PhD Candidate. Supervised by Nick Koudas. I now work at Facebook. Previously:   M.Sc in CS from University of Toronto. 2006.   B.Tech in CSE from IIT Kanpur. 2004. 5160 Bahen Centre for Information Technology 40 St.George Street Toronto, Ontario M5S 2E4 cmishra@cs.toronto.edu

Research

I conduct research on database systems. In particular, on database monitoring, adaptivity and testing.

Click here for a chronological list of publications.

And here's my thesis: Queries, Data, and Statistics: Pick Two. [PDF].

	ConEx The goal of the ConEx project is to design a general framework for monitoring and estimating query progress in a database system. Such a utility provides informative feedback to database users and administrators, and additionally serves as a building block for incorporating autonomic features in a database system. ConEx consists of a suite of online statistical estimation techniques, implemented inside the query processor of the Postgresql engine. The Design of a Query Monitoring System. Chaitanya Mishra, Nick Koudas. In ACM Transactions on Database Systems, TODS 2009. [PDF]. ConEx: A System for Monitoring Queries. Chaitanya Mishra, Maksims Volkovs. In ACM SIGMOD International Conference on Management of Data, SIGMOD 2007. [PDF]. System Demonstration. A Lightweight Online Framework for Query Progress Indicators. Chaitanya Mishra, Nick Koudas. In IEEE International Conference on Data Engineering, ICDE 2007. [PDF]. Short Paper.
	XS The XS (Execution Simulation) framework extends the monitoring techniques of ConEx to the problem of adaptively reordering join pipelines inside a database engine. XS performs lightweight reoptimizations of join pipelines with probabilistic guarantees on its estimates. Our prototype implementation of XS inside the Postgresql engine has been measured to improve query execution times by upto a factor of 8. Join Reordering by Join Simulation. Chaitanya Mishra, Nick Koudas. In IEEE International Conference on Data Engineering, ICDE 2009. [PDF].
	Stretch 'n' Shrink The Stretch 'n' Shrink (SnS) system attempts to provide database users a measure of control over the answer size of their queries. SnS enables interactive refinement of SQL queries that return too many or too few tuples through the operations of stretching (relaxing) or shrinking (contracting) query predicates. Interactive Query Refinement. Chaitanya Mishra, Nick Koudas. In International Conference on Extending Database Technology, EDBT 2009. [PDF] Stretch 'n' Shrink: Resizing Queries to User Preferences. Chaitanya Mishra, Nick Koudas. In ACM SIGMOD International Conference on Management of Data, SIGMOD 2008. [PDF]. System Demonstration.
	TQGen TQGen is a tool for generating targeted test queries that satisfy cardinality constraints on intermediate subexpressions for the purposes of testing the performance of different components of database engines. TQGen is a "data-aware" query generation framework, enabling it to generate test queries satisfying runtime properties. Generating Targeted Queries for Database Testing. Chaitanya Mishra, Nick Koudas, Calisto Zuzarte. In ACM SIGMOD International Conference on Management of Data, SIGMOD 2008. [PDF]. Slides: [PDF].

University of Toronto