Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ashvin Agrawal"'
Publikováno v:
SIGMOD Conference
Bing's monetization pipeline is one of the largest and most critical streaming workloads deployed in Microsoft's internal data lake. The pipeline runs 24/7 at a scale of 3500 YARN containers and is required to meet a Service Level Objective (SLO) of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae0c2b58ff5df670abe23820d417dce9
https://doi.org/10.1145/3318464.3386142
https://doi.org/10.1145/3318464.3386142
Autor:
Mohammad Hossein Namaki, Ashvin Agrawal, Fotis Psallidas, Yinghui Wu, Yiwen Zhu, Avrilia Floratou, Subru Krishnan, Markus Weimer
Publikováno v:
KDD
There has recently been a lot of ongoing research in the areas of fairness, bias and explainability of machine learning (ML) models due to the self-evident or regulatory requirements of various ML applications. We make the following observation: All
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9901fbe44b27ede6f099bde24480458
Autor:
Avrilia Floratou, Ashvin Agrawal
Publikováno v:
Proceedings of the VLDB Endowment. 11:2050-2053
In a world where organizations are being inundated with data from various sources, analyzing data and gaining actionable insights in real-time has become a key service differentiator. Over the last few years, several stream processing frameworks have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24e23e4de228dfc146d074c220a2b542
https://doi.org/10.14778/3229863.3236257
https://doi.org/10.14778/3229863.3236257
Publikováno v:
Proceedings of the VLDB Endowment. 10:1825-1836
In recent years, there has been an explosion of large-scale real-time analytics needs and a plethora of streaming systems have been developed to support such applications. These systems are able to continue stream processing even when faced with hard
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da61d87f6429c719dd4de24345089dd8
https://doi.org/10.14778/3137765.3137786
https://doi.org/10.14778/3137765.3137786
Autor:
Avrilia Floratou, Ishai Menache, Ashvin Agrawal, Chris Douglas, Srikanth Kandula, Joseph (Seffi) Naor, Virajith Jalaparti, Sriram Rao, Mainak Ghosh
Publikováno v:
SoCC
We consider a common setting where storage is disaggregated from the compute in data-parallel systems. Colocating caching tiers with the compute machines can reduce load on the interconnect but doing so leads to new resource management challenges. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::807b2624083eddb89fa1b1cd64e9e452
https://doi.org/10.1145/3267809.3267827
https://doi.org/10.1145/3267809.3267827
Autor:
Avrilia Floratou, Ashvin Agrawal
Publikováno v:
BIRTE
In recent years, stream processing systems have been deployed in almost every organization due to the explosion of large-scale analytics applications. Our discussions with users of these systems within Microsoft and Twitter have revealed that a major
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc073dca179a0acca5858e62611fe70b
https://doi.org/10.1145/3129292.3129295
https://doi.org/10.1145/3129292.3129295
Autor:
Neng Lu, Maosong Fu, Mark Li, Ashvin Agrawal, Bill Graham, Cong Wang, Avrilia Floratou, Sriram Rao, Andrew Jorgensen, Karthik Ramasamy
Publikováno v:
ICDE
Twitter's data centers process billions of events per day the instant the data is generated. To achieve real-time performance, Twitter has developed Heron, a streaming engine that provides unparalleled performance at large scale. Heron has been recen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70b6fe0cbfc4be26419f13f16d6e3230
https://doi.org/10.1109/icde.2017.161
https://doi.org/10.1109/icde.2017.161