Graduate Courses

A short introduction and review of databases and database management systems, relational databases and SQL. Storage, insertion, deletion and search methods in databases, including sorted files, tables, indexes, hashing, trees, B-trees and B+ trees. Problems and trade-offs in large datasets during database creation, updating and searching; input/output models, memory hierarchy and the Disk Access Model, with examples. Disk sorting algorithms, merge sort, analysis, divide and conquer, DAM applications, cache-oblivious and cache-aware algorithms. Examples, models and analysis of insertion/search trade-offs and suitable data structures. Implementation issues and performance. Introduction and review of data mining and machine learning. Programming techniques for big data, MapReduce, Hadoop, physical organization and algorithms in the model. Representation and locality-sensitive hashing for texts, distance measures, sampling in data streams, data filtering, estimation, link analysis and association analysis.