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Chi-Square Test to Compare Categorical Variables

Complete Guideline to Find Dependencies among Categorical Variables with Chi-Square TestPhoto by Kier In Sight on UnsplashMotivationMany statistical tests are available, like the p-test, z-test, students’ t-test, ANOVA test, etc. Why do we need the Chi-Square test? None of the above tests show the dependency of categorical variables. Chi-Square test is the best statistical weapon for doing the job. The main...
Scalable WebSocket Architecture for Multiplayer Games

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Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support…

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloadsby Kostas ChristidisIntroductionTimestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of our media encoding platform, Cosmos. Over the past 2.5 years, its usage has increased, and Timestone is now also the priority queueing engine backing our general-purpose workflow orchestration engine (Conductor),...
Data processing with Spark: time traveling

The utilities which enable us to accomplish ACID in Spark, do not come empty handed. They have many features and in this article I will detail out time traveling. So buckle up, we are visiting the past!In order to show-case time traveling I will make use of the late arriving facts data. The data used for the POC reflects the registration...
Super Tables: The road to building reliable and discoverable data products

Co-authors: David Lu, Hong Liu, Thomas Kwan, Christopher Harris, Weiping Si Many companies, including LinkedIn, have experienced exponential data growth ever since the Apache Hadoop adoption a decade ago. With a proliferation of self-service data authoring tools and publishing platforms, different teams have created and shared datasets to address business needs quickly. While the use of self-service tools and platforms was...