Pinot, an open source scalable distributed columnar OLAP data store, is used extensively across almost all areas of LinkedIn. It drives member-facing use cases such as Feed Item Popularity and Who Viewed My Profile, supports recruiter tools such as Talent Intelligence, and holds the data for our internal unified metrics platform. Pinot adoption has grown...
Performance Articles
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- Topics:
- Performance,
- Pinot,
- linux
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Monitor, profile, optimize, and ramp. This is the cycle of performance operations that we rely on to improve our Android app. Part 1 of this blog series covered monitoring and profiling — monitoring gives us the “true north” of optimizations to make data-driven decisions, while profiling helps us pinpoint the areas of opportunity. In part 2, we will look at...
- Topics:
- Performance,
- Mobile,
- Android,
- RUM,
- site speed
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Defined as the speed at which an app loads and responds to a member, app performance is critical to an app’s success. When an app responds slowly to a member interaction, it’s an unsatisfactory experience. In order to maintain a reliable and consistent member experience, we have a dedicated performance engineering team to monitor and troubleshoot performance...
- Topics:
- Performance,
- Mobile,
- Android
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One of the core aspirations of the engineering teams at LinkedIn is to delight our members with instantaneous page load experiences....
- Topics:
- Performance,
- site speed
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“Make LinkedIn feel instantaneous” is a mantra our performance team lives by to deliver the best possible experience to our members....
- Topics:
- Performance,
- experimentation,
- machine learning
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At LinkedIn, we use data to improve our members’ experiences while using our site. On the video team, we value metrics that yield...
- Topics:
- Video,
- Performance,
- NYC Engineering