On June 1-2, over 2,000 developers, sysadmins, and DBAs will converge in New York City for MongoDB World, our annual user conference. It’s your chance to to get inspired, share ideas and get the latest insights on using MongoDB.
If you’re active on social media, you may have a chance to win a free conference pass. Simply share your enthusiasm for MongoDB World on Twitter during the month of March.
How to Enter
- Follow @mongodb or @mongodbinc on Twitter
- Tell us why you’re excited about MongoDB World by tweeting with a mention of @mongodb or @mongodbinc and make sure to use the #MongoDBWorld hashtag. Get creative! Start conversations, use humor, share photos, tell us what speakers you look forward to hearing from.
Click to tweet: I can't wait for #MongoDBWorld w/ @MongoDB because...
## Prizes 1st Prize: Ticket to MongoDB World 2015 2nd Prize: Fully loaded MongoDB World swag pack 3rd Prize: MongoDB T-shirt
How Winners Will Be Selected
MongoDB will pick the winning applicant by April 3rd, and will notify the winner via twitter direct message. The winners will be chosen based on a combination of most widely shared content and creativity used to experience their excitement about MongoDB World.
Call for Feedback: The New PHP and HHVM Drivers
In the beginning Kristina created the MongoDB PHP driver. Now the PECL mongo extension was new and untested, write operations tended to be fire-and-forget, and Boolean parameters made more sense than $options arrays. And Kristina said, "Let there be MongoCollection," and there was basic functionality. Since the PHP driver first appeared on the scene, MongoDB has gone through many changes. Replica sets and sharding arrived early on, but things like the aggregation framework and command cursors were little more than a twinkle in Eliot's eye at the time. The early drivers were designed with many assumptions in mind: write operations and commands were very different; the largest replica set would have no more than a dozen nodes; cursors were only returned by basic queries. In 2015, we know that these assumptions no longer hold true. Beyond MongoDB's features, our ecosystem has also changed. When the PHP driver, a C extension, was first implemented, there wasn't yet a C driver that we could utilize. Therefore, the 1.x PHP driver contains its own BSON and connection management C libraries. HHVM , an alternative PHP runtime with its own C++ extension API, also did not exist years ago, nor was PHP 7.0 on the horizon. Lastly, methods of packaging and distributing libraries have changed. Composer has superseded PEAR as the de facto standard for PHP libaries and support for extensions (currently handled by PECL) is forthcoming. During the spring of 2014, we worked with a team of students from Facebook's Open Academy program to prototype an HHVM driver modeled after the 1.x API. The purpose of that project was twofold: research HHVM's extension API and determine the feasibility of building a driver atop libmongoc (our then new C driver) and libbson . Although the final result was not feature complete, the project was a valuable learning experience. The C driver proved quite up to the task, and HNI, which allows an HHVM extension to be written with a combination of PHP and C++, highlighted critical areas of the driver for which we'd want to use C. This all leads up to the question of how best to support PHP 5.x, HHVM, and PHP 7.0 with our next-generation driver. Maintaining three disparate, monolithic extensions is not sustainable. We also cannot eschew the extension layer for a pure PHP library, like mongofill , without sacrificing performance. Thankfully, we can compromise! Here is a look at the architecture for our next-generation PHP driver: At the top of this stack sits a pure PHP library, which we will distribute as a Composer package. This library will provide an API similar to what users have come to expect from the 1.x driver (e.g. CRUD methods, database and collection objects, command helpers) and we expect it to be a common dependency for most applications built with MongoDB. This library will also implement common specifications , in the interest of improving API consistency across all of the drivers maintained by MongoDB (and hopefully some community drivers, too). Sitting below that library we have the lower level drivers (one per platform). These extensions will effectively form the glue between PHP and HHVM and our system libraries (libmongoc and libbson). These extensions will expose an identical public API for the most essential and performance-sensitive functionality: Connection management BSON encoding and decoding Object document serialization (to support ODM libraries) Executing commands and write operations Handling queries and cursors By decoupling the driver internals and a high-level API into extensions and PHP libraries, respectively, we hope to reduce our maintainence burden and allow for faster iteration on new features. As a welcome side effect, this also makes it easier for anyone to contribute to the driver. Additionally, an identical public API for these extensions will make it that much easier to port an application across PHP runtimes, whether the application uses the low-level driver directly or a higher-level PHP library. GridFS is a great example of why we chose this direction. Although we implemented GridFS in C for our 1.x driver, it is actually quite a high-level specification. Its API is just an abstraction for accessing two collections: files (i.e. metadata) and chunks (i.e. blocks of data). Likewise, all of the syntactic sugar found in the 1.x driver, such as processing uploaded files or exposing GridFS files as PHP streams, can be implemented in pure PHP. Provided we have performant methods for reading from and writing to GridFS' collections – and thanks to our low level extensions, we will – shifting this API to PHP is win-win. Earlier I mentioned that we expect the PHP library to be a common dependency for most applications, but not all. Some users may prefer to stick to the no-frills API offered by the extensions, or create their own high-level abstraction (akin to Doctrine MongoDB for the 1.x driver), and that's great! Hannes has talked about creating a PHP library geared for MongoDB administration, which provides an API for various user management and ops commands. I'm looking forward to building the next major version of Doctrine MongoDB ODM directly atop the extensions. While we will continue to maintain and support the 1.x driver and its users for the foreseeable future, we invite everyone to check out our next-generation driver and consider it for any new projects going forward. You can find all of the essential components across GitHub and JIRA: Project GitHub JIRA PHP Library mongodb/mongo-php-library PHPLIB PHP 5.x Driver (phongo) mongodb/mongo-php-driver PHPC HHVM Driver (hippo) mongodb/mongo-hhvm-driver HHVM The existing PHP project in JIRA will remain open for reporting bugs against the 1.x driver, but we would ask that you use the new projects above for anything pertaining to our next-generation drivers. If you're interested in hearing more about our upcoming PHP and HHVM drivers, Derick Rethans is presenting a new talk entitled One Extension, Two Engines at php[tek] 2015 in May. About the Author - Jeremy Jeremy Mikola is a software engineer at MongoDB's NYC office. As a member of the driver and evangelism team, he helps develop the PHP driver and contributes to various OSS projects, such as Doctrine ODM and React PHP. Jeremy lives in Hoboken, NJ and is known to enjoy a good sandwich.
Control Your Colours in MongoDB Charts
Colours are integral to the story you want to convey with any sort of data visualisation. With the latest release of MongoDB Charts , we have added more control to how you can assign colours to your charts! Previously, colour assignment of a series were always based on the series order within that chart. However, we may instead want to colour the chart based on the series value. Some basic scenarios where these different strategies prove useful include: Colouring the top 3 series with the colours gold, silver and bronze. Colouring the series "Summer" and "Winter" with "Red" and "Blue" respectively, to symbolise the season. If the above examples did not give it away enough, we will create some beautiful charts using an Olympics dataset to fully understand the capabilities of the new features. Single-series charts We will start off with a basic single-series chart. These charts usually have a single field encoded to the x and y axes and will display a single colour for the chart. In these charts, we now show a single colour swatch for you to edit. Simple, right? Multi-series charts For more complicated charts with multiple series, we may want to colour the series based on the encoded field itself. These charts are created when multiple fields are encoded to an aggregation channel where the field key is used to build the multi-series chart. In the above chart, I have a medal tally of the top 10 countries based on medal count. The chart itself is fine, but we could improve this chart with some useful colouring! A notable colour scheme we could apply to this chart is assigning each series to the colour of the medal. Inside the Color Palette customisation option, you will see that each encoded field is now listed based on the order that they were encoded in. With the colour scheme set to the medal colour, the chart will be a lot easier to convey the original information. Colours assigned to these channels will always have the same colour assigned and will ignore the ordering of these fields. Assigning chart colours to string data The final chart that we want to create, involves a chart where the data itself is a String type. With these chart types, the Color Palette will provide options to toggle between the two different colour assignment strategies where: 'By Order' will allow you to assign colours by the ordering of the series 'By Series' lets you customise the colour for a specific series value To help streamline the process of assigning colours in the above chart, in the ‘By Order’ menu, I can choose to assign colours based on the value order of the Discipline that appears in the chart. This may be useful if we don't care what the colours are that represent each Discipline. Alternatively, we could assign colours using 'By Series' so that we can be assured that I can represent the Disciplines with an associated colour. Now that we have created all of our charts using the different ways we can assign colours, we can be confident that the colours in our data visualisations are consistent throughout our dashboard. Want to start colouring your charts today? You can start now for free by signing up for MongoDB Atlas , deploying a free tier cluster and activating Charts. Have an idea on how we can make MongoDB Charts better? Feel free to leave an idea at the MongoDB Feedback Engine .