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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

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A Note to Business Leaders on Software Engineering

Strategic Tech

A software developer with a computer science degree will produce the same quality of work as any other software developer with a computer science degree. It makes business sense to hire cheap programmers and put in place a standard process. In fact, there are near infinite ways to solve every software engineering challenging.

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All of Netflix’s HDR video streaming is now dynamically optimized

The Netflix TechBlog

A vital aspect of such development is subjective testing with HDR encodes in order to generate training data. This is achieved by more efficiently spacing the ladder points, especially in the high-bitrate region. As noted in an earlier blog post , we began developing an HDR variant of VMAF; let’s call it HDR-VMAF. Krasula, A.

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Evolution of ML Fact Store

The Netflix TechBlog

We built Axion primarily to remove any training-serving skew and make offline experimentation faster. We make sure there is no training/serving skew by using the same data and the code for online and offline feature generation. Our machine learning models train on several weeks of data.

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From Student to Junior Software Engineer at Tasktop

Tasktop

The beginning of my experience as a Junior Software Engineer on one of Tasktop’s ‘Integrations Teams’ marked a definitive transition in the way I learned and practiced computer science and software development. I began my co-op term at Tasktop with two weeks of boot camp-style training.

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

These include ETL pipelines, ML model training workflows, batch jobs, etc. For example, a workflow to backfill hourly data for the past five years can lead to 43800 jobs (24 * 365 * 5), each of which processes data for an hour. But sometimes, it is not efficient.

Java 202
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Post: InterviewCamp.io, Scrapinghub, Fauna, Sisu, Educative, PA File Sight, Etleap, Triplebyte, Stream

High Scalability

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! T riplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Try out their platform. Apply here.

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