ACM Transactions on Database Systems (TODS)
A data locality optimizing algorithm
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Shoring up persistent applications
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Thread scheduling for cache locality
Proceedings of the seventh international conference on Architectural support for programming languages and operating systems
An analysis of database workload performance on simultaneous multithreaded processors
Proceedings of the 25th annual international symposium on Computer architecture
Thread scheduling for out-of-core applications with memory server on multicomputers
Proceedings of the sixth workshop on I/O in parallel and distributed systems
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Making B+- trees cache conscious in main memory
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Pipelining in multi-query optimization
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Optimizing multidimensional index trees for main memory access
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Improving index performance through prefetching
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Fractal prefetching B+-Trees: optimizing both cache and disk performance
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Common expression analysis in database applications
SIGMOD '82 Proceedings of the 1982 ACM SIGMOD international conference on Management of data
On the Multiple-Query Optimization Problem
IEEE Transactions on Knowledge and Data Engineering
Data page layouts for relational databases on deep memory hierarchies
The VLDB Journal — The International Journal on Very Large Data Bases
Using Common Subexpressions to Optimize Multiple Queries
Proceedings of the Fourth International Conference on Data Engineering
Database Architecture Optimized for the New Bottleneck: Memory Access
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
DBMSs on a Modern Processor: Where Does Time Go?
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Query Scheduling in Multi Query Optimization
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Cache Conscious Algorithms for Relational Query Processing
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
The Memory Performance of DSS Commercial Workloads in Shared-Memory Multiprocessors
HPCA '97 Proceedings of the 3rd IEEE Symposium on High-Performance Computer Architecture
Multiple Query Optimization by Cache-Aware Middleware Using Query Teamwork
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
QPipe: a simultaneously pipelined relational query engine
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Buffering accesses to memory-resident index structures
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Data morphing: an adaptive, cache-conscious storage technique
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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This paper proposes a complementary novel idea, called MiniTasking to further reduce the number of cache misses by improving the data temporal locality for multiple concurrent queries. Our idea is based on the observation that, in many workloads such as decision support systems (DSS), there is usually significant amount of data sharing among different concurrent queries. MiniTasking exploits such data sharing to improve data temporal locality by scheduling query execution at three levels: query level batching, operator level grouping and mini-task level scheduling. The experimental results with various types of concurrent TPC-H query workloads show that, with the traditional N-ary Storage Model (NSM) layout MiniTasking significantly reduces the L2 cache misses by up to 83%, and thereby achieves 24% reduction in execution time. With the Partition Attributes Across (PAX) layout, MiniTasking further reduces the cache misses by 65% and the execution time by 9%. For the TPC-H throughput test workload, MiniTasking improves the end performance up to 20%.