PPT-Practical Perfect Hashing for very large Key-Value Databases

Amjad Daoud PhD httpiswsaacmorgmphf Practical Perfect Hashing for very large KeyValue Databases Abstract This presentation describes a practical algorithm for perfect hashing that is suitable for very large KV key value. Allows us to do some computations in database and extract reduced data for further manipulation Relational Databases brPage 2br What do statisticians need to know about databases Understand the relevance of databases Have familiarity with the basic 1 Overview Hashing is a great practical tool with an interesting and su btle theory too In addition to its use as a dictionary data structure hashing also comes up in many di 64256erent areas including cryptography and complexity theory In this lectu The analysis uses only very basic and intuitively understandable concepts of probability theory and is meant to be accessible even for undergraduates taking their 64257rst algorithms course 1 Introduction dictionary is a data structure for storing a Up to this point the greatest drawback of cuckoo hashing appears to be that there is a polynomially small but practically signicant probability that a failure occurs during the insertion of an item requiring an expensive rehashing of all items in th COL 106. Shweta Agrawal, . Amit. Kumar. Slide Courtesy : Linda Shapiro, . Uwash. Douglas W. Harder, . UWaterloo. 12/26/03. Hashing - Lecture 10. 2. The Need for Speed. Data structures we have looked at so far. Yunchao. Gong. UNC Chapel Hill. yunchao@cs.unc.edu. The problem. Large scale image search:. We have a candidate image. Want to search a . large database . to find similar images. Search the . internet. Approximate Near Neighbors. Ilya Razenshteyn (CSAIL MIT). Alexandr. . Andoni. (Simons Institute). Approximate Near Neighbors (ANN). Dataset:. . n. points in . d. dimensions. Query:. a point within . of . Modern Cryptography. Josh Benaloh. Brian . LaMacchia. Winter 2011. January 6, 2011. Practical Aspects of Modern Cryptography. Cryptography is .... Protecting Privacy of Data. Authentication of Identities. PAST PERFECT TENSE. Police Dog Catches Burglars. (from the newspaper). T. hree burglars were arrested yesterday. They were waiting in a bus shelter. . five miles from the scene of their crime. They . Plan. I spent the last decade advising on numerous cases where hash tables/functions were used. A few observations on . What data structures I’ve seen implemented and where. What do developers think, were they need help. Consider a set of data with N data items stored in some data structure. We must be able to insert, delete & search for items. What are possible ways to do this? What is the complexity of each structure & method ?. In static hashing, function . h. maps search-key values to a fixed set of . B. . buckets, that contain a number of (K,V) entries.. . . Problem: d. atabases . grow . (or shrink) . with time. . If initial number of buckets is too small, and file grows, performance will degrade due to too much overflows.. Naifan Zhuang, Jun Ye, Kien A. Hua. Department of Computer Science. University of Central Florida. ICPR 2016. Presented by Naifan Zhuang. Motivation and Background. According to a report from Cisco, by 2019:. What is a hashing function?. Fingerprint for a given piece of data. Typically generated by a mathematical algorithm. Produces a fixed length string as its . output. Hashes are sometimes . called a . checksum or message digests.