TY - BOOK ID - 80734674 TI - Big data analytics with R and Hadoop PY - 2013 SN - 9781782163299 1782163298 1306166055 9781306166058 178216328X 9781782163282 PB - Birmingham : Packt Publishing, DB - UniCat KW - Electronic data processing KW - Data mining KW - Data structures (Computer science) KW - R (Computer program language) KW - GNU-S (Computer program language) KW - Domain-specific programming languages KW - Information structures (Computer science) KW - Structures, Data (Computer science) KW - Structures, Information (Computer science) KW - File organization (Computer science) KW - Abstract data types (Computer science) KW - Algorithmic knowledge discovery KW - Factual data analysis KW - KDD (Information retrieval) KW - Knowledge discovery in data KW - Knowledge discovery in databases KW - Mining, Data KW - Database searching KW - Distributed computer systems in electronic data processing KW - Distributed computing KW - Distributed processing in electronic data processing KW - Computer networks KW - Distributed processing KW - Apache Hadoop. KW - Hadoop KW - E-books KW - Big data. KW - Data mining. KW - Data sets, Large KW - Large data sets KW - Data sets UR - https://www.unicat.be/uniCat?func=search&query=sysid:80734674 AB - If you’re an R developer looking to harness the power of big data analytics with Hadoop, then this book tells you everything you need to integrate the two. You’ll end up capable of building a data analytics engine with huge potential. Write Hadoop MapReduce within R Learn data analytics with R and the Hadoop platform Handle HDFS data within R Understand Hadoop streaming with R Encode and enrich datasets into R In Detail Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing. Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS of Hadoop. You will start with the installation and configuration of R and Hadoop. Next, you will discover information on various practical data analytics examples with R and Hadoop. Finally, you will learn how to import/export from various data sources to R. Big Data Analytics with R and Hadoop will also give you an easy understanding of the R and Hadoop connectors RHIPE, RHadoop, and Hadoop streaming. ER -