PPT-New Algorithms for Heavy Hitters in Data Streams

Author : yoshiko-marsland | Published Date : 2017-05-02

David Woodruff IBM Almaden J oint works with Arnab Bhattacharyya Vladimir Braverman Stephen R Chestnut Palash Dey Nikita Ivkin Jelani Nelson and Zhengyu

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New Algorithms for Heavy Hitters in Data Streams: Transcript

David Woodruff IBM Almaden J oint works with Arnab Bhattacharyya Vladimir Braverman Stephen R Chestnut Palash Dey Nikita Ivkin Jelani Nelson and Zhengyu Wang Streaming Model. Yehuda. . Afek. Anat. . Bremler. -Barr. . Shir. Landau . Feibish. This work is part of the . Kabarnit. –Cyber Consortium (2012-2014) under Magnet program, funded by the chief scientist in the Israeli ministry of Industry, Trade and Labor. . Vladimir . Braverman. . (JHU). Stephen R. . Chestnut . (ETH). Nikita . Ivkin. . (JHU). David P. . Woodruff . (IBM). Streaming Model. Stream of elements a. 1. , …, a. m. . in . [n] = {1, …, n. David Woodruff . IBM . Almaden. Based on works with Vladimir . Braverman. , Stephen R. Chestnut Nikita . Ivkin. , Jelani Nelson, and . Zhengyu. Wang. Streaming Model. Stream of elements a. 1. , …, a. Omid Alipourfard. , Masoud Moshref, Minlan Yu. {. alipourf. , . moshrefj. , . minlanyu. }@. usc.edu. Software Switches are Popular. Data centers. : . “Use the cloud to manage the cloud”. Load balancer and Firewall on VMs. COMP3211 . Advanced Databases. Dr. Nicholas Gibbins – . nmg@ecs.soton.ac.uk. 2014-2015. From Databases to Data Streams. 2. Traditional DBMS makes several assumptions:. persistent data storage. relatively static records. Vibhaalakshmi Sivaraman. Srinivas Narayana, Ori . RottenSTREICH. , MUTHU . MuthuKRSISHNAN. , JENNIFER REXFORD. 1. Heavy Hitter Flows. Flows above a certain threshold of total packets. “Top-. k. ” flows by size. David Woodruff . IBM . Almaden. Based on works with Vladimir . Braverman. , Stephen R. Chestnut Nikita . Ivkin. , Jelani Nelson, and . Zhengyu. Wang. Streaming Model. Stream of elements a. 1. , …, a. David Woodruff . IBM . Almaden. J. oint works with Arnab Bhattacharyya, Vladimir . Braverman. , Stephen R. Chestnut, . Palash. . Dey. Nikita . Ivkin. , Jelani Nelson, and . Zhengyu. Wang. Streaming Model. Grigory. . Yaroslavtsev. http://grigory.us. Lecture . 3. : Streaming. Slides at . http://grigory.us/big-data-class.html. Count-Min Sketch. https. ://sites.google.com/site/countminsketch/. Stream: . elements from universe . David Woodruff . IBM . Almaden. J. oint works with Arnab Bhattacharyya, Vladimir . Braverman. , Stephen R. Chestnut, . Palash. . Dey. Nikita . Ivkin. , Jelani Nelson, and . Zhengyu. Wang. Streaming Model. David Woodruff . IBM . Almaden. Based on works with Vladimir . Braverman. , Stephen R. Chestnut Nikita . Ivkin. , Jelani Nelson, and . Zhengyu. Wang. Streaming Model. Stream of elements a. 1. , …, a. Vibhaalakshmi Sivaraman. Srinivas Narayana, Ori . RottenSTREICH. , MUTHU . MuthuKRSISHNAN. , JENNIFER REXFORD. 1. Heavy Hitter Flows. Flows above a certain threshold of total packets. “Top-. k. ” flows by size. Stream Estimation 1: Count-Min Sketch Contd.. Input data element enter one after another (i.e., in a stream ). Cannot store the entire stream accessibly How do you make critical calculations about the stream using a limited amount of memory? Why Social Graphs Are Different. Communities. Finding Triangles. Jeffrey D. Ullman. Stanford University/. Infolab. Social Graphs. Graphs can be either directed or undirected.. Example. : The Facebook “friends” graph (undirected)..

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