Optimize Analysis Workspace performance
Various factors influence the performance of a project within Analysis Workspace. To understand these factors, help you to plan and build projects in the most optimal way.
To gain insight into the performance of Analysis Workspace:
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Select Help > Performance.
You can see a modal dialog that displays factors that impact your project’s performance, including network, browser, and project factors. For the most accurate results, allow the project to load before you- The Current Project column displays the results for your current project and user environment.
- The Guideline column displays Adobe’s recommended threshold for each factor.
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Select Download as CSV to download the performance report, so you can share the report within your internal organization or with Adobe support.
Network factors
Network factors include:
Browser factors
Browser factors include:
If those actions do not help, discuss hardware details with your IT team.
If those actions do not help, discuss hardware details with your IT team.
Project factors
Project factors include:
Additionally, minimize the number of year-over-year comparisons used in the project. When a year-over-year comparison is calculated, the calculations look across the full 13 months of data between the months of interest. This comparison has the same impact as changing the panel date range to last 13 months.
Request factors
Request factors
Use the following diagram and terms to learn how requests are processed and the various factors that influence processing times:
Request processing diagram
Request processing terms
The time required from when the request is initiated to when it is complete. The guideline is 15 seconds.
In the Request processing diagram above, the request time represents the full process, from Analysis Workspace request initiated to Analysis Workspace request complete.
The time required from when the request is initiated to when it is complete.
In the Request processing diagram above, the request time represents the full process, from Analysis Workspace request initiated to Analysis Workspace request complete.
Because Analysis Workspace stores only the hash for any strings that are used in any segments, each time you process a project, Lookups are performed to match the hashes with the appropriate values. The guideline is under 2 seconds.
These lookups can be a resource-intensive process, depending on the number of values that could potentially match the hash.
In the Request processing diagram above, the lookup time is represented in the Lookups phase (at the time of Request Engine processing phase).
The total time waiting in the queue before requests are processed. The guideline is 5 seconds.
In the Request processing diagram above, the queue time is represented in the Request Engine queue phase and Server queue phase.
The average amount of time it takes to process the request.
In the Request processing diagram above, the average server processing time is represented in the Server queue phase and Server processing phase. The guideline is 10 seconds
Not all requests require the same amount of time to process. Request complexity can help provide a general idea about the time required to process the request. The guideline is Medium or lower.
Possible values include:
- Low
- Medium
- High
This value is influenced by the values in the following columns:
- Month boundaries
- Columns
- Segments
Additional factors
Additional factors that are not included in Help > Performance include:
Factors that add complexity to a segment (in descending order of impact) include:
- Operators of contains, contains any of, matches, starts with, or ends with/
- Sequential segmentation, especially when dimension restrictions (Within/After) are used
- The number of unique dimension items within dimensions used in the segment (for example, Page = ‘A’ when Page has 10 unique items are faster than Page = ‘A’ when Page has 100000 unique items).
- The number of different dimensions used (for example, Page = ‘Home’ and Page = ‘Search results’ are faster than eVar 1 = ‘red’ and eVar 2 = ‘blue’)
- Many OR operators (instead of AND)
- Nested containers that vary in scope (for example, Hit inside of Visit inside of Visitor)
While some of the complexity factors cannot be prevented, look for opportunities to reduce the complexity of your segments. In general, the more specific you can be with your segment criteria, the better. For example:
- With containers, using a single container at the top of the segment are faster than a series of nested containers.
- With operators, equals are faster than contains, and equals any of are faster than contains any of.
- With many criteria, AND operators are faster than a series of OR operators.
Look for opportunities to reduce many OR statements into a single equals any of statement.
Classifications can also help to consolidate many values into concise groups from which you can then create segments. Segmentation on classification groups provides performance benefits over segments that contain many OR statements or contains criteria.
Factors that add complexity to a visualization include:
- Range of data requested
- Number of segments applied; for instance, segments used as rows of a freeform table
- Use of complex segments
- Static item rows or columns in freeform tables
- Filters applied to rows in freeform tables
- Number of metrics included, especially calculated metrics that use segments
If you find yourself continually using segments and calculated metrics for data points that are important to your business, consider improving your implementation to capture these data points more directly. The use of a tags in Adobe Experience Platform and Adobe’s processing rules can make implementation changes quick and easy to implement.
Tips to increase productivity in Analysis Workspace
See