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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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Long-running queries

Database queries that are initiated by Superset to render charts must complete within the lifetime of HTTP/HTTPS requests. Some long-running database queries can cause a request timeout if they exceed the maximum duration of a request. But it is possible to configure Superset to handle long-running queries properly using a Celery distributed queue, and transfer the responsibility of query handling to Celery workers.

In large databases, it is common to run queries that run for minutes and hours while most commonly web request timeouts are within 30-60 seconds. Therefore, it is necessary that we configure this asynchronous query execution backend for Superset.

We need to ensure that the worker and the Superset server both have the same values for common configuration variables.

Redis is the recommended message queue for submitting new queries to Celery workers...

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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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