MARC Record from Library of Congress

LEADER: 01980cam a2200409 i 4500
001 2015304861
003 DLC
005 20150723105409.0
008 150702s2015 cc a 001 0 eng c
010 $a 2015304861
015 $aGBB349884$2bnb
016 7 $a016416144$2Uk
020 $a9781449358624$q(pbk.)
020 $a1449358624$q(pbk.)
035 $a(OCoLC)ocn844872440
040 $aUKMGB$beng$cUKMGB$dBTCTA$dYDXCP$dOCLCO$dOCLCQ$erda$dSINLB$dCOD$dCDX$dILC$dDLC
042 $apcc
050 00 $aQA76.9.D343$bK363 2015
082 00 $a006.3/12$223
100 1 $aKarau, Holden,$eauthor.
245 10 $aLearning Spark /$cHolden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia.
250 $aFirst edition.
264 1 $aBeijing ;$aSebastopol :$bO'Reilly,$c[2015]
300 $axvi, 254 pages :$billustrations ;$c24 cm
336 $atext$2rdacontent
337 $aunmediated$2rdamedia
338 $avolume$2rdacarrier
500 $aSubtitle on cover: Lightning-fast data analysis.
500 $aIncludes index.
520 $aThis book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. You'll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.--$cSource other than Library of Congress.
505 0 $aIntroduction to data analysis with Spark -- Downloading Spark and getting started -- Programming with RDDs -- Working with key/value pairs -- Loading and saving your data -- Advanced Spark programming -- Running on a cluster -- Tuning and debugging Spark -- Spark SQL -- Spark streaming -- Machine learning with MLlib.
630 00 $aSpark (Electronic resource : Apache Software Foundation)
650 0 $aBig data.
650 0 $aData mining$xComputer programs.
700 1 $aKonwinski, Andy,$eauthor.
700 1 $aWendell, Patrick,$eauthor.
700 1 $aZaharia, Matei,$eauthor.