Engineering

Engineering Blog

Beyond Labels: Stories of Asian Pacific Islanders at Yelp

During Asian Pacific American Heritage Month, ColorCoded (a Yelp employee resource group) hosted a panel discussion called “Beyond Labels: Stories of Asian Pacific Islanders (API)* at Yelp.” We heard stories from five API Yelpers about their cultural backgrounds, identities, and thoughts on what it means to be an API in today’s world. Their stories helped us understand that identity is both multilayered and contextual, and that individuality goes beyond labels. Read more from their unique perspectives below. Tenzin Kunsal, Events + Partnerships, Engineering Recruiting From a young age, I knew the concept of “home” was complicated. Like many refugees, my...

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Open sourcing spark-redshift-community

At Yelp, we are heavy users of both Spark and Redshift. We’re excited to announce spark-redshift-community, a fork from databricks’ original spark-redshift project. spark-redshift is a Scala package which uses Amazon S3 to efficiently read and write data from AWS Redshift into Spark DataFrames. After the open source project effort was abandoned in 2017, the community has struggled to keep up with updating dependencies and fixing bugs. The situation came to a complete halt upon release of Spark 2.4 which was sharply incompatible with the latest spark-redshift. Developers looking for a solution turned to online threads on websites like StackOverflow...

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Redesigning Yelp for Apple Watch with SwiftUI

At this year’s WWDC, Apple unveiled SwiftUI, a framework that helps developers build declarative user interfaces. At Yelp, we were immediately excited about it and were looking for a way to start adopting it. We decided that our Apple Watch application was the perfect candidate for modernization using SwiftUI and were excited to explore a redesign with this new framework. At Yelp, one of the things we pride ourselves on is the quality of our content. Yelp users have posted hundreds of millions of reviews and photos. As we set out to re-imagine the user interface for our Apple Watch...

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Discovering Popular Dishes with Deep Learning

Discovering Popular Dishes with Deep Learning Introduction Yelp is home to nearly 200 million user-submitted reviews and even more photos. This data is rich with information about businesses and user opinions. Through the application of cutting-edge machine learning techniques, we’re able to extract and share insights from this data. In particular, the Popular Dishes feature leverages Yelp’s deep data to take the guesswork out of what to order. For more details on the product itself, check out our product launch blog post. The Popular Dishes feature highlights the most talked about and photographed dishes at a restaurant, gathering user opinions...

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Hosting Our First Awesome Women in Engineering Summit in SF

Last month, we held our first Awesome Women in Engineering (AWE) Summit at our headquarters in San Francisco. AWE’s mission is to build a strong community for women and allies in our engineering and product departments by facilitating professional career-building activities, leadership, and mentorship opportunities. As a resource group, we provide support and organize activities targeted towards professional growth for women, helping them to maximize their potential at Yelp and beyond. The summit was an internal, half-day event for women and allies in engineering and product at Yelp. We had previously hosted a summit for our EU offices, but this...

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Breaking Down Technical Interviews

Finding that first job in the tech industry can be a daunting task. You might not get a response to your application, or maybe you’ll move forward with the interview, but it doesn’t pan out in the end. You might wonder, “How are other people successful at getting offers? What do others do differently? What’s the secret to getting through this arduous process?” The answer is pretty simple: lots of practice. While there’s never a guarantee of getting an offer, following these recommendations can increase your chances of successfully going through the interview process and potentially landing your dream job!...

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Maptype — fast doc-value lookups for map data in Elasticsearch

The ability to quickly serve search results is essential for Yelp. Ranking performance has a significant impact on the time it takes to process a search request, and it’s crucial for fast ranking that we can quickly look up the data that’s fed into our machine learning models. Per-document map-like data is especially challenging in this regard, as traditional approaches often read and decode the full map only to look up a single value within that map later on. MapType is a custom Elasticsearch datatype that provides an optimized look-up approach for such data. Let’s start by discussing a concrete...

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Autoscaling AWS Step Functions Activities

In an ongoing effort to break down our monolithic applications into microservices here at Yelp, we’ve migrated several business flows to modern architecture using AWS Step Functions. Transactional ordering at Yelp covers a wide variety of verticals, including food (delivery/takeout orders), booking, home services, and many more. These orders are processed via Step Functions, where each is represented as an execution instance of the workflow, as shown below. Figure 1: Illustrative Step Functions Workflow for Transactions Orders Each step in the above workflow is an “activity,” and Yelp implements these activities as batch daemons, which interact with AWS Step Functions...

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