Abstract
In this paper, we survey the use of advanced hardware features for optimizing main-memory database systems in the context of our HyPer project. We exploit the virtual memory management for snapshotting the transactional data in order to separate OLAP queries from parallel OLTP transactions. The access behavior of database objects from simultaneous OLTP transactions is monitored using the virtual memory management component in order to compact the database into hot and cold partitions. Utilizing many-core NUMA-organized database servers is facilitated by the morsel-driven adaptive parallelization and partitioning that guarantees data locality w.r.t. the processing core. The most recent Hardware Transactional Memory support of, e.g., Intel’s Haswell processor, can be used as the basis for a lock-free concurrency control scheme for OLTP transactions. Finally, we show how heterogeneous processors of “wimpy” devices such as tablets can be utilized for high-performance and energy-efficient query processing.
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Notes
Low Level Virtual Machine (LLVM, llvm.org) is an open-source compiler infrastructure project that provides a machine-independent assembly language.
References
Albutiu MC, Kemper A, Neumann T (2012) AQ2Massively parallel sort-merge joins in main memory multi-core database systems. Proceedings VDLB Endowment 5(10):1064–1075
Alonso G (2013) AQ3Hardware killed the software star. In: ICDE, Brisbane, Queensland, 8–12 April 2013
Alonso G, Kossmann D, Roscoe T (2011) AQ4SWissBox: an architecture for data processing appliances. In: CIDR 2011, Asilomar, CA, USA, January 9–12, 2011
Apple. AQ5Data Management in iOS. https://developer.apple.com/technologies/ios/data-management.html, accessed 1 Sep 2014
Balakrishnan S, Rajwar R, Upton M, Lai K (2005) The impact of performance asymmetry in emerging multicore architectures. ACM SIGARCH Comp Archit News 33(2):506–517
Balkesen C, Alonso G, Teubner J, Özsu MT (2013) Multi-core, main-memory joins: sort vs. hash revisited. Proceedings VDLB Endowment 7(1):85–96
Bernstein PA, Hadzilacos V, Goodman N (1987) AQ6Concurrency control and recovery in database systems. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA
Carey MJ (1983) Modeling and evaluation of database concurrency control algorithms. PhD thesis . EECS Department, University of California, Berkeley, CA, USA
Diaconu C, Freedman C, Ismert E, Larson P-Å, Mittal P, Stonecipher R, Verma N, Zwilling M (2013) Hekaton: SQL server’s memory-optimized OLTP engine. In: SIGMOD 2013, New York, NY, USA, June 22–27, 2013
Esmaeilzadeh H, Blem E, St. Amant R, Sankaralingam K, Burger D (2011) Dark silicon and the end of multicore scaling. In: ISCA 2011, June 4–8, 2011, San Jose, CA, USA
Färber F, Cha SK, Primsch J, Bornhövd C, Sigg S, Lehner W (2011) SAP HANA database: data management for modern business applications. SIGMOD Rec 40(4):45–51
Funke F, Kemper A, Neumann T (2012) Compacting transactional data in hybrid OLTP&OLAP databases. Proceedings VDLB Endowment 5(11):1424–1435
Google. Storage options. http://developer.android.com/guide/topics/data/data-storage.html#db, accessed 1 Sep 2014
Gorman M (2004) Understanding the Linux virtual memory manager. Prentice Hall , Upper Saddle River, New Jersey, USA
Greenhalgh P (2011) big. LITTLE processing with ARM Cortex-A15 & Cortex-A7. Whitepaper by ARM, URL: http://www.arm.com/files/download/big_LITTLE_Final_Final.pdf, September 2011, accessed 1 Sep 2014
Hardavellas N, Ferdman M, Falsafi B, Ailamaki A (2011) Toward dark silicon in servers. IEEE Micro 31(4):6–15
Harizopoulos S, Abadi DJ, Madden S, Stonebraker M (2008) OLTP through the looking glass, and what we found there. In: SIGMOD 2008, Vancouver, BC, Canada, June 10–12, 2008
Herlihy M, Moss JEB (1993) Transactional memory: architectural support for lock-free data structures. In: ISCA May 1993, San Diego, CA, USA
IHS. Processor market set for strong growth in 2013, Courtesy of smartphones and tablets. http://press.ihs.com/printpdf/18632, accessed 1 Sep 2014
Kemper A, Neumann T (2011) HyPer: a hybrid OLTP&OLAP main memory database system based on virtual memory snapshots. In: ICDE, Hannover, 11–16 April 2011
Leis V, Kemper A, Neumann T (2013) The adaptive radix tree: ARTful indexing for main-memory databases. In: ICDE, Brisbane, Queensland, 8–12 April 2013
Leis V, Kemper A, Neumann T (2014) Exploiting hardware transactional memory in main-memory databases. In: ICDE, Chicago, IL, 31 March to 4 April 2014
Leis V, Boncz P, Kemper A, Neumann T (2014) Morsel-driven parallelism: a NUMA-aware query evaluation framework for the many-core age. In: Proceedings of the 2014 ACM SIGMOD international conference on management of data, Snowbird, UT, 22–27 June 2014
Li Y, Pandis I, Müller R, Raman V, Lohman GM (2013) NUMA-aware algorithms: the case of data shuffling. In: CIDR 2013, Asilomar, CA, USA, January 6–9, 2013
Mühlbauer T, Rödiger W, Seilbeck R, Kemper A, Neumann T (2014) Heterogeneity-conscious parallel query execution: getting a better mileage while driving faster! In: DaMoN 2014, Snowbird, Utah, USA, June 23, 2014
Mühlbauer T, Rödiger W, Seilbeck R, Reiser A, Kemper A, Neumann T (2014) One DBMS for all: the brawny few and the wimpy crowd. In: SIGMOD 2014, Snowbird, UT, USA, June 22–27, 2014
Neumann T (2011) Efficiently compiling efficient query plans for modern hardware. Proceedings VLDB Endowment 4(9):539–550
Schall D, Härder T (2013) Energy-proportional query execution using a cluster of wimpy nodes. In: DaMoN 2013, New York, NY, USA, June 24, 2013
IBM solidDB (2012) http://www.ibm.com/software/data/soliddb/, accessed 1 Sep 2014
Tsirogiannis D, Harizopoulos S, Shah MA (2010) Analyzing the energy efficiency of a database server. In: SIGMOD 2010, Indianapolis, Indiana, USA, June 6–10, 2010
Van Craeynest K, Eeckhout L (2013) Understanding fundamental design choices in single-ISA heterogeneous multicore architectures. ACM Trans Archit Code Optim 9(4):Art. 32
VoltDB (2010) Technical overview.http://voltdb.com/downloads/datasheets_collateral/technical_overview.pdf, accessed 1 Sep 2014
Acknowledgement
This work has been supported by the German Research Foundation DFG and various collaborations and donations by industry partners (Google, IBM, Oracle, SAP).
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Funke, F., Kemper, A., Mühlbauer, T. et al. HyPer Beyond Software: Exploiting Modern Hardware for Main-Memory Database Systems. Datenbank Spektrum 14, 173–181 (2014). https://doi.org/10.1007/s13222-014-0165-y
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DOI: https://doi.org/10.1007/s13222-014-0165-y