Co-authors: Scott Meyer, Andrew Carter, and Andrew Rodriguez Editor’s note: This is the second part of a two-part blog series. Part 1 described how graph data relates to the in-memory graph of structures commonly used as models (as in “model-view-controller”) by applications, how graph data can be stored in a conventional relational database, and why...
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- Topics:
- scale,
- infrastructure,
- knowledge graph,
- Data
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The internet software industry has moved away from long development cycles and dedicated quality assurance (QA) stages, toward a fast-paced continuous-integration/continuous-delivery (CI/CD) pipeline, where new code is quickly written, committed, and pushed to user-facing applications and services. Doing so has dramatically increased iteration speeds, and at...
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Co-authors: Hunter Lee and Dru Pollini LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover new opportunities and get better at what they do. An important part of our mission is helping people to find other professionals who are interested in the same things they...
- Topics:
- Apache Helix,
- Distributed Systems,
- ESPRESSO,
- Data
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Co-authors: Sriram Vasudevan, Cyrus DiCiccio, and Kinjal Basu At LinkedIn, our imperative is to create economic opportunity for every...
- Topics:
- Spark,
- machine learning,
- Data,
- Artificial Intelligence,
- Open Source
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In the previous blog posts of our “Rebuilding messaging” series, we shared the process of how we designed the system from high-level...
- Topics:
- infrastructure,
- Architecture,
- Product Design
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Co-authors: Grace Tang, Pavan K. Ganganahalli Marulappa, Montinee Khunvirojpanich, and Ting Chen LinkedIn is an active professional...