PPT-Succinct: Enabling Queries on Compressed Data

Shreya Current Query Methods Data Scans Loads file into memory and scans Column oriented stores Low memory high latency Index based scan the file is preprocessed and stored in memory with indices. joint work with Dan . Suciu. (University of Washington). Alexandra Meliou. Hypothetical (What-if. ). Queries. Brokerage company. DB. Key Performance Indicators (KPI). Example from [. Balmin. et al. VLDB’00]:. through . Path Decompositions . Roberto . Grossi. Giuseppe . Ottaviano*. Università. di Pisa. * Part of the work done while at Microsoft Research Cambridge. t. three. trial. triangle. trie. triple. A Main Memory Compression Framework with . Low Complexity and Low Latency . Gennady Pekhimenko. , . Vivek. . Seshadri. . , . Yoongu. Kim, . Hongyi. . Xin. , . Onur. . Mutlu. , . Todd C. . Mowry. Exploiting . Spatial Locality . for Energy-Optimized . Compressed Caching. Somayeh. . Sardashti. and . David . A. . Wood. University . of Wisconsin-Madison. 1. 2. 3. Where does energy go?. Communication vs. Computation. Johannes . Gehrke. Department . of Computer Science, Cornell University . With . Gabriel Bender, Nitin Gupta, Lucja Kot, Sudip Roy (. Cornell) and . Milos Nikolic, Christoph Koch (EPFL) . Introduction to Entangled Queries . Robert Nishihara. Data store tradeoffs. Queries on values are tricky. Low latency, high throughput. Build an index. Memory efficiency. Just store data in memory. Succinct. Achieves low latency and memory efficiency. Action Queries. CS1100. 1. Advanced Queries. Action Queries. So far we have used queries to extract and view data. But can also be . used to create tables, perform data entry, modify records, etc. .. Compressed Sensing. Mobashir. . Mohammad. Aditya Kulkarni. Tobias Bertelsen. Malay Singh. Hirak. . Sarkar. Nirandika. . Wanigasekara. Yamilet Serrano . Llerena. Parvathy. . Sudhir. Introduction. Mobashir. Exploiting . Spatial Locality . for Energy-Optimized . Compressed Caching. Somayeh. . Sardashti. and . David . A. . Wood. University . of Wisconsin-Madison. 1. 2. 3. Where does energy go?. Communication vs. Computation. Robert Nishihara. Data store tradeoffs. Queries on values are tricky. Low latency, high throughput. Build an index. Memory efficiency. Just store data in memory. Succinct. Achieves low latency and memory efficiency. Barzan. . Mozafari. (presented by Ivo D. Dinov). University of Michigan, Ann Arbor. Research Goals. Using statistics to build better data-intensive systems. Faster. How to query petabytes of data in seconds?. Slobodan Vucetic * Vladimir Coric Zhuang Wang Department of Computer and Information Sciences Temple University Philadelphia, PA 19122, USA * t , y t ), t = 1…T}, where x t -dimensional inp Feng Zhang †⋄, . Jidong. . Zhai. ⋄, . Xipeng. Shen #, . Onur. . Mutlu. ⋆, . Wenguang. Chen ⋄. †Renmin University of China. ⋄Tsinghua University. #North Carolina State University. agenda, . and round of introduction of the participants. . 2. Round of introduction and expectations from the participants. GIS . ???. Name, position, location. Your experience with maps, GIS, . GPS.