Views within the WebSphere Real Time perspective

Each view within the WebSphere® Real Time perspective presents data in specific sections of the display.

The controller window

The controller window provides the tools for you to select views of WebSphere Real Time data. There are two main tasks you can perform using the controller window.
Manage custom views
You can create a customized view, and add it to the list of available views. For more information about creating customized views, see Customizing the WebSphere Real Time perspective.
Select different views
You can select different views, using a combination box. The box is populated initially with predefined views. Customized views also appear in this box if a custom view definition file has been created and identified in the preferences.

All predefined views are identified by a System view: prefix. All customized views are identified by a Custom view: prefix.

The outlier plot window

This window displays event data as a simple plot graph. The X-axis of the graph shows the actual time when an event took place. The Y-axis shows the time taken for the event to occur. For convenience, the Y-axis values can be adjusted to display using a logarithmic scale.

When you hover over data in the plot window, a window opens providing details of the trace point associated with the event.

The histogram window

This window provides an alternative display of data. It shows a histogram representation of the data displayed in the outlier plot window. For example, in the predefined class loading view, the histogram representation shows how many class loading events took 0 - 1 ms to complete, how many events took 1 - 2 ms to complete, and so on.

The summary window

This window displays various statistics, calculated from the data presented in the plot window. The statistics include:
  • Total events processed.
  • Maximum time taken.
  • Minimum time taken.
  • Mean value for time taken.
  • Median value for time taken.
  • The standard deviation.

Recommendations and analysis window

This window displays the results of analyzing the collected data. The results are in the form of a determinism score. If the number of data samples is too low, the Health Center warns you that the determinism score might not be accurate. In particular, for Java™ method-based views, where the view descriptor might match multiple methods, a warning is displayed reporting that multiple methods have been matched.

The determinism score is calculated as follows:
  1. Select all the data points in the plot window.
  2. Calculate the median data point value - for example, the median time taken for a class loading event.
  3. Find how many events fall within the following ranges:
    • Median plus or minus 20% of the median value
    • Median plus or minus 40% of the median value
    • Median plus or minus 60% of the median value
    • Median plus or minus 80% of the median value
    • Median plus or minus 100% of the median value
  4. Calculate the average number of events for the ranges.
  5. The average number is the determinism score, expressed as a percentage.
The determinism score can be interpreted as shown in Table 1.
Table 1. Interpreting the meaning of a determinism score
Score Meaning
70 or less A very poor result. There is a wide distribution of results for the event, indicating uneven performance.
70 - 80 A poor result.
80 - 90 A good result.
90 or more A very good result. The results are distributed closely around the median value, indicating consistent performance.


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