Geo Index Implementation

This section will cover the MMFiles based geo-index. The algorithm is optimized for in-memory accesses and optimal CPU cache utilization. The main goal for our geo queries is to reject as many distant possible result points as fast as possible.

The ArangoDB Fulltext index allows you to search for text in arbitrary strings. It is a great way to implement things like autocompletion, product searches or many other use-cases which need some form of fulltext search.The Fulltext Index is suitable for you if your use-case can be broken down to:

• Full matches of words
• Prefix matches of words
• You do not need a “ranking” of the matching documents

Starting with the mass-market availability of smartphones and continuing with IoT devices, self-driving cars ever more data is generated with geo information attached to it. Analyzing this data in real-time requires the use of clever indexing data-structures. Geo data in ArangoDB consists of 2 or more dimensions representing (x, y) coordinates on the earth surface. Searching on a single number is essentially a solved problem, but effectively searching on multi-dimensional data can be more difficult as standard indexing techniques cannot be used.There exist a variety of indexing techniques. In..

In this post, we will introduce you to our new ArangoDB C++ diver fuerte. fuerte allows you to communicate via HTTP and VST with ArangoDB instances. You will learn how to create collections, insert documents, retrieve documents, write AQL Queries and how to use the asynchronous API of the driver.

Requirements (Running the sample)

Please download and inspect the sample described in this post. The sample consists of a C++ – Example Source Code – File and a CMakeLists.txt. You need to install the fuerte diver, which can be found on github, into your system before compiling the sample. Please..

We’re pleased to announce the availability of the Milestone 2 of ArangoDB 3.3. There are a number of improvements, please consult the changelog for a complete overview of changes.

This milestone release contains our new and improved data replication engine. The replication engine is at the core of every distributed ArangoDB setup: whether it is a typical master/slave setup between multiple single servers or a full-fledged cluster. During the last month we:

• redesigned the replication protocol to be more reliable
• refactored and modernized the internal infrastructure to better support..

The next alpha release of the upcoming ArangoDB 3.2 is available for testing. You can download and install alpha3 here.

Moving forward

As ArangoDB 3.2 will include several new features and improvements, we realized that the release model that we currently follow has room for improvement. Going forward we will introduce milestone releases with ArangoDB 3.3. For this major release you will see a bit more alphas. You can read detailed info about the new structure model here.

Pregel computing model

In this alpha we introduce support for incremental graph processing algorithms in a single mode..

Suppose there is an AQL query that’s executing in the server for a long time already and you want to get rid of it. What can be done to abort that query?

If a connection to the server can still be established, the easiest is to use the ArangoShell to fetch the list of currently executing AQL queries and send a kill command to the server for the correct query.

To start, we can fetch the list of all running queries and print their ids, query strings and runtimes. This is only inspection and does not abort any query:

var queries = require("org/arangodb/aql/queries"); queries.current();

Here’s..

With the 2.8 beta phase coming to an end it’s time to shed some light on the improvements in the 2.8 AQL optimizer. This blog post summarizes a few of them, focusing on the query optimizer. There’ll be a follow-up post that will explain dedicated new AQL features soon.

Array indexes

2.8 allows creating hash and skiplist indexes on attributes which are arrays. Creating such index works similar to creating a non-array index, with the exception that the name of the array attribute needs to be followed by a [*] in the index fields definition:

db._create("posts"); db.posts.ensureIndex({ type:..

There are a few API changes coming in the next 2.8 release. Please have a look if you contribute to a language driver or client-side query builder for ArangoDB.

AQL keywords added

The following AQL keywords were added in ArangoDB 2.8:

While working on the upcoming ArangoDB 2.8, we have reimplemented some AQL functions in C++ for improved performance. AQL queries using these functions may benefit from using the new implementation of the function.

The following list shows the AQL functions for which a C++ implementation has been added in 2.8. The other C++-based AQL function implementations added since ArangoDB 2.5 are also still available. Here’s the list of functions added in 2.8:

• document-related functions: DOCUMENT, EDGES, PARSE_IDENTIFIER
• numerical functions: ABS, FLOOR, RAND, ROUND, SQRT
• statistical functions:..