View indexing in relational databases
ACM Transactions on Database Systems (TODS)
NiagaraCQ: a scalable continuous query system for Internet databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
ACM SIGOPS Operating Systems Review
Fair Cache Sharing and Partitioning in a Chip Multiprocessor Architecture
Proceedings of the 13th International Conference on Parallel Architectures and Compilation Techniques
QPipe: a simultaneously pipelined relational query engine
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Integrating compression and execution in column-oriented database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Performance tradeoffs in read-optimized databases
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
How to wring a table dry: entropy compression of relations and querying of compressed relations
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Scheduling threads for constructive cache sharing on CMPs
Proceedings of the nineteenth annual ACM symposium on Parallel algorithms and architectures
Lottery scheduling: flexible proportional-share resource management
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
Cooperative cache partitioning for chip multiprocessors
Proceedings of the 21st annual international conference on Supercomputing
The case for precision sharing
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Adaptive aggregation on chip multiprocessors
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Cooperative scans: dynamic bandwidth sharing in a DBMS
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Constant-Time Query Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
The tight bound of first fit decreasing bin-packing algorithm is FFD(I) ≤ 11/9OPT(I) + 6/9
ESCAPE'07 Proceedings of the First international conference on Combinatorics, Algorithms, Probabilistic and Experimental Methodologies
A scalable, predictable join operator for highly concurrent data warehouses
Proceedings of the VLDB Endowment
MCC-DB: minimizing cache conflicts in multi-core processors for databases
Proceedings of the VLDB Endowment
SIMD-scan: ultra fast in-memory table scan using on-chip vector processing units
Proceedings of the VLDB Endowment
Mining tree-structured data on multicore systems
Proceedings of the VLDB Endowment
Predictable performance for unpredictable workloads
Proceedings of the VLDB Endowment
Automatic contention detection and amelioration for data-intensive operations
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Variance aware optimization of parameterized queries
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Optimizing read convoys in main-memory query processing
Proceedings of the Sixth International Workshop on Data Management on New Hardware
MOSS-DB: a hardware-aware OLAP database
WAIM'10 Proceedings of the 11th international conference on Web-age information management
MRShare: sharing across multiple queries in MapReduce
Proceedings of the VLDB Endowment
Proceedings of the sixth conference on Computer systems
Predictable performance and high query concurrency for data analytics
The VLDB Journal — The International Journal on Very Large Data Bases
SharedDB: killing one thousand queries with one stone
Proceedings of the VLDB Endowment
On the optimization of schedules for MapReduce workloads in the presence of shared scans
The VLDB Journal — The International Journal on Very Large Data Bases
Scaling up analytical queries with column-stores
Proceedings of the Sixth International Workshop on Testing Database Systems
Sharing data and work across concurrent analytical queries
Proceedings of the VLDB Endowment
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Computer architectures are increasingly based on multi-core CPUs and large memories. Memory bandwidth, which has riot kept pace with the increasing number of cores, has become the primary processing bottleneck, replacing disk I/O as the limiting factor. To address this challenge, we provide novel algorithms for increasing the throughput of Business Intelligence (BI) queries, as well as for ensuring fairness and avoiding starvation among a concurrent set of such queries. To maximize throughput, we propose a novel FullSharing scheme that allows all concurrent queries, when performing base-table I/O, to share the cache belonging to a given core. We then generalize this approach to a BatchSharing scheme that avoids thrashing on "agg-tables" ---hash tables that are used for aggregation processing---caused by execution of too many queries on a core. This scheme partitions queries into batches such that the working-set of agg-table entries for each batch can fit into a cache; an efficient sampling technique is used to estimate selectivities and working-set sizes for purposes of query partitioning. Finally, we use lottery-scheduling techniques to ensure fairness and impose a hard upper bound on staging time to avoid starvation. On our 8-core testbed, we were able to completely remove the memory I/O bottleneck, increasing throughput by a factor of 2 to 2.5, while also maintaining fairness and avoiding starvation.