I’m pleased to have recently had my first article published on the Oracle Technology Network (OTN). You can read it in its full splendour and glory(!) over there, but I thought I’d give a bit of background to it and the tools demonstrated within.
OBIEE Performance Analytics Dashboards
One of the things that we frequently help our clients with is reviewing and optimising the performance of their OBIEE systems. As part of this we’ve built up a wealth of experience in the kind of suboptimal design patterns that can cause performance issues, as well as how to go about identifying them empirically. Getting a full stack view on OBIEE performance behaviour is key to demonstrating where an issue lies, prior to being able to resolve it and proving it fixed, and for this we use the Rittman Mead OBIEE Performance Analytics Dashboards.A common performance issue that we see is analyses and/or RPDs built in such a way that the BI Server inadvertently returns many gigabytes of data from the database and in doing so often has to dump out to disk whilst processing it. This can create large NQS_tmp files, impacting the disk space available (sometimes critically), and the disk I/O subsystem. This is the basis of the OTN article that I wrote, and you can read the full article on OTN to find out more about how this can be a problem and how to go about resolving it.
OBIEE implementations that cause heavy use of temporary files on disk by the BI Server can result in performance problems. Until recently in OBIEE, it was really difficult to track because of the transitory nature of the files. By the time the problem had been observed (for example, disk full messages), the query responsible had moved on and so the temporary files deleted. At Rittman Mead we have developed lightweight diagnostic tools that collect, amongst other things, the amount of temporary disk space used by each of the OBIEE components.This can then be displayed as part of our Performance Analytics Dashboards, and analysed alongside other performance data on the system such as which queries were running, disk I/O rates, and more: Because the Performance Analytics Dashboards are built in a modular fashion, it is easy to customise them to suit specific analysis requirements. In this next example you can see performance data from Oracle being analysed by OBIEE dashboard page in order to identify the cause of poorly-performing reports: We’ve put online a set of videos here demonstrating the Performance Analytics Dashboards, and explaining in each case how they can help you quickly and accurately diagnose OBIEE performance problems.