Parallel database systems: the future of high performance database systems
Communications of the ACM
Multi-table joins through bitmapped join indices
ACM SIGMOD Record
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Data warehousing and OLAP for decision support
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A performance evaluation of cluster architectures
SIGMETRICS '97 Proceedings of the 1997 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Materialized views and data warehouses
ACM SIGMOD Record
Caching multidimensional queries using chunks
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Bitmap index design and evaluation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Implications of certain assumptions in database performance evauation
ACM Transactions on Database Systems (TODS)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Parallel Star Join + DataIndexes: Efficient Query Processing in Data Warehouses and OLAP
IEEE Transactions on Knowledge and Data Engineering
Hash-Based Join Algorithms for Multiprocessor Computers
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
The Universal B-Tree for Multidimensional Indexing: general Concepts
WWCA '97 Proceedings of the International Conference on Worldwide Computing and Its Applications
Improving OLAP Performance by Multidimensional Hierarchical Clustering
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Multi-dimensional clustering: a new data layout scheme in DB2
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Processing star queries on hierarchically-clustered fact tables
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Efficient query processing for multi-dimensionally clustered tables in DB2
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Ad hoc star join query processing in cluster architectures
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
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Data warehouse workloads are crucial for the support of on-line analytical processing (OLAP). The strategy to cope with OLAP queries on such huge amounts of data calls for the use of large parallel computers. The trend today is to use cluster architectures that show a reasonable balance between cost and performance. In such cases, it is necessary to tune the applications in order to minimize the amount of I/O and communication, such that the global execution time is reduced as much as possible. In this paper, we model and analyze the most up-to-date strategies for ad hoc star join query processing in a cluster of computers. We show that, for ad hoc query processing and assuming a limited amount of resources available, these strategies still have room for improvement both in terms of I/O and inter-node data traffic communication. Our analysis concludes with the proposal of a hybrid solution that improves these two aspects compared to the previous techniques, and shows near optimal results in a broad spectrum of cases.