Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more. Pinot uses Apache Helix for managing cluster resources and Apache Zookeeper to store metadata. Pinot has wide adoption at LinkedIn, ranging from internal...
Pinot Articles
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- Topics:
- scale,
- Developer Productivity,
- Pinot,
- infrastructure
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Pinot is an open source, scalable distributed OLAP data store that entered the Apache Incubation recently. Developed at LinkedIn, it works across a wide variety of production use cases to deliver real-time, low latency analytics. One of the biggest challenges in Pinot is achieving and maintaining tight SLA on latency and throughput on large data sets. Existing...
- Topics:
- Pinot,
- Distributed Systems,
- Open Source
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Earlier this year, we published a blog post sharing details on ThirdEye, LinkedIn’s comprehensive platform for real-time monitoring and root cause analysis. LinkedIn relies on ThirdEye to monitor a wide spectrum of metrics, ranging from product health to high-level business metrics, and also including machine learning model performance. While monitoring is a...
- Topics:
- monitoring,
- metrics,
- Pinot
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Pinot is a scalable distributed OLAP data store developed at LinkedIn to deliver real-time, low latency analytics. Pinot’s powerful...
- Topics:
- Pinot,
- Open Source
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At LinkedIn, we have many different monitoring systems—each with its own role and granularity— ranging from quarterly reports about...
- Topics:
- metrics,
- Pinot,
- real time monitoring
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LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first...
- Topics:
- scale,
- rest.li,
- Play,
- Open Source,
- Galene,
- Pinot,
- engineering culture,
- ESPRESSO,
- Kafka,
- inversion,
- Architecture,
- Voldemort,
- operations,
- Java,
- Search,
- Samza