bdutil | Script used to manage Hadoop

by GoogleCloudDataproc Shell Version: 1.3.3 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | bdutil Summary

bdutil is a Shell library typically used in Big Data, Spark, Hadoop applications. bdutil has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

bdutil is a command-line script used to manage Apache Hadoop and Apache Spark instances on Google Compute Engine. bdutil manages deployment, configuration, and shutdown of your Hadoop instances.

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Quality

Security

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Support

bdutil has a low active ecosystem.

It has 111 star(s) with 96 fork(s). There are 53 watchers for this library.

It had no major release in the last 12 months.

There are 26 open issues and 21 have been closed. On average issues are closed in 18 days. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of bdutil is 1.3.3

Quality

bdutil has 0 bugs and 0 code smells.

Security

bdutil has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

bdutil code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

bdutil is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

bdutil releases are available to install and integrate.

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bdutil Key Features

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bdutil Examples and Code Snippets

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Community Discussions

Trending Discussions on bdutil

How to install optional components (anaconda, jupyter) in custom dataproc image

QUESTION

How to install optional components (anaconda, jupyter) in custom dataproc image

Asked 2021-May-03 at 20:41

To speed up my cluster instantiation time, I've created a custom image with all the additional dependencies installed using miniconda3 available for dataproc image 1.5.34-debian10. (I followed the steps here: GCP Dataproc custom image Python environment to ensure I used the correct python environment).

However, when I start my cluster with --optional-components ANACONDA,JUPYTER my custom dependencies are removed and I'm left with a base installation of anaconda and jupyter. I assume the anaconda installation is overwriting my custom dependencies. Is there any way to ensure my dependencies aren't overwritten? If not, is it possible to install anaconda and jupyter as part of my custom dataproc image instead?

I've used the following command to create the custom image:

...

ANSWER

Answered 2021-May-03 at 20:41

The customize_conda.sh script is the recommended way of customizing Conda env for custom images.

If you need more than the script does, you can read the code and create your own script, but anyway you want to use the absolute path e.g., /opt/conda/anaconda/bin/conda, /opt/conda/anaconda/bin/pip, /opt/conda/miniconda3/bin/conda, /opt/conda/miniconda3/bin/pip to install/uninstall packages for the Anaconda/Miniconda env.

Source https://stackoverflow.com/questions/67357670

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