Multi-table joins through bitmapped join indices

O’Neil, Patrick E.; Graefe, Goetz

doi:10.1145/211990.212001

Cited by 225 publications

(110 citation statements)

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“…If a tuple does not belong to the context relation R B , we must set its corresponding bits in the vectors to 0. In fact, logic bit vector operations easily allow us to integrate the proposed techniques with bitmap index-based solutions for selection conditions [21,22,16] and join queries [24].…”

Section: Dealing With Boolean Conditionsmentioning

confidence: 99%

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On contextual ranking queries in databases

2013

Information Systems

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In this paper, we identify a novel and interesting type of queries, contextual ranking queries, which return the ranks of query tuples among some context tuples given in the queries. Contextual ranking queries are useful for olap and decision support applications in non-traditional data exploration. They provide a mechanism to quickly identify where tuples stand within the context. In this paper, we extend the sql language to express contextual ranking queries and propose a general partition-based framework for processing them. In this framework, we use a novel method that utilizes bitmap indices built on ranking functions. This method can efficiently identify a small number of candidate tuples, thus achieves lower cost than alternative methods. We analytically investigate the advantages and drawbacks of these methods, according to a preliminary cost model. Experimental results suggest that the algorithm using bitmap indices on ranking functions can be substantially more efficient than other methods.

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Section: Dealing With Boolean Conditionsmentioning

confidence: 99%

“…The synthetic table can be viewed as the results after such conditions are applied. To obtain the results, the approach of using bitmap index has been well-studied and is shown to be very efficient for range selections and star-joins [24,16,21,22]. In Section 5.1.4 we have discussed how to integrate with such techniques.…”

Section: Join Queriesmentioning

confidence: 99%

On contextual ranking queries in databases

2013

Information Systems

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“…Following the publication of O'Neil's seminal paper on bitmap indexes [20], there has been a number of publications on the subject [5,6,7,15,18,22,21,26,32,39,38,37]. In addition, there are a number of techniques from closely related indexing techniques which can be easily adapted to bitmap indexes as well, such as inverted files [31] and signature files [11,40].…”

Section: Reviewmentioning

confidence: 99%

Performances of Multi-Level and Multi-Component Compressed BitmapIndices

Wu¹,

Stockinger²,

Shoshani³

2007

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Bitmap indexes are known as the most effective indexing methods for range queries on append-only data, especially for low cardinality attributes. Recently, bitmap indexes were also shown to be just as effective for high cardinality attributes when certain compression methods are applied. There are many different bitmap indexes in the literature but no definite comparison among them has been made, largely because there is no accurate prediction of their index sizes and search time. This paper presents a systematic evaluation of two large subsets of compressed bitmap indexes that use multi-component and multi-level encodings. We combine extensive analyses with ample experimental results to confirm them, whereas earlier studies of these indexes are either empirical or for uncompressed indexes only. Our analyses provide highly accurate predictions that agree with test measurements. These analyses not only identify the best methods in terms of index size and query processing cost, but also reveal new ways of using multi-level methods that significantly improve their performance. Using the best parameters obtained through analyses, we produce three two-level indexes with the optimal computational complexity. Furthermore, the fastest two-level indexes are predicted and observed to be 5 to 10 times faster than other well-known indexes.

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“…Also related to our work are Bloom filters [4] and bit-map join indices [10] as ways of efficiently computing joins with the aid of pre-computation. Additionally, and closer related, are the techniques of hash teams [6] and generalized hash teams [8], in which the objective is to minimize the number of performed operations in hash-based evaluation plans by sharing computation and hash table storage space.…”

Section: Related Workmentioning

confidence: 99%

Maximizing the Output Rate of Multi-Way Join Queries over Streaming Information Sources

Viglas

Naughton

Burger

2003

Proceedings 2003 VLDB Conference

186

175

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Recently there has been a growing interest in join query evaluation for scenarios in which inputs arrive at highly variable and unpredictable rates. In such scenarios, the focus shifts from completing the computation as soon as possible to producing a prefix of the output as soon as possible. To handle this shift in focus, most solutions to date rely upon some combination of streaming binary operators and "on-the-fly" execution plan reorganization. In contrast, we consider the alternative of extending existing symmetric binary join operators to handle more than two inputs. Toward this end, we have completed a prototype implementation of a multi-way join operator, which we term the "MJoin" operator, and explored its performance. Our results show that in many instances the MJoin produces outputs sooner than any tree of binary operators. Additionally, since MJoins are completely symmetric with respect to their inputs, they can reduce the need for expensive runtime plan reorganization. This suggests that supporting multi-way joins in a single, symmetric, streaming operator may be a useful addition to systems that support queries over input streams from remote sites.

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Multi-table joins through bitmapped join indices

Abstract: This technical note shows how to combine some well-known techniques to create a method that will efficiently execute common multi-table joins. We concentrate on a commonly occurring type of join known as a star-join, although the method presented will generalize to any type of multi-

Cited by 225 publications

References 1 publication

On contextual ranking queries in databases

On contextual ranking queries in databases

Performances of Multi-Level and Multi-Component Compressed BitmapIndices

Maximizing the Output Rate of Multi-Way Join Queries over Streaming Information Sources

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