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You're reading from  Apache Superset Quick Start Guide

Product typeBook
Published inDec 2018
Reading LevelIntermediate
Publisher
ISBN-139781788992244
Edition1st Edition
Languages
Python
Tools
Apache Superset
Concepts
Business Intelligence
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Author (1)
Shashank Shekhar
Shashank Shekhar
author image
Shashank Shekhar

Shashank Shekhar is a data analyst and open source enthusiast. He has contributed to Superset and pymc3 (the Python Bayesian machine learning library), and maintains several public repositories on machine learning and data analysis projects of his own on GitHub. He heads up the data science team at HyperTrack, where he designs and implements machine learning algorithms to obtain insights from movement data. Previously, he worked at Amino on claims data. He has worked as a data scientist in Silicon Valley for 5 years. His background is in systems engineering and optimization theory, and he carries that perspective when thinking about data science, biology, culture, and history.
Read more about Shashank Shekhar

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Web server

We can integrate Superset with many web server options, such as Gunicorn, NGINX, and Apache HTTP, depending on our runtime requirements.

Web servers handle HTTP or HTTPS requests. A Superset web server typically processes a large number of such requests to render charts. Each request generates an I/O-bound database query in Superset. This query is not CPU-bound because the query execution happens at the database level and the result is returned to Superset by the database query execution engine. Requests to a Superset web server almost always require a dynamic output and not a static resource as a response. Gunicorn is a Python WSGI HTTP server. WSGI is a Python application interface based on the Python Enhancement Proposal (PEP) 333 standard. It specifies how Python applications interface with a web server. Gunicorn is the recommended web server for deploying a Superset...

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Apache Superset Quick Start Guide
Published in: Dec 2018Publisher: ISBN-13: 9781788992244
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Shashank Shekhar

Shashank Shekhar is a data analyst and open source enthusiast. He has contributed to Superset and pymc3 (the Python Bayesian machine learning library), and maintains several public repositories on machine learning and data analysis projects of his own on GitHub. He heads up the data science team at HyperTrack, where he designs and implements machine learning algorithms to obtain insights from movement data. Previously, he worked at Amino on claims data. He has worked as a data scientist in Silicon Valley for 5 years. His background is in systems engineering and optimization theory, and he carries that perspective when thinking about data science, biology, culture, and history.
Read more about Shashank Shekhar

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