Academic
Publications
Increasing Buffer-Locality for Multiple Relational Table Scans through Grouping and Throttling

Increasing Buffer-Locality for Multiple Relational Table Scans through Grouping and Throttling,10.1109/ICDE.2007.368972,Christian A. Lang,Bishwaranjan

Increasing Buffer-Locality for Multiple Relational Table Scans through Grouping and Throttling   (Citations: 9)
BibTex | RIS | RefWorks Download
Decision support (DSS) workloads generally contain multiple large concurrent scan operations. These are often executed as relational table scans which can take up a lot of I/O bandwidth. This is especially true for ad-hoc queries where the workload is not known in advance. Common database management systems have only limited ability to reuse memory buffer content across multiple running queries due to their treatment of queries in isolation. Previous attempts to coordinate scans for better buffer reuse were less than satisfactory due to drifting between scans and the required radical DBMS architecture changes. In this paper, we describe a new mechanism to keep similar table scans closer together during scanning. This is achieved via dynamic grouping and regrouping of scans based on their runtime behavior and via adaptive throttling of scan speeds based on scan group characteristics. The required memory footprint is very small and the effort required to extend existing database management systems is minimal, as shown in our DB2 UDB prototype. Our experiments show significant gains in end-to-end response times as well as average response times for TPC-H workloads.
Conference: International Conference on Data Engineering - ICDE , pp. 1136-1145, 2007
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
    • ...In the literature, a few methods [1] [2] [4] [6] [7] have been proposed to address the above problem on HDDs...
    • ...To relieve the performance loss of the fast scans, DB2 [6] [7] proposes an improved “group shared” scheme in which the scans with similar speeds are grouped together and sharing happens within each group...

    Chang Xuet al. Towards Efficient Concurrent Scans on Flash Disks

    • ...Cooperative scans originate in the data-warehousing domain and have been implemented for disk-based database systems such as DB2 UDB [14] and MonetDB/X100 [25], with the goal of sharing disk bandwidth and maximizing buer-pool utilization across queries...

    Philipp Unterbrunneret al. Predictable Performance for Unpredictable Workloads

    • ...Some of the techniques used include compressing the data [3], scan sharing of the data access [4], various caching techniques [5], data clustering mechanisms [6] etc...
    • ...Index Compression and compression in general are examples of the latter and mechanisms like Scan Sharing [4], Data Caching [5], and Data Clustering [6] etc are examples of the former...
    • ...Scan Sharing [4] is a mechanism to achieve IO reduction on retrieval...

    Bishwaranjan Bhattacharjeeet al. Efficient Index Compression in DB2 LUW

    • ...Shared scans have been used in the past to overcome disk I/O bottlenecks [16, 21], but bringing this technique to main-memory DBMS’s poses significant challenges...
    • ...Many recent systems explicitly synchronize concurrent queries to improve the amount of I/O that can be shared at the buffer pool, by grouping together queries that run at similar speeds [16, 21]...

    Lin Qiaoet al. Main-memory scan sharing for multi-core CPUs

    • ...In [1, 6, 10, 11, 12, 19], scans are coordinated for better buffer reuse (increasing buffer locality)...
    • ...Recently, a modified circular scan has been proposed in IBM DB2 system [11, 12] by adding explicit group control and allowing throttling of faster scans...

    Yu Caoet al. Optimizing complex queries with multiple relation instances

Sort by: