Performance debugging for distributed systems of black boxes
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
An Execution Slice and Inter-Block Data Dependency-Based Approach for Fault Localization
APSEC '04 Proceedings of the 11th Asia-Pacific Software Engineering Conference
Web services navigator: visualizing the execution of web services
IBM Systems Journal
A time-and-value centric provenance model and architecture for medical event streams
Proceedings of the 1st ACM SIGMOBILE international workshop on Systems and networking support for healthcare and assisted living environments
SPC: a distributed, scalable platform for data mining
Proceedings of the 4th international workshop on Data mining standards, services and platforms
SPADE: the system s declarative stream processing engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Streamsight: a visualization tool for large-scale streaming applications
Proceedings of the 4th ACM symposium on Software visualization
Advances and Challenges for Scalable Provenance in Stream Processing Systems
Provenance and Annotation of Data and Processes
Scale-Up Strategies for Processing High-Rate Data Streams in System S
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Proceedings of the 2nd Workshop on High Performance Computational Finance
Tools and strategies for debugging distributed stream processing applications
Software—Practice & Experience
Visualizing large-scale streaming applications
Information Visualization
COLA: optimizing stream processing applications via graph partitioning
Middleware'09 Proceedings of the ACM/IFIP/USENIX 10th international conference on Middleware
Design principles for developing stream processing applications
Software—Practice & Experience - Focus on Selected PhD Literature Reviews in the Practical Aspects of Software Technology
A code generation approach for auto-vectorization in the SPADE compiler
LCPC'09 Proceedings of the 22nd international conference on Languages and Compilers for Parallel Computing
Towards low overhead provenance tracking in near real-time stream filtering
IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
Ariadne: managing fine-grained provenance on data streams
Proceedings of the 7th ACM international conference on Distributed event-based systems
IBM streams processing language: analyzing big data in motion
IBM Journal of Research and Development
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Stream processing is a new computing paradigm that enables continuous and fast analysis of massive volumes of streaming data. Debugging streaming applications is not trivial, since they are typically distributed across multiple nodes and handle large amounts of data. Traditional debugging techniques like breakpoints often rely on a stop-the-world approach, which may be useful for debugging single node applications, but insufficient for streaming applications. We propose a new visual and analytic environment to support debugging, performance analysis, and troubleshooting for stream processing applications. Our environment provides several visualization methods to study, characterize, and summarize the flow of tuples between stream processing operators. The user can interactively indicate points in the streaming application from where tuples will be traced and visualized as they flow through different operators, without stopping the application. To substantiate our discussion, we also discuss several of these features in the context of a financial engineering application.