bpr-spark | Bayesian Personalized Ranking for Spark

by alfredolainez Python Version: Current License: MIT

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

kandi X-RAY | bpr-spark Summary

bpr-spark is a Python library typically used in Big Data, Spark applications. bpr-spark has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However bpr-spark build file is not available. You can download it from GitHub.

Bayesian Personalized Ranking for Spark

Support

Quality

Security

License

Reuse

Support

bpr-spark has a low active ecosystem.

It has 38 star(s) with 25 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 0 have been closed. On average issues are closed in 984 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of bpr-spark is current.

Quality

bpr-spark has 0 bugs and 0 code smells.

Security

bpr-spark has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

bpr-spark code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

bpr-spark is licensed under the MIT License. This license is Permissive.

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

Reuse

bpr-spark releases are not available. You will need to build from source code and install.

bpr-spark has no build file. You will be need to create the build yourself to build the component from source.

bpr-spark saves you 142 person hours of effort in developing the same functionality from scratch.

It has 355 lines of code, 12 functions and 5 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed bpr-spark and discovered the below as its top functions. This is intended to give you an instant insight into bpr-spark implemented functionality, and help decide if they suit your requirements.

Optimizes a given set of ratings
Gradient of a single point
Sample the optimizer

Get all kandi verified functions for this library.

bpr-spark Key Features

No Key Features are available at this moment for bpr-spark.

bpr-spark Examples and Code Snippets

No Code Snippets are available at this moment for bpr-spark.

Community Discussions

Trending Discussions on bpr-spark

AttributeError: 'NoneType' object has no attribute 'write in Pyspark

QUESTION

AttributeError: 'NoneType' object has no attribute 'write in Pyspark

Asked 2019-Sep-26 at 14:31

Spark: 2.4.4 Pyspark

I have registered temp table and trying to save output to a csv file. but getting error as "AttributeError: 'NoneType' object has no attribute 'write'"

...

ANSWER

Answered 2019-Sep-26 at 10:22

You are assigning the result of show() to the variable output and show() doesn't return a value.

So, you want to assign the Dataframe to the variable output, and then saving it like this:

Source https://stackoverflow.com/questions/58114009

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install bpr-spark

You can download it from GitHub.
You can use bpr-spark like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: