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Research on Synopsis

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Submitted By shru1407
Words 17478
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Chapter 9
A SURVEY OF SYNOPSIS CONSTRUCTION
IN DATA STREAMS

Abstract
The large volume of data streams poses unique space and time constraints on the computation process. Many query processing, database operations, and mining algorithms require efficient execution which can be difficult to achieve with a fast data stream. In many cases, it may be acceptable to generate approximate solutions for such problems. In recent years a number of synopsis structures have been developed, which can be used in conjunction with a variety of mining and query processing techniques in data stream processing. Some key synopsis methods include those of sampling, wavelets, sketches and histograms. In this chapter, we will provide a survey of the key synopsis techniques, and the mining techniques supported by such methods. We will discuss the challenges and tradeoffs associated with using different kinds of techniques, and the important research directions for synopsis construction.

1.

Introduction

Data streams pose a unique challenge to many database and data mining applications because of the computational and storage costs associated with the large volume of the data stream. In many cases, synopsis data structures

170

DATA STREAMS: MODELS AND ALGORITHMS

and statistics can be constructed from streams which are useful for a variety of applications. Some examples of such applications are as follows:
Approximate Query Estimation: The problem of query estimation is possibly the most widely used application of synopsis structures [11].
The problem is particularly important from an efficiency point of view, since queries usually have to be resolved in online time. Therefore, most synopsis methods such as sampling, histograms, wavelets and sketches are usually designed to be able to solve the query estimation problem.
Approximate Join Estimation: The

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