activity
20122023
most citedAutomatically Leveraging MapReduce Frameworks for Data-Intensive Applications

35 citations · 174 across the 25 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

cs.DB2018★ 5 cited

Improving High Contention OLTP Performance via Transaction Scheduling

Guna Prasaad, Alvin Cheung, Dan Suciu

Research in transaction processing has made significant progress in improving the performance of multi-core in-memory transactional systems. However, the focus has mainly been on l…

cs.CL2018

Mapping Language to Code in Programmatic Context

Srinivasan Iyer, Ioannis Konstas, Alvin Cheung +1

Source code is rarely written in isolation. It depends significantly on the programmatic context, such as the class that the code would reside in. To study this phenomenon, we intr…

cs.DB2018★ 10 cited

Cuttlefish: A Lightweight Primitive for Adaptive Query Processing

Tomer Kaftan, Magdalena Balazinska, Alvin Cheung +1

Modern data processing applications execute increasingly sophisticated analysis that requires operations beyond traditional relational algebra. As a result, operators in query plan…

cs.DB2018★ 5 cited

Axiomatic Foundations and Algorithms for Deciding Semantic Equivalences of SQL Queries

Shumo Chu, Brendan Murphy, Jared Roesch +2

Deciding the equivalence of SQL queries is a fundamental problem in data management. As prior work has mainly focused on studying the theoretical limitations of the problem, very f…

cs.DB2018★ 35 cited

Automatically Leveraging MapReduce Frameworks for Data-Intensive Applications

Maaz Bin Safeer Ahmad, Alvin Cheung

MapReduce is a popular programming paradigm for developing large-scale, data-intensive computation. Many frameworks that implement this paradigm have recently been developed. To le…