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Exporting Data for Offline Processing in PHP: ArangoDB Guide
A few weeks ago I wrote about ArangoDB’s specialized export API.
The export API is useful when the goal is to extract all documents from a given collection and to process them outside of ArangoDB.
The export API can provide quick and memory-efficient snapshots of the data in the underlying collection, making it suitable for extract all documents of the collection. It will be able to provide data much faster than with an AQL query that will extract all documents.
In this post I’ll show how to use the export API to extract data and process it with PHP.
Please read the full blog post Exporting Data for Offline Processing.
AQL Functions Enhancements: Boosting ArangoDB Query Capabilities
Waiting for a git pull to complete over an 8 KiB/s internet connection is boring. So I thought I’d rather use the idle time and quickly write about some performance improvements for certain AQL functions that were recently completed and that will become available with ArangoDB 2.6.
The improvements affect the following AQL functions:
UNSET(): remove specified attributes from an object/documentKEEP(): keep only specified attributes of an object/documentMERGE(): merge the attributes of multiple objects/documents
This blog post shows a few example queries that will benefit from 50 to more than 60 % reductions in query execution times due to the changes done to these functions.
Efficient Data Collection with Hash Tables: ArangoDB Insights
ArangoDB 2.6 will feature an alternative hash implementation of the AQL COLLECT operation. The new implementation can speed up some AQL queries that can not exploit indexes on the COLLECT group criteria.
This blog post provides a preview of the feature and shows some nice performance improvements. It also explains the COLLECT-related optimizer parts and how the optimizer will decide whether to use the new or the traditional implementation.
Creating Multi-Game Highscore Lists: ArangoDB Techniques
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.
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Enhancements for Data Modification Queries: ArangoDB Updates
Data-modification queries were enhanced in ArangoDB 2.4 to be able to also return the inserted, update or removed documents. For example, the following statement inserted a few documents and also returned them with all their attributes:
FOR i IN 1..10
INSERT { value: i } IN test
LET inserted = NEW
RETURN inserted
The syntax for returning documents from data-modification queries only supported the exact above format. Using a LET clause was required, and the RETURN clause was limited to returning the variable introduced by the LET. These syntax restrictions have been lifted in the devel branch, which will become release 2.6 eventually.
The changes make returning values from data-modification statements easier and also more flexible.
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ArangoDB 2.5 Release: Enhanced Features & Performance
This version is deprecated. Download the new version of ArangoDB
We are proud to announce the latest release of ArangoDB, adding a bunch of new features and lot’s of improvements to existing ones. ArangoDB 2.5 is available for download now and could be installed from your favourite package manager.
See the previous blogposts on sparse indexes performance, ES6 features in ArangoDB, improved Foxx development process or API Key management to learn more about ArangoDB 2.5 and check the manual for a deeper dive into specific features.
The AWS image of ArangoDB 2.5 will be available shortly.
Please give ArangoDB 2.5 a try and provide us with your valuable feedback.
Git Commit Analysis with ArangoDB: Insightful Data Exploration
I often find myself searching for certain commits using git log and friends. While I really love the power and flexibility that come with the git and other Unix command-line tools, sometimes it can be more convenient to use a database to filter and aggregate commit data.
I gave it a quick try yesterday and imported the commit history of ArangoDB’s Git repository into ArangoDB and ran some queries on the data.
// retrieving number of commits per month / year
query = 'FOR commit IN commits
COLLECT year = DATE_YEAR(commit.date), month = DATE_MONTH(commit.date)
WITH COUNT INTO count
RETURN { month: CONCAT(year, "/", month), count: count }';
db._query(query).toArray();
While the query results for our repository may not be interesting for everyone, I think it is still worth sharing what I did. Even though I didn’t try it, I think the overall procedure is applicable with any other Git repository.
More queries and how to convert and import Git commits in ArangoDB: Read on in Jan’s Blog
Enhanced AQL in ArangoDB 2.5: Improved Query Capabilities
Contained in 2.5 are some small but useful AQL language improvements plus several AQL optimizer improvements.
We are working on further AQL improvements for 2.5, but work is still ongoing. This post summarizes the improvements that are already completed and will be shipped with the initial ArangoDB 2.5 release.
Exploring More ES6 Features: ArangoDB Insights
ArangoDB 2.5 comes with an upgraded version of V8, Google’s open source JavaScript engine.
The built-in version of V8 has been upgraded from 3.29.54 to 3.31.74.1.
In addition to several already usable ES6 features (detailed in this blog, the following ES6 features are activated in ArangoDB 2.5 by default:
- iterators and generators
- template strings
- enhanced object literals
- enhanced numeric literals
- block scoping with
letandconstantvariables using const - additional String methods (such as
startsWith,repeatetc.)
The above features are available in ArangoDB 2.5, and can now be used for scripting purposes in the ArangoShell and in server-side Foxx actions inside the database.
This blog post briefly explains the features provides some quick examples for using them.
When and how to use sparse indexes in ArangoDB 2.5
This version is deprecated. Download the new version of ArangoDB
In ArangoDB 2.5, hash and skiplist indexes can optionally be made sparse.
Such sparse indexes will exclude documents in which at least one of the index attributes is either not set or has a value of null. Declaring an index as sparse can provide great savings in memory and index creation CPU time for some cases.
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