ACM Home Page
Please provide us with feedback. Feedback
Join processing in database systems with large main memories
Full text PdfPdf (1.41 MB)
Source ACM Transactions on Database Systems (TODS) archive
Volume 11 ,  Issue 3  (September 1986) table of contents
Pages: 239 - 264  
Year of Publication: 1986
ISSN:0362-5915
Author
Leonard D. Shapiro  North Dakota State Univ.
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 27,   Downloads (12 Months): 272,   Citation Count: 116
Additional Information:

abstract   references   cited by   index terms   review   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/6314.6315
What is a DOI?

ABSTRACT

We study algorithms for computing the equijoin of two relations in a system with a standard architecture hut with large amounts of main memory. Our algorithms are especially efficient when the main memory available is a significant fraction of the size of one of the relations to he joined; but they can be applied whenever there is memory equal to approximately the square root of the size of one relation. We present a new algorithm which is a hybrid of two hash-based algorithms and which dominates the other algorithms we present, including sort-merge. Even in a virtual memory environment, the hybrid algorithm dominates all the others we study. Finally, we describe how three popular tools to increase the efficiency of joins, namely filters, Babb arrays, and semijoins, can he grafted onto any of our algorithms.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
2
3
 
4
BLASGEN, M. W., AND ESWARAN, K. P. Storage and access in relational databases. IBM Syst. J. 16, 4 (1977).
 
5
6
 
7
DEWITT, D., AND GERBER, R. Multiprocessor hash-based join algorithms. In Proceedings of the Conference on Very Large Data Bases (Stockholm, 1985).
 
8
DIGITAL EQUIPMENT CORP. Product announcement, 1984.
9
 
10
GARCIA-MOLINA, H., LIPTON, R., AND VALDES, J. A massive memory machine. IEEE Trans. Comput. C-33, 5 (1984), 391-399.
 
11
GOODMAN, J.R. An investigation of multiprocessor structures and algorithms for data base management. Electronics Research Lab. Memo. ECB/ERL M81/33, Univ. of California, Berkeley, 1981.
12
 
13
KIESSLINO, W. Tuneable dynamic filter algorithms for high performance database systems. In Proceedings of the International Workshop on High Level Computer Architecture (May 1984), 6.10-6.20.
 
14
KITSUREOAWA, M., ET AL. Application of hash to data base machine and its architecture. New Generation Comput. 1 (1983), 62-74.
 
15
16
 
17
SACCO, G. M., AND SCHOLNICK, M. A mechanism for managing the buffer pool in a relational database system using the hot-set model. Computer Science Res. Rep. RJ-3354, IBM Research Lab., San Jose, Calif., Jan. 1982.
18
 
19
SLOTNICK, D. Logic per track devices. In Advances in Computers, Vol. 10, J. Tou, Ed., Academic Press, New York, 1970, 291-296.
20
21
 
22
YAMANE, Y. A hash join technique for relational database systems. In Proceedings of the International Conference on Foundations of Data Organization (Kyoto, May 1985}.

CITED BY  116


REVIEW

"Vasant B. Kaujalgi : Reviewer"

Database Management Systems (DBMSs) are playing an increasing role in the development of integrated packages. The design strategies of DBMSs have changed over the years. Relational DBMSs, even though simple in structure, are considerably complex  more...