0
Your cart

Your cart is empty

Books > Computing & IT > Computer programming

Buy Now

Synopses for Massive Data - Samples, Histograms, Wavelets, Sketches (Paperback) Loot Price: R2,329
Discovery Miles 23 290
Synopses for Massive Data - Samples, Histograms, Wavelets, Sketches (Paperback): Graham Cormode, Minos Garofalakis, Peter J....

Synopses for Massive Data - Samples, Histograms, Wavelets, Sketches (Paperback)

Graham Cormode, Minos Garofalakis, Peter J. Haas, Chris Jermaine

Series: Foundations and Trends (R) in Databases

 (sign in to rate)
Loot Price R2,329 Discovery Miles 23 290 | Repayment Terms: R218 pm x 12*

Bookmark and Share

Expected to ship within 10 - 15 working days

Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches describes basic principles and recent developments in building approximate synopses (i.e., lossy, compressed representations) of massive data. Such synopses enable approximate query processing, in which the user's query is executed against the synopsis instead of the original data. The monograph focuses on the four main families of synopses: random samples, histograms, wavelets, and sketches. A random sample comprises a "representative" subset of the data values of interest, obtained via a stochastic mechanism. Samples can be quick to obtain, and can be used to approximately answer a wide range of queries. A histogram summarizes a data set by grouping the data values into subsets, or "buckets," and then, for each bucket, computing a small set of summary statistics that can be used to approximately reconstruct the data in the bucket. Histograms have been extensively studied and have been incorporated into the query optimizers of virtually all commercial relational DBMSs. Wavelet-based synopses were originally developed in the context of image and signal processing. The data set is viewed as a set of M elements in a vector - i.e., as a function defined on the set {0, 1, 2, . . ., M-1} - and the wavelet transform of this function is found as a weighted sum of wavelet "basis functions." The weights, or coefficients, can then be "thresholded," for example, by eliminating coefficients that are close to zero in magnitude. The remaining small set of coefficients serves as the synopsis. Wavelets are good at capturing features of the data set at various scales. Sketch summaries are particularly well suited to streaming data. Linear sketches, for example, view a numerical data set as a vector or matrix, and multiply the data by a fixed matrix. Such sketches are massively parallelizable. They can accommodate streams of transactions in which data is both inserted and removed. Sketches have also been used successfully to estimate the answer to COUNT DISTINCT queries, a notoriously hard problem. Synopses for Massive Data describes and compares the different synopsis methods. It also discusses the use of AQP within research systems, and discusses challenges and future directions. It is essential reading for anyone working with, or doing research on massive data.

General

Imprint: Now Publishers Inc
Country of origin: United States
Series: Foundations and Trends (R) in Databases
Release date: December 2011
First published: 2012
Authors: Graham Cormode • Minos Garofalakis • Peter J. Haas • Chris Jermaine
Dimensions: 234 x 156 x 16mm (L x W x T)
Format: Paperback
Pages: 308
ISBN-13: 978-1-60198-516-3
Categories: Books > Computing & IT > Computer programming > General
Books > Computing & IT > Applications of computing > Databases > General
Promotions
LSN: 1-60198-516-9
Barcode: 9781601985163

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!

You might also like..

Problem Solving with C++ - Global…
Walter Savitch Paperback R2,481 Discovery Miles 24 810
Introducing Delphi Programming - Theory…
John Barrow, Linda Miller, … Paperback  (1)
R863 Discovery Miles 8 630
C++ Programming - Program Design…
D. Malik Paperback R1,626 R1,507 Discovery Miles 15 070
Program Construction - Calculating…
Roland Backhouse Paperback R2,664 Discovery Miles 26 640
Programming Logic & Design…
Joyce Farrell Paperback R1,227 R1,146 Discovery Miles 11 460
C++ How to Program: Horizon Edition
Harvey Deitel, Paul Deitel Paperback R1,844 Discovery Miles 18 440
Sams Teach Yourself: Beginning…
Greg Perry, Dean Miller Paperback R599 R244 Discovery Miles 2 440
Introduction to Computational Economics…
Hans Fehr, Fabian Kindermann Hardcover R4,347 Discovery Miles 43 470
Java How to Program, Late Objects…
Paul Deitel, Harvey Deitel Paperback R900 R750 Discovery Miles 7 500
Data Abstraction and Problem Solving…
Janet Prichard, Frank Carrano Paperback R2,238 Discovery Miles 22 380
Arduino for Musicians - A Complete Guide…
Brent Edstrom Hardcover R3,714 Discovery Miles 37 140
The Data Quality Blueprint - A Practical…
John Parkinson Hardcover R1,638 Discovery Miles 16 380

See more

Partners