By Topic

Hash-merge join: a non-blocking join algorithm for producing fast and early join results

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
M. F. Mokbel ; Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA ; M. Lu ; W. G. Aref

We introduce the hash-merge join algorithm (HMJ, for short); a new nonblocking join algorithm that deals with data items from remote sources via unpredictable, slow, or bursty network traffic. The HMJ algorithm is designed with two goals in mind: (1) minimize the time to produce the first few results, and (2) produce join results even if the two sources of the join operator occasionally get blocked. The HMJ algorithm has two phases: The hashing phase and the merging phase. The hashing phase employs an in-memory hash-based join algorithm that produces join results as quickly as data arrives. The merging phase is responsible for producing join results if the two sources are blocked. Both phases of the HMJ algorithm are connected via a flushing policy that flushes in-memory parts into disk storage once the memory is exhausted. Experimental results show that HMJ combines the advantages of two state-of-the-art nonblocking join algorithms (XJoin and Progressive Merge Join) while avoiding their shortcomings.

Published in:

Data Engineering, 2004. Proceedings. 20th International Conference on

Date of Conference:

30 March-2 April 2004