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Impala: A Modern, Open-Source SQL Engine for Hadoop
- Marcel Kornacker, Alexander Behm, Michael Yoder
- Computer ScienceConference on Innovative Data Systems Research
- 2015
This paper presents Impala from a user’s perspective, gives an overview of its architecture and main components and briefly demonstrates its superior performance compared against other popular SQL-on-Hadoop systems.
DB2 with BLU Acceleration: So Much More than Just a Column Store
- Vijayshankar Raman, Gopi K. Attaluri, Liping Zhang
- Computer ScienceProceedings of the VLDB Endowment
- 27 August 2013
Full integration with DB2 ensures that DB2 with BLU Acceleration benefits from the full functionality and robust utilities of a mature product, while still enjoying order-of-magnitude performance gains from revolutionary technology without even having to change the SQL.
Aether: A Scalable Approach to Logging
- Ryan Johnson, I. Pandis, R. Stoica, Manos Athanassoulis, A. Ailamaki
- Computer ScienceProceedings of the VLDB Endowment
- 1 September 2010
This paper identifies four logging-related impediments to database system scalability and addresses them with techniques that, when combined, comprise a holistic, scalable approach to logging.
Shore-MT: a scalable storage manager for the multicore era
- Ryan Johnson, I. Pandis, N. Hardavellas, A. Ailamaki, B. Falsafi
- Computer Science, BusinessInternational Conference on Extending Database…
- 24 March 2009
Shore-MT is presented, a multithreaded and highly scalable version of Shore which was developed by identifying and successively removing internal bottlenecks, and exhibits superior scalability and 2--4 times higher absolute throughput than its peers.
Data-oriented transaction execution
- I. Pandis, Ryan Johnson, N. Hardavellas, A. Ailamaki
- Computer ScienceProceedings of the VLDB Endowment
- 1 September 2010
DORA is designed, a system that decomposes each transaction to smaller actions and assigns actions to threads based on which data each action is about to access, and attains up to 4.8x higher throughput than a state-of-the-art storage engine when running a variety of synthetic and real-world OLTP workloads.
Queuing Systems
- M. Vassilakopoulos, T. Tzouramanis, M. Patiño-Martínez
- Computer ScienceEncyclopedia of Database Systems
- 14 November 2018
ERMIA: Fast Memory-Optimized Database System for Heterogeneous Workloads
- Kangnyeon Kim, Tianzheng Wang, Ryan Johnson, I. Pandis
- Computer ScienceSIGMOD Conference
- 26 June 2016
This paper presents ERMIA, a memory-optimized database system built from scratch to cater the need of handling heterogeneous workloads that include read-mostly transactions that adopts snapshot isolation concurrency control to coordinate heterogeneous transactions and provides serializability when desired.
TPC-E vs. TPC-C: characterizing the new TPC-E benchmark via an I/O comparison study
- Shimin Chen, A. Ailamaki, R. Stoica
- Computer ScienceSGMD
- 8 February 2011
This paper compares T PC-E with the familiar TPCC benchmark in order to understand the behavior of the new TPC-E benchmark, and finds that Tpc-E is more read intensive with a 9.7:1 I/O read to write ratio, while TPC -C sees a 1.9:1 read-to-write ratio.
Improving OLTP Scalability using Speculative Lock Inheritance
- Ryan Johnson, I. Pandis, A. Ailamaki
- Computer ScienceProceedings of the VLDB Endowment
- 1 August 2009
Speculative Lock Inheritance is proposed and evaluated, a technique where hot database locks pass directly from transaction to transaction, bypassing the lock manager bottleneck, and it is shown that lock inheritance fundamentally improves scalability by decoupling the number of simultaneous requests for popular locks from thenumber of threads in the system.
Database Servers on Chip Multiprocessors: Limitations and Opportunities
- N. Hardavellas, I. Pandis, Ryan Johnson, Naju Mancheril, A. Ailamaki, B. Falsafi
- Computer ScienceConference on Innovative Data Systems Research
- 5 January 2007
This paper characterize the performance of a commercial database server running on emerging chip multiprocessor technologies and finds that the major bottleneck of current software is data cache stalls, with L2 hit stalls rising from oblivion to become the dominant execution time component in some cases.
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