ACM Transactions on Database Systems (TODS)
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Making B+- trees cache conscious in main memory
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Database Architecture Optimized for the New Bottleneck: Memory Access
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Set Containment Joins: The Good, The Bad and The Ugly
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Evaluation of Main Memory Join Algorithms for Joins with Set Comparison Join Predicates
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Cache Conscious Algorithms for Relational Query Processing
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Adaptive algorithms for set containment joins
ACM Transactions on Database Systems (TODS)
Efficient processing of joins on set-valued attributes
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Buffering accesses to memory-resident index structures
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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We present two algorithms for set containment joins based on inverted lists. The first algorithm scans the left relation and determines for each tuple all the qualifying tuples by querying the inverted file for the right relation. The second algorithm employs the common inverted file for both relations. We focus on improving performance of algorithms in main memory by reducing number of L2 cache misses which is achieved by applying such techniques as partitioning and compression. We study algorithms analytically and experimentally and determine which one is better depending on parameters of the input relations. We also demonstrate that both algorithms are superior to some other known methods for set containment joins.