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Uber Engineering
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Добавлен 27 фев 2016
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[Uber Open Source] Understanding the History of Apache Pinot
Apache Pinot is a distributed columnar database for real-time analytics. It powers many well-known applications, including LinkedIn’s Who Viewed My Profile feature and Uber Eats timely analytics. Since Pinot joined Apache Incubator in 2019, it has gained a lot of momentum with a growing community.
During this May 2020 Uber Engineering Meetup, software engineer Kishore Gopalakrishna discusses why LinkedIn decided to build Pinot, and how the solution has changed the analytics landscape at LinkedIn, Uber, and other companies.
During this May 2020 Uber Engineering Meetup, software engineer Kishore Gopalakrishna discusses why LinkedIn decided to build Pinot, and how the solution has changed the analytics landscape at LinkedIn, Uber, and other companies.
Просмотров: 4 678
Видео
![[Uber Open Source] Using Apache Pinot at Scale](http://i.ytimg.com/vi/3UN0ZkmydM8/mqdefault.jpg)
![[Uber Open Source] Using Apache Pinot at Scale](/img/tr.png)
[Uber Open Source] Using Apache Pinot at Scale
Просмотров 2,7 тыс.4 года назад
Apache Pinot is a distributed columnar database for real-time analytics. It powers many well-known applications, including LinkedIn’s Who Viewed My Profile feature and Uber Eats timely analytics. Since Pinot joined Apache Incubator in 2019, it has gained a lot of momentum with a growing community. During this May 2020 Uber Engineering Virtual Meetup, Uber software engineer Ting Chen introduces ...
![[Uber Open Source] Leveraging Pinot at Uber for Large-scale Analytics](http://i.ytimg.com/vi/E8Xsmc9AqDM/mqdefault.jpg)
[Uber Open Source] Leveraging Pinot at Uber for Large-scale Analytics
Просмотров 2,8 тыс.4 года назад
Apache Pinot is a distributed columnar database for real-time analytics. It powers many well-known applications, including LinkedIn’s Who Viewed My Profile feature and Uber Eats timely analytics. Since Pinot joined Apache Incubator in 2019, it has gained a lot of momentum with a growing community. During this May 2020 Uber Engineering Meetup, software engineers Haibo Wang and James Shao discuss...
![[Uber Open Source] New Features in Pinot: Standard SQL and Cloud Readiness](http://i.ytimg.com/vi/LayrViOqiOM/mqdefault.jpg)
[Uber Open Source] New Features in Pinot: Standard SQL and Cloud Readiness
Просмотров 8144 года назад
Apache Pinot is a distributed columnar database for real-time analytics. It powers many well-known applications, including LinkedIn’s Who Viewed My Profile feature and Uber Eats timely analytics. Since Pinot joined Apache Incubator in 2019, it has gained a lot of momentum with a growing community. During this May 2020 Uber Engineering Meetup, software engineers Sidd and Xiang introduces new Apa...
Piranha: An Open Source Tool to Automatically Delete Stale Code
Просмотров 10 тыс.4 года назад
At Uber, we use feature flags to customize our mobile app execution, serving different features to different sets of users. However, after a feature has either been 100 percent rolled out to our users or an experimental feature has been deemed unsuccessful, the feature flag in the code becomes obsolete. These nonfunctional feature flags represent technical debt, making it difficult for develope...
Introducing Uber's Engineering and Sponsorship Development Program
Просмотров 2,2 тыс.4 года назад
Uber's Engineering Sponsorship and Development Program (ESDP) was created by Thuan Pham, Uber CTO, and Sarah Bowman, CoS to the CTO, to help inspire a culture of sponsorship at Uber, as well as cultivate a more diverse and cross-functional engineering community. Through a six-month-long structured pilot program focused on sponsorship and leadership, ESDP gave junior engineers at Uber the opport...
![[WiSDOM] Moving the World with Data 2019 Introduction](http://i.ytimg.com/vi/xBqLbGC1a5E/mqdefault.jpg)
[WiSDOM] Moving the World with Data 2019 Introduction
Просмотров 1,7 тыс.5 лет назад
On October 24, 2019, the WiSDOM (Women in Statistics, Data, Optimization, and Machine Learning) Employee Resource Group hosted the second annual Moving The World With Data meetup, welcoming hundreds of members of the Bay Area tech community to learn about some of our toughest, most interesting data science problems. To kick off the event, Uber Chief Economist Jonathan Hall discussed why diversi...
![[WiSDOM] Learning Word2Vec Embeddings for Hexcluster Generation](http://i.ytimg.com/vi/kRqFn7jAsoo/mqdefault.jpg)
[WiSDOM] Learning Word2Vec Embeddings for Hexcluster Generation
Просмотров 2,9 тыс.5 лет назад
On October 24, 2019, the WiSDOM (Women in Statistics, Data, Optimization, and Machine Learning) Employee Resource Group hosted the second annual Moving The World With Data meetup, welcoming hundreds of members of the Bay Area tech community to learn about some of our toughest, most interesting data science problems. During her presentation, data scientist Mo Zhou explains how her approach to cr...
![[WiSDOM] Conversational AI at Uber](/img/1.gif)
[WiSDOM] Conversational AI at Uber
Просмотров 1,1 тыс.5 лет назад
On October 24, 2019, the WiSDOM (Women in Statistics, Data, Optimization, and Machine Learning) Employee Resource Group hosted the second annual Moving The World With Data meetup, welcoming hundreds of members of the Bay Area tech community to learn about some of our toughest, most interesting data science problems. Zhaleh Feizollahi, a computational linguist with Uber AI, offers a deep dive lo...
[WiSDOM] Learning Values and Policies from Observation
Просмотров 8365 лет назад
On October 24, 2019, the WiSDOM (Women in Statistics, Data, Optimization, and Machine Learning) Employee Resource Group hosted the second annual Moving The World With Data meetup, welcoming hundreds of members of the Bay Area tech community to learn about some of our toughest, most interesting data science problems. In this presentation, Ashley Edwards, a research scientist with Uber AI Labs, s...
[Distributed Tracing NYC] Building a DIY Distributed Database in One Weekend
Просмотров 1,7 тыс.5 лет назад
During a September 2019 Uber NYC Engineering meetup, Uber engineer Richard Artoul discusses how he built a horizontally-scalable high-throughput time series database over the course of a single weekend by leveraging M3DB, Uber's open source scalable, distributed time series database, and FoundationDB, an open source multi-model NoSQL database. Learn more about M3DB: m3db.github.io/m3/m3db/ Lear...
[Distributed Tracing NYC] Distributed Transactions -- Parallel Commits
Просмотров 1,3 тыс.5 лет назад
During a September 2019 meetup hosted at Uber's NYC Engineering Office, Peter Mattis, co-founder of Cockroach Labs, discusses how distributed transactions work and explains the benefits of parallel commits through foundational computer science theory.
[Production Engineering] Production Engineering Competencies at Uber
Просмотров 2,3 тыс.5 лет назад
In this tech talk delivered during a Production Engineering Meetup in August 2019, Uber engineering manager Donald Sumbry discusses how and why Uber's Production Engineering track introduced new competencies to reflect the discipline's unique requirements.
[Production Engineering] Designing the Blameless Infrastructure
Просмотров 9005 лет назад
In this tech talk delivered during an August 2019 Production Engineering meetup, Blameless engineer Kevin Greenan discusses how Blameless, creator of the Blameless SRE platform, designed their infrastructure to involve minimal operational staff. He also talks about the challenges his team dealt with when leveraging cloud IaaS in combination with Terraform, Kuebernetes, Helm, and custom scripts ...
[Destination:Web] Building a Great Developer Experience: The Road to Parcel Version 2
Просмотров 1,1 тыс.5 лет назад
In this tech talk delivered during a November 2019 Destination:Web Meetup, Adobe engineer Devon Govett discusses the origin of Parcel, a zero configuration web application bundler, how it distinguishes itself from similar tools, and what's in store for Parcel version 2.
[Destination:Web] A Doc Site That Writes Code for You
Просмотров 7285 лет назад
[Destination:Web] A Doc Site That Writes Code for You
[Uber Visualization] Urban Symphony
Просмотров 2,1 тыс.5 лет назад
[Uber Visualization] Urban Symphony
[Uber Seattle] Introduction to Kappa+ Architecture using Apache Flink
Просмотров 4 тыс.5 лет назад
[Uber Seattle] Introduction to Kappa Architecture using Apache Flink
[Uber Seattle] When Apache Pulsar Meets Apache Flink
Просмотров 1,4 тыс.5 лет назад
[Uber Seattle] When Apache Pulsar Meets Apache Flink
[Visualization Nights] The Metropolitan Planning Organization for Greater Cincinnati
Просмотров 5545 лет назад
[Visualization Nights] The Metropolitan Planning Organization for Greater Cincinnati
[Visualization Nights] Urban Planning Workshop with Kepler gl & Uber Movement
Просмотров 5145 лет назад
[Visualization Nights] Urban Planning Workshop with Kepler gl & Uber Movement
[Visualization Nights] SharedStreets.io
Просмотров 1 тыс.5 лет назад
[Visualization Nights] SharedStreets.io
[Visualization Nights] Introduction: Kepler.gl & Movement Speeds
Просмотров 7 тыс.5 лет назад
[Visualization Nights] Introduction: Kepler.gl & Movement Speeds
[Uber Eng Blog] Visualizing Uber Air Simulated Flights
Просмотров 3,7 тыс.5 лет назад
[Uber Eng Blog] Visualizing Uber Air Simulated Flights
Science at Uber: Improving Transportation with Artificial Intelligence
Просмотров 6 тыс.5 лет назад
Science at Uber: Improving Transportation with Artificial Intelligence
Science at Uber: Powering Machine Learning at Uber
Просмотров 6 тыс.5 лет назад
Science at Uber: Powering Machine Learning at Uber
Science at Uber: Innovating Across Digital and Physical Worlds
Просмотров 1,3 тыс.5 лет назад
Science at Uber: Innovating Across Digital and Physical Worlds
Science at Uber: Making a Real-world Impact with Data Science
Просмотров 2,6 тыс.5 лет назад
Science at Uber: Making a Real-world Impact with Data Science
Science at Uber: Applying Artificial Intelligence at Uber
Просмотров 13 тыс.5 лет назад
Science at Uber: Applying Artificial Intelligence at Uber
[Destination:Web] Lifecycle of a TC39 Proposal
Просмотров 2845 лет назад
[Destination:Web] Lifecycle of a TC39 Proposal
Amazing talk, love the explanations so clear and on point!!
Can you share a presentation plz?
Can you share a presentation plz?
Brilliant
Are there any implementations in Python?
Interesting!
Random thoughts, I just enjoy the way this speaker represents her content very much. No condescending tone, no trying-to-be-cool, and with warmth.
The critical t-statistic changes with sample size though, so that static 1.96 is misleading
This is so interestingly boring...
I can't understand what she is saying
Hey why did you only include part of the talk, that is part 7 of 8, where are all the other ones, please??!
does Uber still use this or fallen back to Google's MAP APIs for calculating the best route, ETAs based on traffic?
back to Google Maps APIs
Does this work alongside Cadence inside Uber?
Excellent talk, thnx for sharing
Great talk thanks!
Good talk
Is this available outside uber ?