Big Data Analytics with R and Hadoop: set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics
Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who...
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Birmingham, UK [u.a.]
Packt Publ.
2013
|
| Edition: | 1. publ. |
| Series: | Packt open source
Community experience distilled |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Summary: | Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R |
| Physical Description: | VI, 219 S. graph. Darst. |
| ISBN: | 9781782163282 178216328X |
Staff View
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| adam_text | Table of Contents Preface___________________________________________________ 1 Chapter 1 : Getting Ready to Use R and Hadoop_________________13 Installing R Installing RStudio Understanding the features of R language Using R packages Performing data operations Increasing community support Performing data modeling in R Installing Hadoop Understanding different Hadoop modes Understanding Hadoop installation steps Installing Hadoop on Linux, Ubuntu flavor (single node cluster) Installing Hadoop on Linux, Ubuntu flavor (multinode cluster) Installing Cloudera Hadoop on Ubuntu Understanding Hadoop features Understanding HDFS Understanding the characteristics of HDFS Understanding MapReduce Learning the HDFS and MapReduce architecture Understanding the HDFS architecture Understanding HDFS components Understanding the MapReduce architecture Understanding MapReduce components Understanding the HDFS and MapReduce architecture by plot Understanding Hadoop subprojects Summary 14 15 16 16 16 17 18 19 20 20 20 23 25 28 28 28 28 30 30 30 31 31 31 33 36
Table of Contents Chapter 2: Writing Hadoop MapReduce Programs__________________ 37 Understanding the basics of MapReduce 37 Introducing Hadoop MapReduce 39 Listing Hadoop MapReduce entities 40 Understanding the Hadoop MapReduce scenario 40 Loading data into HDFS Executing the Map phase Shuffling and sorting Reducing phase execution Understanding the limitations of MapReduce Understanding Hadoop s ability to solve problems Understanding the different Java concepts used in Hadoop programming Understanding the Hadoop MapReduce fundamentals Understanding MapReduce objects Deciding the number of Maps in MapReduce Deciding the number of Reducers in MapReduce Understanding MapReduce dataflow Taking a closer look at Hadoop MapReduce terminologies Writing a Hadoop MapReduce example Understanding the steps to run a MapReduce job Learning to monitor and debug a Hadoop MapReduce job Exploring HDFS data Understanding several possible MapReduce definitions to solve business problems Learning the different ways to write Hadoop MapReduce in R Learning RHadoop Learning RHIPE Learning Hadoop streaming Summary 40 41 42 42 43 44 44 45 45 46 46 47 48 51 52 58 59 60 61 61 62 62 62 Chapter 3: Integrating R and Hadoop_______________________________ 63 Introducing RHİPE 64 Installing RHIPE 65 Installing Hadoop Installing R Installing protocol buffers Environment variables The rJava package installation Installing RHIPE Understanding the architecture of RHIPE Understanding RHIPE samples RHIPE sample program (Map only) Word count 65 66 66 66 67 67 68 69 69 71
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Table of Contents Understanding the RHIPE function reference 73 Initialization HDFS MapReduce 73 73 75 Introducing RHadoop Understanding the architecture of RHadoop Installing RHadoop Understanding RHadoop examples 76 77 77 79 Word count 81 Understanding the RHadoop function reference 82 The hdfs package The rmr package 82 85 Summary 85 Chapter 4: Using Hadoop Streaming with R______________________ 87 Understanding the basics of Hadoop streaming 87 Understanding how to run Hadoop streaming with R 92 Understanding a MapReduce application 92 Understanding how to code a MapReduce application 94 Understanding how to run a MapReduce application 98 Executing a Hadoop streaming job from the command prompt Executing the Hadoop streaming job from R or an RStudio console 98 99 Understanding how to explore the output of MapReduce application Exploring an output from the command prompt Exploring an output from R or an RStudio console 99 100 Understanding basic R functions used in Hadoop MapReduce scripts Monitoring the Hadoop MapReduce job Exploring the HadoopStreaming R package Understanding the hsTableReader function Understanding the hsKeyValReader function Understanding the hsLineReader function Running a Hadoop streaming job Executing the Hadoop streaming job 99 101 102 103 104 106 107 110 112 Summary Chapter 5: Learning Data Analytics with R and Hadoop Understanding the data analytics project life cycle Identifying the problem Designing data requirement Preprocessing data Performing analytics over data Visualizing data [пі] 112 ________ 113 113 114 114 115 115 116
Table of Contents Understanding data analytics problems Exploring web pages categorization Identifying the problem Designing data requirement Preprocessing data Performing analytics over data Visualizing data Computing the frequency of stock market change Identifying the problem Designing data requirement Preprocessing data Performing analytics over data Visualizing data Predicting the sale price of blue book for bulldozers - case study Identifying the problem Designing data requirement Preprocessing data Performing analytics over data Understanding Poisson-approximation resampling Summary 117 118 118 118 120 121 128 128 128 129 129 130 136 137 137 138 139 141 141 147 Chapter 6: Understanding Big Data Analysis with Machine Learning_______________________________________________ 149 Introduction to machine learning 149 Types of machine-learning algorithms 150 Supervised machine-learning algorithms 150 Linear regression 150 Linear regression with R Linear regression with R and Hadoop Logistic regression Logistic regression with R Logistic regression with R and Hadoop Unsupervised machine learning algorithm Clustering Clustering with R Performing clustering with R and Hadoop 152 154 157 159 159 162 162 163 163 Recommendation algorithms 167 Steps to generate recommendations in R 170 Generating recommendations with R and Hadoop 173 Summary 178 Chapter 7: Importing and Exporting Data from Various DBs_______179 Learning about data files as database 181 Understanding different types of files 182 Installing R packages 182
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Table of Contents Importing the data into R Exporting the data from R Understanding MySQL Installing MySQL Installing RMySQL Learning to list the tables and their structure Importing the data into R Understanding data manipulation Understanding Excel Installing Excel Importing data into R Exporting the data to Excel Understanding MongoDB Installing MongoDB Mapping SQL to MongoDB Mapping SQL to MongoQL Installing rmongodb Importing the data into R Understanding data manipulation Understanding SQLite Understanding features of SQLite Installing SQLite Installing RSQLite Importing the data into R Understanding data manipulation Understanding PostgreSQL Understanding features of PostgreSQL Installing PostgreSQL Installing RPostgreSQL Exporting the data from R Understanding Hive Understanding features of Hive Installing Hive Setting up Hive configurations Installing RHive Understanding RHive operations Understanding HBase Understanding HBase features Installing HBase Installing thrift Installing RHBase 182 183 183 184 184 184 185 185 186 186 186 187 187 188 189 190 190 190 191 192 193 193 193 193 194 194 195 195 195 196 197 197 197 198 199 199 200 200 201 203 203 ----------------------------------------- M ------------------------------------------
Table of Contents Importing the data into R Understanding data manipulation 204 204 Summary 204 Appendix: References R + Hadoop help materials R groups Hadoop groups R + Hadoop groups Popular R contributors Popular Hadoop contributors 205 205 207 207 208 208 209 211 Index [vi]
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| author | Prajapati, Vignesh |
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| isbn | 9781782163282 178216328X |
| language | English |
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| spelling | Prajapati, Vignesh Verfasser aut Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics Vignesh Prajapati 1. publ. Birmingham, UK [u.a.] Packt Publ. 2013 VI, 219 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Packt open source Community experience distilled Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R Apache Hadoop R (Computer program language) Big data Data mining Data structures (Computer science) Electronic data processing / Distributed processing Data architecture Data architecture management Datenverarbeitung Data Mining (DE-588)4428654-5 gnd rswk-swf Big Data (DE-588)4802620-7 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Hadoop (DE-588)1022420135 gnd rswk-swf Big Data (DE-588)4802620-7 s Data Mining (DE-588)4428654-5 s Datenanalyse (DE-588)4123037-1 s R Programm (DE-588)4705956-4 s Hadoop (DE-588)1022420135 s DE-604 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027163206&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Prajapati, Vignesh Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics Apache Hadoop R (Computer program language) Big data Data mining Data structures (Computer science) Electronic data processing / Distributed processing Data architecture Data architecture management Datenverarbeitung Data Mining (DE-588)4428654-5 gnd Big Data (DE-588)4802620-7 gnd Datenanalyse (DE-588)4123037-1 gnd R Programm (DE-588)4705956-4 gnd Hadoop (DE-588)1022420135 gnd |
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| title | Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics |
| title_auth | Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics |
| title_exact_search | Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics |
| title_full | Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics Vignesh Prajapati |
| title_fullStr | Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics Vignesh Prajapati |
| title_full_unstemmed | Big Data Analytics with R and Hadoop set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics Vignesh Prajapati |
| title_short | Big Data Analytics with R and Hadoop |
| title_sort | big data analytics with r and hadoop set up an integrated infrastructure of r and hadoop to turn your data analytics into big data analytics |
| title_sub | set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics |
| topic | Apache Hadoop R (Computer program language) Big data Data mining Data structures (Computer science) Electronic data processing / Distributed processing Data architecture Data architecture management Datenverarbeitung Data Mining (DE-588)4428654-5 gnd Big Data (DE-588)4802620-7 gnd Datenanalyse (DE-588)4123037-1 gnd R Programm (DE-588)4705956-4 gnd Hadoop (DE-588)1022420135 gnd |
| topic_facet | Apache Hadoop R (Computer program language) Big data Data mining Data structures (Computer science) Electronic data processing / Distributed processing Data architecture Data architecture management Datenverarbeitung Data Mining Big Data Datenanalyse R Programm Hadoop |
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