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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154
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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the retry success probability) and compute cost efficiency (i.e., Multi-objective optimizations.

Tuning 202
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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. The result is increased efficiency, reduced operating costs, and enhanced productivity.

Software 202
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An overview of end-to-end entity resolution for big data

The Morning Paper

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. Dynamic approaches schedule block processing on the fly to maximise efficiency. Open source ER systems.

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Experiences with approximating queries in Microsoft’s production big-data clusters

The Morning Paper

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. Individual samplers need to be built to be high throughput and memory efficient.

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Ensuring Performance, Efficiency, and Scalability of Digital Transformation

Alex Podelko

Computing System Congestion Management Using Exponential Smoothing Forecasting by James Brady, State of Nevada. – System performance management is an important topic – and James is going to share a practical method for it. System Performance Estimation, Evaluation, and Decision (SPEED) by Kingsum Chow, Yingying Wen, Alibaba.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. I developed many batch and real-time data pipelines using open source technologies for AOL Advertising and eBay. What is your favorite project?