Explore the concept of sketching in big data through this 50-minute lecture by Jelani Nelson from Harvard University, part of the Simons Institute Open Lecture Series. Delve into the fundamentals of sketching, starting with a simple example and progressing to more complex applications like approximate counting and frequent items in streaming models. Learn about known algorithms, reductions, and proof techniques used in graph streaming problems. Discover how to handle data insertions and removals in streaming scenarios, and understand the challenges of querying in this context. Gain insights into the practical applications of sketching techniques in managing and analyzing large-scale data sets.
Overview
Syllabus
Intro
What is sketching
Simple sketching example
Approximate counting
Morriss idea
Frequent Items
turnstile streaming model
frequent heavyhitters
known algorithms
plan of attack
reduction
wishful thinking
proof lemma
graph streaming
inserting a strawberry
removing a peach
inserting and removing
query
remove
Strawberry
Coconut
Streaming Problem
Taught by
Simons Institute
