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This page contains information about improving the performance of FishEye repository scans.
When you add a repository, FishEye needs to perform a once-off scan through the repository to build up its initial index and cache. This scan can take some time. Until this scan is complete, you may find that some data is not displayed. As a guide, FishEye should be able to process about 100KB-200KB per second on an averaged-size PC. If FishEye is accessing the repository over the network (e.g. over a NFS mount), then you should expect the initial scan to take longer.
You can increase the speed of your scans using the following options:
One option is break large repositories into multiple smaller repositories. While this technique will not improve the overall initial scan time, it allows for all fully scanned repositories to be updated while the initial scan is still being performed on those remaining.
In FishEye 1.3.4 and later, the initial and incremental scans happen in separate, single threads. So, splitting the repositories will allow incremental scans to run concurrently alongside the initial scans. You may also wish to split projects into separate repositories, since permissions in FishEye are applied on a per-repository basis.
The http/s protocol has the slowest performance during the initial scan. The svn protocol (svn://) is faster and the file protocol (file:///) is the fastest.
Therefore if you find your initial scan takes an extended amount of time (more than a day or two), you should consider switching over from the http/s protocol to the svn or file protocol to define the location of your SVN repository. (Use svnsync to mirror the repository onto the fisheye server, so that you can access it with the file protocol.)
E.g. Switch from https://example.com/svn/project/ to svn://example.com/svn/project/ or file:///home/user/some/location/svn/project
In order for SVN protocol to work you need to have set up an svnserve based server.
More information on how to troubleshoot SVN indexing related issues can be found here.
If you have implemented at least one of the suggestions above but are still experiencing slow performance, ask us for help: