samdoran

Aerohive

Initial setup

1. Reset to factory defaults

    reset config bootstrap
    reset config
   

   The username is admin and the password is aerohive or Aerohive1.

Chaser324

Whether you're trying to give back to the open source community or collaborating on your own projects, knowing how to properly fork and generate pull requests is essential. Unfortunately, it's quite easy to make mistakes or not know what you should do when you're initially learning the process. I know that I certainly had considerable initial trouble with it, and I found a lot of the information on GitHub and around the internet to be rather piecemeal and incomplete - part of the process described here, another there, common hangups in a different place, and so on.

In an attempt to coallate this information for myself and others, this short tutorial is what I've found to be fairly standard procedure for creating a fork, doing your work, issuing a pull request, and merging that pull request back into the original project.

Creating a Fork

Just head over to the GitHub page and click the "Fork" button. It's just that simple. Once you've done that, you can use your favorite git client to clone your repo or j

sirf

evdev:name:Kingsis Peripherals Evoluent VerticalMouse*
 KEYBOARD_KEY_90004=reserved

gbehrmann

First a little background info. The Berkeley DB Java Edition library used by the pools (if so configured) uses a log structured file format. What this means is that the files of the database (called log segments) are only ever appended to. Once they reach a certain size (10 MB by default), a new log segment is created and the previous log segments are never modified. If existing data is modified or deleted, this leaves unused fragments in these these database files. Once the utilization (amount of data still in use) falls under a certain level, remaining data is copied to the end of the last segment and the original segment is deleted (this is all text book log structured database).

Berkeley DB uses a btree structure, i.e. it is structured as a tree, with the actual data at the leafs and the internal nodes allowing fast search of the data.

Berkeley DB internally maintains a cache of the files. The default in dCache is to use 20% of the maximum heap size as a cache for Berkeley DB. It is a recommendation fr