Doing ridge regression -- Chapter 8: Supervised Learning with MLlib â€? Classification -- Introduction -- Doing classification using logistic regression 
505 8 |a Doing binary classification using SVMDoing classification using decision trees -- Doing classification using Random Forests -- Doing classification using Gradient Boosted Trees -- Doing classification with NaÃv̄e Bayes -- Chapter 9: Unsupervised Learning -- Introduction -- Clustering using k-means -- Dimensionality reduction with principal component analysis -- Dimensionality reduction with singular value decomposition -- Chapter 10: Recommender Systems -- Introduction -- Collaborative filtering using explicit feedback 
520 |a If you are a data engineer, an application developer, or a data scientist who would like to leverage the power of Apache Spark to get better insights from big data, then this is the book for you. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
630 0 0 |a Spark (Electronic resource : Apache Software Foundation) 
630 0 7 |a Spark (Electronic resource : Apache Software Foundation)  |2 fast 
650 0 |a Big data. 
650 0 |a Data mining  |x Computer programs. 
650 6 |a Données volumineuses. 
650 6 |a Exploration de données (Informatique)  |x Logiciels. 
650 7 |a COMPUTERS  |x Computer Literacy.  |2 bisacsh 
650 7 |a COMPUTERS  |x Computer Science.  |2 bisacsh 
650 7 |a COMPUTERS  |x Data Processing.  |2 bisacsh 
650 7 |a COMPUTERS  |x Hardware  |x General.  |2 bisacsh 
650 7 |a COMPUTERS  |x Information Technology.  |2 bisacsh 
650 7 |a COMPUTERS  |x Machine Theory.  |2 bisacsh 
650 7 |a COMPUTERS  |x Reference.  |2 bisacsh 
650 7 |a Big data  |2 fast 
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776 0 8 |i Print version:  |n Druck-Ausgabe  |t Yadav, Rishi. Spark Cookbook 
830 0 |a Quick answers to common problems. 
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856 4 0 |u https://learning.oreilly.com/library/view/~/9781783987061/?ar  |z Texto completo 
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938 |a EBSCOhost  |b EBSC  |n 1044814 
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938 |a YBP Library Services  |b YANK  |n 12546797 
994 |a 92  |b IZTAP 

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