Co-authors: Kenneth Tay and Xiaofeng Wang At Linkedin, we constantly evaluate the value our products and services deliver, so that we can provide the best possible experiences for our members and customers. This includes understanding how product changes impact key metrics related to those experiences. However, simply looking at connections between product...
scale Articles
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- Topics:
- infrastructure,
- scale,
- A/B Testing
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Co-authors: Kinjal Basu, Yao Pan, Rohan Ramanath, Konstantin Salomatin, Amol Ghoting, and S. Sathiya Keerthi Building thriving internet or web products requires optimizing for multiple business metrics. In many applications, these business metrics can move in conflicting directions, and delicately balancing these tradeoffs can be vital for the success of a...
- Topics:
- artificial intelligence,
- scale,
- machine learning,
- Open Source
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Co-authors: Xiaoyang Gu, Xie Lu, and Xiaoguang Wang Introduction In August 2019, we introduced our members and customers to the idea of moving LinkedIn’s two core talent products—Jobs and Recruiter—onto a single platform to help talent professionals be even more productive. This single platform is called the New Recruiter & Jobs. Figure 1: New Recruiter & Jobs...
- Topics:
- infrastructure,
- scale,
- Data
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Within a matter of hours of each day beginning, we ingest tens of billions of records from online sources to HDFS, aggregated across...
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Co-authors: Konstantin V. Shvachko, Chen Liang, and Simbarashe Dzinamarira LinkedIn runs its big data analytics on Hadoop. During the...
- Topics:
- scale,
- Hadoop,
- Distributed Systems,
- infrastructure
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Co-authors: Vincent Wang, Siddharth Teotia, Manoj Thakur, and Mayank Shrivastava As our LinkedIn Marketing Solutions Blog recently...