Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Shivakumar Venkataraman"'
Autor:
Venkatesh Basker, Haifeng Jiang, Alexander Smolyanov, Divy Agrawal, Scott Holzer, Shan He, Monica Chawathe Lenart, Navin Reginald Melville, Vinny Ganeshan, Manpreet Singh, Manish Bhatia, Tianhao Qiu, Namit Sikka, Shivakumar Venkataraman, Yuri Vasilevski, Ashish Gupta
Publikováno v:
Real-Time Business Intelligence and Analytics ISBN: 9783030241230
BIRTE (Revised Selected Papers)
BIRTE (Revised Selected Papers)
Most of today’s Internet applications generate vast amounts of data (typically, in the form of event logs) that needs to be processed and analyzed for detailed reporting, enhancing user experience and increasing monetization. In this paper, we desc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6b9d22140bbd43c62d91271f8a0e887
https://doi.org/10.1007/978-3-030-24124-7_10
https://doi.org/10.1007/978-3-030-24124-7_10
Autor:
Jeff Shute, Fan Yang, Divyakant Agrawal, Andrey Gubarev, Sanjay Bhansali, Ankur Agiwal, Abhilash Rajesh Kumar, Shuo Wu, Kelvin K. W. Chan, Kevin Lai, Sandeep Govind Dhoot, Shivakumar Venkataraman, Adam Kirsch, Ashish Gupta, Mingsheng Hong, Masood Siddiqi, David Jones, Jason Govig, Jamie Cameron
Publikováno v:
Communications of the ACM. 59:117-125
Mesa is a highly scalable analytic data warehousing system that stores critical measurement data related to Google's Internet advertising business. Mesa is designed to satisfy a complex and challenging set of user and systems requirements, including
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a2ff63ba904fc5f5c393aed74111446
https://doi.org/10.1145/2936722
https://doi.org/10.1145/2936722
Autor:
Fan Yang, Andrey Gubarev, David Jones, Masood Siddiqi, Jamie Cameron, Sandeep Govind Dhoot, Ankur Agiwal, Abhilash Rajesh Kumar, Sanjay Bhansali, Jason Govig, Mingsheng Hong, Divyakant Agrawal, Kevin Lai, Kelvin K. W. Chan, Shivakumar Venkataraman, Jeff Shute, Shuo Wu, Adam Kirsch, Ashish Gupta
Publikováno v:
Proceedings of the VLDB Endowment. 7:1259-1270
Mesa is a highly scalable analytic data warehousing system that stores critical measurement data related to Google's Internet advertising business. Mesa is designed to satisfy a complex and challenging set of user and systems requirements, including
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a661d96117922783ad6b37a9ff06059
https://doi.org/10.14778/2732977.2732999
https://doi.org/10.14778/2732977.2732999
Autor:
Jeffrey D. Ullman, Jun Xu, Chad Whipkey, Nitin Gangahar, Stephan Ellner, Alejandro Estrella-Balderrama, Bart Samwel, Gokul Nath Babu Manoharan, Himani Apte, Karl Schnaitter, Stephan Gudmundson, Larysa Aharkava, Ben Handy, Divyakant Agrawal, Apurv Gupta, Sridatta Chegu, Shivakumar Venkataraman
Publikováno v:
SIGMOD Conference
We describe Shasta, a middleware system built at Google to support interactive reporting in complex user-facing applications related to Google's Internet advertising business. Shasta targets applications with challenging requirements: First, user que
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a54e1629efe6c7eb244bb85c51f74d5
https://doi.org/10.1145/2882903.2904444
https://doi.org/10.1145/2882903.2904444
Autor:
Sumit Das, Rajagopal Ananthanarayanan, Deomid Ryabkov, Ashish Gupta, Manpreet Singh, Tianhao Qiu, Haifeng Jiang, Venkatesh Basker, Shivakumar Venkataraman, Alexey Reznichenko
Publikováno v:
SIGMOD Conference
Web-based enterprises process events generated by millions of users interacting with their websites. Rich statistical data distilled from combining such interactions in near real-time generates enormous business value. In this paper, we describe the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a4f5f4e0f0967a5eaea6f8d00b22a7ab
https://doi.org/10.1145/2463676.2465272
https://doi.org/10.1145/2463676.2465272
Publikováno v:
The VLDB Journal The International Journal on Very Large Data Bases. 5:3-18
In this paper we describe the design and implementation of ParSets, a means of exploiting parallelism in the SHORE OODBMS. We used ParSets to parallelize the graph traversal portion of the OO7 OODBMS benchmark, and present speedup and scaleup results
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7d793f6f1fd91f98a5abf7af2844909
https://doi.org/10.1007/s007780050012
https://doi.org/10.1007/s007780050012
Publikováno v:
Proceedings of the VLDB Endowment. 7:1720-1721
In this collaborative keynote address, we will share Google's experience in building a scalable data infrastructure that leverages datacenters for managing Google's advertising data over the last decade. In order to support the massive online adverti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::067699a5b8bf9d3e986cd83fba841953
https://doi.org/10.14778/2733004.2733073
https://doi.org/10.14778/2733004.2733073
Publikováno v:
PDIS
Describes the design and implementation of ParSets, a means of exploiting parallelism in the SHORE persistent object store. We used ParSets to create and parallelize the graph traversals of the OO7 OODBMS benchmark, and present speedup and scaleup re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c85054ba7d858f2348b71f933e3ea09
https://doi.org/10.1109/pdis.1994.331725
https://doi.org/10.1109/pdis.1994.331725
Publikováno v:
SIGMOD Conference
Next generation decision support applications, besides being capable of processing huge amounts of data, require the ability to integrate and reason over data from multiple, heterogeneous data sources. Often, these data sources differ in a variety of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d32ab6b54d24a767015847adafea0d1
https://doi.org/10.1145/276304.276333
https://doi.org/10.1145/276304.276333