Category: Engineering

Last year Spark Connect was introduced at the Data and AI Summit. As part of the recently released Apache SparkTM 3.4, Spark Connect is now generally available. We have also recently re-architected Databricks Connect to be based on Spark Connect. This blog post walks through what Spark Connect is, how it works, and how to […]

Since 2016, Grab has been using GrabChat, a built-in messaging feature to connect our users with delivery-partners or driver-partners. However, as the Grab superapp grew to include more features, the limitations of the old system became apparent. GrabChat could only handle two-party chats because that’s what it was designed to do. To make our messaging […]

Today, we are happy to announce the availability of Apache Spark™ 3.4 on Databricks as part of Databricks Runtime 13.0. We extend our sincere appreciation to the Apache Spark community for their invaluable contributions to the Spark 3.4 release. To further unify Spark, bring Spark to applications anywhere, increase productivity, simplify usage, and add new […]

Collective Health is not an insurance company. We’re a technology company that’s fundamentally making health insurance work better for everyone— starting with the 155M+ Americans covered by their employer. We’ve created a powerful, flexible infrastructure to simplify employer-led healthcare, and started a movement that prioritizes the human experience within health benefits. We’ve built smarter technology […]

You’ve likely tried the buzziest advances in generative AI in the past year, tools like ChatGPT and DALL-E. They consume complex data and generate more data in ways that feel startlingly like something intelligent. These and other new ideas (diffusion models, generative adversarial networks or GANs) are entertaining, even frightening to play with. However, the […]

Background eBay’s View Item page lives at the center of our e-commerce platform. Our customers load this page over 250 million times each day, and stringent budgets on site speed and availability guarantee the quality of their experience. And yet, this page had its last intentional rewrite ten years ago. A decade of rapid iteration […]

Data profiling is the process of collecting statistics and summaries of data to assess its quality and other characteristics. It is an essential step in both data discovery and the data science lifecycle because it helps us ensure quality data flows from which we can derive trustworthy and actionable insights. Profiling involves analyzing data across […]

In the United States, roughly 7 out of every 1000 mothers suffer from both pregnancy and delivery complications each year1. Of those mothers with pregnancy complications, 700 die but 60% of those deaths are preventable with the right medical attention, according to the CDC. Even among the 3.7 million successful births, 19% have either low […]

We live in a world of discovery where visual appetite reigns supreme. Window shopping, infinite scroll lists, and micro engagements using simple visual cues are the norm. Search engines traditionally interpret a textual query input and match items and/or documents ranked by their relevance to the input query. The relevance of the retrieved results is […]

To achieve our vision of becoming the leading superapp in Southeast Asia, we constantly need to balance development velocity with maintaining the high quality of the Grab app. Like most tech companies, we started out with the traditional software development lifecycle (SDLC) but as our app evolved, we soon noticed several challenges like high feature bugs and […]