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6 - Visualization and debugging

from Part II - Application development

Published online by Cambridge University Press:  05 March 2014

Henrique C. M. Andrade
Affiliation:
J. P. Morgan
Buğra Gedik
Affiliation:
Bilkent University, Ankara
Deepak S. Turaga
Affiliation:
IBM Thomas J. Watson Research Center, New York
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Summary

Overview

In this chapter, we examine visualization and debugging as well as the relationship of these services and the infrastructure provided by a SPS. Visualization and debugging tools help developers and analysts to inspect and to understand the current state of an application and the data flow between its components, thus mitigating the cognitive and software engineering challenges associated with developing, optimizing, deploying, and managing SPAs, particularly the large-scale distributed ones.

On the one hand, visualization techniques are important at development time, where the ability to picture the application layout and its live data flows can aid in refining its design.

On the other hand, debugging techniques and tools, which are sometimes integrated with visualization tools, are important because the continuous and critical nature of some SPAs requires the ability to effectively diagnose and address problems before and after they reach a production stage, where disruptions can have serious consequences.

This chapter starts with a discussion of software visualization techniques for SPAs (Section 6.2), including the mechanisms to produce effective visual representations of an application's data flow graph topology, its performance metrics, and its live status.

Debugging is intimately related to visualization. Hence, the second half of this chapter focuses on the different types of debugging tasks used in stream processing (Section 6.3).

Visualization

Comprehensive visualization infrastructure is a fundamental tool to support the development, understanding, debugging, and optimization of SPAs.

Type
Chapter
Information
Fundamentals of Stream Processing
Application Design, Systems, and Analytics
, pp. 178 - 200
Publisher: Cambridge University Press
Print publication year: 2014

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References

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