Administrators of most user-facing systems depend on periodic log data to get an idea of the
health and status of production applications. Logs report information, which is crucial to …

Graph mining is one of the most important areas in data mining. However, scalable solutions
for graph mining are still lacking as existing studies focus on sequential algorithms. While …

A temporal graph is a graph in which vertices communicate with each other at specific time,
eg, A calls B at 11 am and talks for 7 minutes, which is modeled by an edge from A to B with …

Solving business problems increasingly requires going beyond the limits of a single data
processing platform (platform for short), such as Hadoop or a DBMS. As a result …

As a general abstraction for coordinating the distributed storage and access of model
parameters, the parameter server (PS) architecture enables distributed machine learning to …

In this thesis, we study the problem of choosing among partitioning strategies in distributed
graph processing systems. To this end, we evaluate and characterize both the performance …

Big data analytics often involves complex join queries over two or more tables. Such join
processing is expensive in a distributed setting both because large amounts of data must be …

Several distributed programming language solutions have been proposed to reason about
the placement of data, computations, and peers interaction. Such solutions include, among …

Monotask is a unit of work that uses only a single type of resource (eg, CPU, network, disk
I/O). While monotask was primarily introduced as a means to reason about job performance …

Parameter server (PS) as the state-of-the-art distributed framework for large-scale iterative
machine learning tasks has been extensively studied. However, existing PS-based systems …