Supporting React Native at Pinterest

Early last year, a small group of engineers started investigating the possibility of adopting React Native at Pinterest. We’ve been following the ecosystem with interest since it was first open-sourced in 2015. Since then, a robust community has developed around it, and it’s been…

Building the Pinterest app for Windows 10

Solving a user problem As we focus on developing ways to help Pinners find inspiration across all interests, locations and platforms, we knew we had to improve the experience for Windows. Accessing Pinterest from desktop requires using a browser, often times with numerous tabs…

How we built rearranging Pins

Listening to user feedback is essential to building a product Pinners love and use to discover and save ideas every day. Often, their feature requests present interesting technical challenges for our engineers. For example, today we launched the ability to…

Hybrid Search: Building a textual and visual discovery experience at Pinterest

As a visual discovery engine, Pinterest helps you discover ideas even when you don’t know what you’re looking for, or have the words to describe it. Using a mix of technology (including visual search) and community input (thanks to the 175B+ Pins…

The Fantastic Fixathon

Engineers at Pinterest are always focused on doing what’s best for the product, but working in a codebase that’s clean, well-maintained, and relatively bug-free transforms engineering tasks from being “just work” to enjoyable opportunities to flex our skills. We’re also enriched as engineers, both technically and otherwise, when we take…

Pinterest + ktlint = ❤

Ha pasado casi un año desde que la base de código Android de Pinterest se convirtió en la prioridad de Kotlin, y aproximadamente dos años desde que adoptamos ktlint para el formato y lint de Kotlin. Hoy, compartimos que Pinterest se…

Three-day no-meeting schedule for engineers

About 100 days ago, our product engineering team began experimenting with a three-day no-meeting schedule for individual contributors on our teams. It’s not a big revelation that software development requires long stretches of uninterrupted time to focus. As Pinterest has grown…

Developing fast & reliable iOS builds at Pinterest (Part one)

At Pinterest we’re focused on helping people discover inspiring ideas, from dinner recipes to try, home and style products to buy, to places to travel. Building the best products for mobile is a critical part of that, with 80% of all Pinners…

Using PID controllers to diversify content types on home feed

Every day millions of Pinners visit the home feed to find inspiration on Pinterest. As a member of the home feed ranking team, it’s my job to not only figure out what relevant pins to show Pinners but also to make sure that…

Pre-Submit Integration Tests For Ads-Serving

Introduction & Background The ads-serving platform is the highest-scale, highest-complexity, and highest-velocity recommendation service at Pinterest. Our ads business is growing and expanding, and the ads engineering team is iterating quickly to continue to improve the system. Therefore, it is vital to keep the system healthy, in order…

Pin2Interest: A scalable system for content classification

Content understanding is at the core of any great recommendation system. By knowing what each Pin is about, Pinterest can connect Pinners with the most relevant and inspiring content that best matches their interests. Taxonomy of interests The Interest Taxonomy captures popular concepts that appear within Pinterest…

PinSage: A new graph convolutional neural network for web-scale recommender systems

Deep learning methods have achieved unprecedented performance on a broad range of machine learning and artificial intelligence tasks like visual recognition, speech recognition and machine translation. However, despite amazing progress, deep learning research has mainly focused on data defined on Euclidean domains, such…

Partitioning Pinlater for Fun(?) and Profit(!)

Contained within the November 2015 announcement of the open-sourcing of Pinlater, our asynchronous job execution system, was a description of some of the improvements that had been made to the system since the original 2014 blog post describing its creation. Notable among…

Building a real-time user action counting system for ads

The Pinterest ads team’s mission is to provide the best experience for both Pinners and advertisers. Our ads system is a real-time bidding system that delivers targeted ads based on a variety of attributes. One…

Interest Taxonomy: A knowledge graph management system for content understanding at Pinterest

Interest Taxonomy at Pinterest We recently began rolling out the beta version of Pinterest Trends, a new tool that gives a view of the top U.S. search terms on Pinterest within the past 12 months, and a look into when search terms peak for…

Empowering Pinterest data scientists and machine learning engineers with PySpark

Data scientists and machine learning engineers at Pinterest found themselves hitting major challenges with existing tools. Hive and Presto were readily accessible tools for large scale data transformations, but complex logic…

Geo-blocking media content on Pinterest

Pinterest engineers are tasked with showing Pinners the best ideas related to their interests, which includes taking into account signals like location. As part of these efforts, we built a video and image platform to enable a…

Building a dynamic and responsive Pinterest

In 2015, the majority of content on Pinterest was pregenerated for users prior to login. It was stored statically in HBase and served directly upon entering the service. (More details can be found in the blog post Building a smarter home feed.) …

Powering Pinterest ads analytics with Apache Druid

The Change When we launched Promoted Pins in 2014, we chose Apache HBase as our database to store and serve all of our reporting metrics. At the beginning of our ads business, this was an appropriate choice because…

How we designed our Continuous Integration System to be more than 50% Faster

Earlier this year, the Engineering Productivity team at Pinterest published a blog called How a one line change decreased our clone times by 99%. In that post, we described how a simple Git configuration sped up clone times in one of our…

Driving Shopping Upsells from Pinterest Search

Pinterest’s mission is to bring everyone the inspiration to create a life they love. Shopping is at the core of Pinterest’s mission by helping Pinners find and purchase the products they like. Oftentimes when Pinners want to buy…

GokuL: Extending time series data storage to serve beyond one day

At Pinterest, developers rely heavily on Statsboard to monitor their systems and get alerted when issues happen. Last year, we introduced our time series database (aka Goku) which stores and serves the most recent one day’s…

How ads indexing works at Pinterest

Introduction Ads indexing is a data processing pipeline that builds servable ad documents for the ads delivering stack at Pinterest, including ads targeting, retrieval, ranking and auction. The pipeline converts ad campaigns in the raw format to the servable format via a heavy computational…

Building a universal search system for Pinterest

On Pinterest, the best answer goes beyond text, but can even go beyond an image too. When you’re looking for eye makeup ideas for example, a video personalized to your skin tone range teaching you how to create a certain look is likely…

API Profiling at Pinterest

When I walked into Pinterest on the first day of my internship and learned I’d be focusing on profiling the API Gateway service — the core backend service of the Pinterest product — my only thought was “What is profiling?”. Profiling is often shoved aside…