Big data for chimps / (Record no. 11630)

MARC details
000 -LEADER
fixed length control field 01831cam a2200349 i 4500
CONTROL NUMBER
control field 19155224
DATE AND TIME OF LATEST TRANSACTION
control field 20190415162815.0
FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160628t20152016caua 001 0 eng d
LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2016304965
INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789352132447
SYSTEM CONTROL NUMBER
System control number (OCoLC)ocn930445550
CATALOGING SOURCE
Original cataloging agency YDXCP
Language of cataloging eng
Transcribing agency YDXCP
Description conventions rda
Modifying agency OCLCO
-- OCLCF
-- DLC
AUTHENTICATION CODE
Authentication code lccopycat
LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.B45
Item number K738 2015
DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.7
Edition number 23
Item number KRO
MAIN ENTRY--PERSONAL NAME
Personal name Kromer, Philip,
Relator term author.
TITLE STATEMENT
Title Big data for chimps /
Statement of responsibility, etc Philip Kromer and Russell Jurney.
VARYING FORM OF TITLE
Title proper/short title Big data for chimps :
Remainder of title a guide to massive-scale data processing in practice
PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Mumbai :
Name of publisher, distributor, etc Shroff Publishers & Distributors,
Date of publication, distribution, etc 2018.
PHYSICAL DESCRIPTION
Extent xv, 200 p. :
Other physical details ill. ;
Dimensions 24 cm
GENERAL NOTE
General note Includes index.
SUMMARY, ETC.
Summary, etc "Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data"--
SUBJECT ADDED ENTRY--UNIFORM TITLE
Uniform title Apache Hadoop.
SUBJECT ADDED ENTRY--UNIFORM TITLE
Uniform title MapReduce (Computer file)
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big data.
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pattern recognition systems.
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Electronic data processing.
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business
General subdivision Data processing.
ADDED ENTRY--PERSONAL NAME
Personal name Jurney, Russell,
Relator term author.
ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     Learning Resource Centre Learning Resource Centre 18/04/2019 20 333.00   005.7 KRO 13883 18/04/2019 450.00 18/04/2019 Books
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