This section describes how to use the performance data that you collect to identify ways to improve the performance of Tableau Server. Because no two server environments are identical, we can't provide hard and fast rules for tuning server performance. However, you can draw conclusions about performance from patterns in the data that you collected.
For example, are there recurring spikes? Do any of the patterns that you notice in the administrative views correspond to similar patterns in a monitoring tool ? Observing patterns like this can guide you in testing and incremental tuning.
Most performance tuning for Tableau Server boils down to these general approaches:
Optimize for User Traffic: This tunes the server to respond to user requests and to display views quickly.
Optimize for Extracts: This tunes the server to refresh extracts for published data sources. You might want to optimize for extract refreshes if your organization has a lot of data and the data needs to be as up to date as possible.
Optimize for Extract Query-Heavy Environments: This is a specialized server configuration to optimize for query performance of workbooks that use extracts as their data source.
Rendering views and refreshing extracts generate the most load on the server, so you should optimize for the task that your organization is most interested in.
As a best practice, optimize your workbooks for performance. For more information and resources on how to optimize your workbooks, see Optimize Workbook Performance.
Other articles in this sectionRetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4