271 results for "pinot" across all locations

Prueba piloto de la función que muestra las ganancias estimadas por kilómetro recorrido en las solicitudes de viaje
We are piloting the introduction of estimated earnings per active hour on trip requests in a few cities in Chile, Argentina, and Mexico.
When choosing to accept a trip request, drivers consider many factors such as fare, distance, and time. Estimated earnings per kilometer is a simple way to compare trips requests that you receive.

Pinot for Low-Latency Offline Table Analytics
Learn how Uber uses Apache Pinot for serving over 100 low-latency offline analytics use cases.

Engineering SQL Support on Apache Pinot at Uber
We engineered full SQL support on Apache Pinot to enable quick analysis and reporting on aggregated data, leading to improved experiences on our platform.

Serving Millions of Apache Pinot™ Queries with Neutrino
At Uber, we serve 500 million Pinot queries every day. Learn how we optimized and built an internal fork of Presto to support query features like window functions and sub-queries, all while supporting sub-second latencies at thousands of QPS.

Operating Apache Pinot @ Uber Scale
Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making.

Enabling Infinite Retention for Upsert Tables in Apache Pinot
With contributions from Uber and others, Apache Pinot™ now supports deletion with upsert tables! Learn how Uber drove these advancements and how you can benefit from cost-efficient infinite retention.

Real-Time Analytics for Mobile App Crashes using Apache Pinot
Updating enterprise-scale software and infrastructure without creating unintentional downstream issues is a daunting task–we leveraged Apache Pinot to create Healthline, a tool for minimizing release errors in real time and at Uber scale.

Pinot Real-Time Ingestion with Cloud Segment Storage

How Uber Accomplishes Job Counting At Scale
Have more rows than you can count on two hands? Don’t feel like using approximations? Learn how Uber uses Apache Pinot™ to count!

Real-Time Exactly-Once Ad Event Processing with Apache Flink, Kafka, and Pinot
Uber recently launched a new capability: Ads on UberEats. With this new ability came new challenges that needed to be solved at Uber, such as systems for ad auctions, bidding, attribution, reporting, and more.