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

LinkedIn Engineering

In 2010, they introduced Apache Kafka , a pivotal Big Data ingestion backbone for LinkedIn’s real-time infrastructure. To transition from batch-oriented processing and respond to Kafka events within minutes or seconds, they built an in-house distributed event streaming framework, Apache Samza.

Process 119
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Building A Data Lake For The Database Administrator At Upsolver

Data Engineering Podcast

What used to be entirely managed by the database engine is now a composition of multiple systems that need to be properly configured to work in concert. What used to be entirely managed by the database engine is now a composition of multiple systems that need to be properly configured to work in concert.

Data Lake 100
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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

This architecture shows that simulated sensor data is ingested from MQTT to Kafka. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase. Machine Learning web service to host forecasting code. Blob Storage for intermediate storage of generated predictions.