Tutorial Archives - Page 4 of 6 - ArangoDB

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Running ArangoDB on a Mac with Docker and Kitematic / Docker-Machine

00DocumentationTags:

When I work with ArangoDB on my Mac, I usually install ArangoDB via homebrew and do tests on the latest new developments based on the devel-branch, compiling ArangoDB right from source.

To test a feature in a special version I use docker images that need a virtual machine on MacOS. I struggled with Boot2Docker several times and recently tried Docker Machine – with the Web UI Kitematic – currently in beta. Read more

Foxx: Module resolution will change in 2.8

03Documentation, FoxxTags: , ,

The implementation of the JavaScript require function will be adjusted to improve compatibility with npm modules. The current implementation in 2.7 and earlier versions of ArangoDB strictly adheres to the CommonJS module standard, which deviates from the behaviour implemented in Node and browser bundlers.

Module paths will now be resolved in the following ways: Read more

Lockfree protection of data structures that are frequently read

04Architecture, SecurityTags:

Motivation

In multi-threaded applications running on multi-core systems, it occurs often that there are certain data structures, which are frequently read but relatively seldom changed. An example of this would be a database server that has a list of databases that changes rarely, but needs to be consulted for every single query hitting the database. In such situations one needs to guarantee fast read access as well as protection against inconsistencies, use after free and memory leaks.

Therefore we seek a lock-free protection mechanism that scales to lots of threads on modern machines and uses only C++11 standard library methods. The mechanism should be easy to use and easy to understand and prove correct. This article presents a solution to this, which is probably not new, but which we still did not find anywhere else.

The concrete challenge at hand

Assume a global data structure on the heap and a single atomic pointer P to it. If (fast) readers access this completely unprotected, then a (slow) writer can create a completely new data structure and then change the pointer to the new structure with an atomic operation. Since writing is not time critical, one can easily use a mutex to ensure that there is only a single writer at any given time. The only problem is to decide, when it is safe to destruct the old value, because the writer cannot easily know that no reader is still accessing the old values. The challenge is aggravated by the fact that without thread synchronization it is unclear, when a reader actually sees the new pointer value, in particular on a multi-core machine with a complex system of caches.

If you want to see our solution directly, scroll down to “Source code links“. We first present a classical good approach and then try to improve on it. More info

Dockerizing a Bloom-based Nonces Service in 10 Minutes

00Documentation, FoxxTags:

In this article I want to explain how to setup a nonce-microservice using docker.

Nonce are one-time tokens that are used to ensure that an action can only be taken once. In a project, we needed to ensure that a pay button is only pressed once. Note that nonces are not used to sign requests or identify a user. This is a separate mechanism.

ArangoDB contains a nonce implementation which is a variation of Bloom-filters. It allows to store nearly unlimited nonces within a limited amount of memory. Nonce are allowed to age, that is after an hour they might expire. If there is sufficient interest, I will explain the algorithm implemented in a separate blog post.

More info

Creating Multi-Game Highscore Lists

03API, Documentation, Query LanguageTags:

I just came across a question about how to create highscore lists or leaderboards in ArangoDB, and how they would work when compared to Redis sorted sets.

This blog post tries to give an answer on the topic and also detailed instructions and queries for setting up highscore lists with ArangoDB. The additional section “Extensions” explains slightly more advanced highscore list use cases like multi-game highscore lists, joining data and maintaining a “last updated” date.
More info

Create an ArangoDB cluster on Google Compute Engine with a single command

01DocumentationTags: ,

Last week we’ve released the first version of our new deployment tool for cloud computing platforms with Digital Ocean support. (Edit: now also available: Amazon Web Services) Today we show how to deploy an ArangoDB cluster on Google Compute Engine with a single command. :

Google Compute Engine

To easy-deploy an ArangoDB cluster on Google Compute Engine you just need to install the official gcloud tool, download a single bash script and watch the tool take care of the rest for you.

Google Compute Engine prerequisites

The script needs an available and configured Google Project.

ProjectID
  • Create a project (GCE Projects).
  • Remember your project-id, you’ll need that later for gcloud configuration.
  • Enable Google Compute Engine API More info

Be more lazy, use a custom .arangod.rc

00DocumentationTags:

How often did you typed

in the arangod console?

If you are familiar with the arangosh JavasScript shell than you probably use a custom .arangosh.rc startup script in your home-directory which defines your own extra variables and functions that you need often.

Now we’ve also added support for a file .arangod.rc that will be executed on server start. For example, you could put the following into the .arangod.rc file:

You’ll never have to go through the history again to add your favourite function again. (Available in devel-branch, coming to the next releases soon).