Zobrazeno 1 - 10
of 159
pro vyhledávání: '"Vijayshankar Raman"'
Autor:
Xi Mao, Haoyan Geng, S R Rajesh, Hakan Hacıgümüş, Ming Dai, Tianhang Sun, Ye (Justin) Tang, Hao Zhang, Zongchang (Jim) Chen, Kevin Lai, Sujata Kosalge, Vijayshankar Raman, Jay Patel, Yanlai Huang, Zeleng Zhuang, Sagar Trehan, Sourashis Roy, Prashant Mishra, Zhi (Adam) Li, Indrajit Roy, Yupu Zhang, Junichi Tatemura, Li Liu, Mayank Singh Shishodia, Bo Huang, Raman Grover, Jagan Sankaranarayanan, Jianyi Liang, Yao Liu, Min Chen, Prasanna Venkatasubramanian, Divyakant Agrawal, Thanh Do, Yalan (Maya) Meng, Haoyu Gao, Tao Lin, Gensheng Zhang, Gokul Nath Babu Manoharan, Ramkumar Vadali, Kefei Zhang, Ankur Agiwal, Goetz Graefe, Jeffrey F. Naughton, Tao Zou
Publikováno v:
Proceedings of the VLDB Endowment. 14:2986-2997
Google services continuously generate vast amounts of application data. This data provides valuable insights to business users. We need to store and serve these planet-scale data sets under the extremely demanding requirements of scalability, sub-sec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50da8371c8da8aa8a5fa1eef549a5d96
https://doi.org/10.14778/3476311.3476377
https://doi.org/10.14778/3476311.3476377
Autor:
Adam J. Storm, Ronald J. Barber, Yuanyuan Tian, Yingjun Wu, Pinar Tözün, Hamid Pirahesh, Ronen Grosman, Christian Garcia-Arellano, René Müller, Vijayshankar Raman, Guy M. Lohman, Richard S. Sidle, Chandrasekaran Mohan
Publikováno v:
Barber, R, Garcia-Arellano, C, Grosman, R, Lohman, G, Mohan, C, Mueller, R, Pirahesh, H, Raman, V, Sidle, R, Storm, A, Tian, Y, Tözün, P & Wu, Y 2019, WiSer: A Highly Available HTAP DBMS for IoT Applications . in IEEE International Conference on Big Data . IEEE, pp. 268-277 . https://doi.org/10.1109/BigData47090.2019.9006519
IEEE BigData
IEEE BigData
In a classic transactional distributed database management system (DBMS), write transactions invariably synchronize with a coordinator before final commitment. While enforcing serializability, this model has long been criticized for not satisfying th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c0260b86a1f489ac1f0278c46c2e3b4
Publikováno v:
Encyclopedia of Big Data Technologies ISBN: 9783319639628
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0d757bed1d35cffb7e1d891f747d0e7
https://doi.org/10.1007/978-3-319-63962-8_257-1
https://doi.org/10.1007/978-3-319-63962-8_257-1
Autor:
Gopi K. Attaluri, Naresh K. Chainani, Vijayshankar Raman, Guy M. Lohman, Ippokratis Pandis, Richard S. Sidle, Ronald J. Barber, Sam Lightstone, David C. Sharpe
Publikováno v:
Proceedings of the VLDB Endowment. 8:353-364
We present new hash tables for joins, and a hash join based on them, that consumes far less memory and is usually faster than recently published in-memory joins. Our hash join is not restricted to outer tables that fit wholly in memory. Key to this h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ccd7eb1a0e08bba1dc040dbe630cc77a
https://doi.org/10.14778/2735496.2735499
https://doi.org/10.14778/2735496.2735499
Autor:
Vincent Kulandai Samy, Oliver Draese, Lin Qiao, Sam Lightstone, Knut Stolze, Naresh K. Chainani, Jae-Gil Lee, Min-Soo Kim, Gopi K. Attaluri, Ippokratis Pandis, Konstantinos Morfonios, Frederick Ho, Guy M. Lohman, Vijayshankar Raman, Stratos Idreos, Keshava Murthy, Richard S. Sidle, Ronald J. Barber, Liping Zhang
Publikováno v:
Proceedings of the VLDB Endowment. 7:1355-1366
Compression has historically been used to reduce the cost of storage, I/Os from that storage, and buffer pool utilization, at the expense of the CPU required to decompress data every time it is queried. However, significant additional CPU efficiencie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::743855c3bfbf892d5c5cce0c6752ecd7
https://doi.org/10.14778/2733004.2733008
https://doi.org/10.14778/2733004.2733008
Autor:
Vijayshankar Raman, Shaorong Liu, Ronald J. Barber, Liping Zhang, Adam J. Storm, Jens Leenstra, David Kalmuk, Rene Mueller, Berni Schiefer, Tim Malkemus, Sam Lightstone, Ippokratis Pandis, David C. Sharpe, Vincent Kulandaisamy, Richard S. Sidle, Gopi K. Attaluri, Guy M. Lohman, Naresh K. Chainani
Publikováno v:
Proceedings of the VLDB Endowment. 6:1080-1091
DB2 with BLU Acceleration deeply integrates innovative new techniques for defining and processing column-organized tables that speed read-mostly Business Intelligence queries by 10 to 50 times and improve compression by 3 to 10 times, compared to tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec9b013b482b8a89cd9553d4900582e8
https://doi.org/10.14778/2536222.2536233
https://doi.org/10.14778/2536222.2536233
Autor:
Oleg Sidorkin, Guy M. Lohman, Yuanyuan Tian, Fatma Ozcan, Richard S. Sidle, Vijayshankar Raman, Chandrasekaran Mohan, Adam J. Storm, Rene Mueller, Pinar Tözün, Matt Huras, Hamid Pirahesh, Ronald J. Barber
Publikováno v:
SIGMOD Conference
We demonstrate Hybrid Transactional and Analytics Processing (HTAP) on the Spark platform by the Wildfire prototype, which can ingest up to ~6 million inserts per second per node and simultaneously perform complex SQL analytics queries. Here, a simpl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d95197154b1b8fc53918984080d3870a
https://doi.org/10.1145/2882903.2899406
https://doi.org/10.1145/2882903.2899406
Publikováno v:
Proceedings of the VLDB Endowment. 1:622-634
Table scans have become more interesting recently due to greater use of ad-hoc queries and greater availability of multi-core, vector-enabled hardware. Table scan performance is limited by value representation, table layout, and processing techniques
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::266bcc0170707c4024189205c808b195
https://doi.org/10.14778/1453856.1453925
https://doi.org/10.14778/1453856.1453925
Publikováno v:
Proceedings of the VLDB Endowment. 1:610-621
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 fact
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e869e73bf8b615844b738a13a3e87038
https://doi.org/10.14778/1453856.1453924
https://doi.org/10.14778/1453856.1453924
Autor:
Daniel M. Yellin, Inderpal S. Narang, Jorge Buenabad-Chávez, Garret Swart, Alvaro A. A. Fernandes, Mengsong Chen, Norman W. Paton, Vijayshankar Raman
Publikováno v:
The VLDB Journal. 18:119-140
Writing parallel programs that can take advantage of non-dedicated processors is much more difficult than writing such programs for networks of dedicated processors. In a non-dedicated environment such programs must use autonomic techniques to respon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9cbb1895e4aba60416c3bba68c1e156
https://doi.org/10.1007/s00778-007-0090-x
https://doi.org/10.1007/s00778-007-0090-x