LogLens: A real-time log analysis system
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 …
health and status of production applications. Logs report information, which is crucial to …
G-miner: an efficient task-oriented graph mining system
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 …
for graph mining are still lacking as existing studies focus on sequential algorithms. While …
Reachability and time-based path queries in temporal graphs
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 …
eg, A calls B at 11 am and talks for 7 minutes, which is modeled by an edge from A to B with …
Rheem: enabling cross-platform data processing: may the big data be with you!
D Agrawal, S Chawla, B Contreras-Rojas… - Proceedings of the …, 2018 - dl.acm.org
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 …
processing platform (platform for short), such as Hadoop or a DBMS. As a result …
Flexps: Flexible parallelism control in parameter server architecture
As a general abstraction for coordinating the distributed storage and access of model
parameters, the parameter server (PS) architecture enables distributed machine learning to …
parameters, the parameter server (PS) architecture enables distributed machine learning to …
An experimental comparison of partitioning strategies in distributed graph processing
S Verma - 2017 - ideals.illinois.edu
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 …
graph processing systems. To this end, we evaluate and characterize both the performance …
AdaptDB: adaptive partitioning for distributed joins
Y Lu - 2017 - dspace.mit.edu
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 …
processing is expensive in a distributed setting both because large amounts of data must be …
Type-safe dynamic placement with first-class placed values
G Zakhour, P Weisenburger… - Proceedings of the ACM on …, 2023 - dl.acm.org
Several distributed programming language solutions have been proposed to reason about
the placement of data, computations, and peers interaction. Such solutions include, among …
the placement of data, computations, and peers interaction. Such solutions include, among …
Improving resource utilization by timely fine-grained scheduling
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 …
I/O). While monotask was primarily introduced as a means to reason about job performance …
DRPS: efficient disk-resident parameter servers for distributed machine learning
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 …
machine learning tasks has been extensively studied. However, existing PS-based systems …