Remove author daili-zhang
article thumbnail

Revolutionizing Real-Time Streaming Processing: 4 Trillion Events Daily at LinkedIn

LinkedIn Engineering

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers. More details about this use case can be found on LinkedIn’s engineering blog.

Process 119
article thumbnail

PinCompute: A Kubernetes Backed General Purpose Compute Platform for Pinterest

Pinterest Engineering

Harry Zhang, Jiajun Wang, Yi Li, Shunyao Li, Ming Zong, Haniel Martino, Cathy Lu, Quentin Miao, Hao Jiang, James Wen, David Westbrook | Cloud Runtime Team Image Source: [link] Overview Modern compute platforms are foundational to accelerating innovation and running applications more efficiently.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Unified Streaming And Batch Pipelines At LinkedIn: Reducing Processing time by 94% with Apache Beam

LinkedIn Engineering

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. In this blog post, we will share our progress, challenges, and lessons learned from implementing Apache Beam.

Process 97
article thumbnail

Enhancing homepage feed relevance by harnessing the power of large corpus sparse ID embeddings

LinkedIn Engineering

Co-authors: Jason (Siyu) Zhu , Amol Ghoting , Birjodh Tiwanna , Maneesh Varshney Introduction At LinkedIn, we strive to provide our members with valuable content that can help them build professional networks, learn new skills, and discover exciting job opportunities.