data_engineering | Dự án mở về Data Engineering của BeeCost Trợ

by beecost Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | data_engineering Summary

data_engineering is a Java library. data_engineering has no bugs, it has no vulnerabilities and it has low support. However data_engineering build file is not available. You can download it from GitHub.

Đây là dự án thực hành các vấn đề thực tế của BeeCost.Com khi làm Data Engineering trên dữ liệu lớn của các trang web E-Commerce. Bạn có thể thoải mái sử dụng hay chia sẻ tài nguyên tại project này, trừ các hình ảnh thuộc về thương hiệu của BeeCost.

Support

Quality

Security

License

Reuse

Support

data_engineering has a low active ecosystem.

It has 16 star(s) with 12 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

data_engineering has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of data_engineering is current.

Quality

data_engineering has 0 bugs and 0 code smells.

Security

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

data_engineering code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

data_engineering does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

data_engineering releases are not available. You will need to build from source code and install.

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

data_engineering saves you 1090 person hours of effort in developing the same functionality from scratch.

It has 2467 lines of code, 239 functions and 28 files.

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

Top functions reviewed by kandi - BETA

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

Runs the tool
Prints the help
Map arguments
Parse argument annotations
Split string by delimiter
Splits a string using the given delimiter
Breaks a string into an array of tokens
Splits a string into an array
Read last line from file
Write a line to a writer
Returns a string representation of the supported values
Returns a random UUID
Add all string array to the source list
Normalize the site
Checks if is after date1
Add a suffix to a file
Creates a temporary directory
Create a string from an array of objects
Executes a command on a Linux platform
Removes a suffix from a file
Returns the number of lines in the file
Get all files in the given directory
Test program
Get params from request path
Maps a string to a type
Gets a field index

Get all kandi verified functions for this library.

data_engineering Key Features

No Key Features are available at this moment for data_engineering.

data_engineering Examples and Code Snippets

No Code Snippets are available at this moment for data_engineering.

Community Discussions

Trending Discussions on data_engineering

Kedro - how to pass nested parameters directly to node

Pipeline can't find nodes in kedro

QUESTION

Kedro - how to pass nested parameters directly to node

Asked 2020-Apr-27 at 09:31

kedro recommends storing parameters in conf/base/parameters.yml. Let's assume it looks like this:

...

ANSWER

Answered 2020-Apr-27 at 09:31

(Disclaimer: I'm part of the Kedro team)

Thank you for your question. Current version of Kedro, unfortunately, does not support nested parameters. The interim solution would be to use top-level keys inside the node (as you already pointed out) or decorate your node function with some sort of a parameter filter, which is not elegant either.

Probably the most viable solution would be to customise your ProjectContext (in src//run.py) class by overwriting _get_feed_dict method as follows:

Source https://stackoverflow.com/questions/61452211

QUESTION

Pipeline can't find nodes in kedro

Asked 2020-Mar-02 at 18:53

I was following pipelines tutorial, create all needed files, started the kedro with kedro run --node=preprocessing_data but got stuck with such error message:

...

ANSWER

Answered 2020-Feb-23 at 03:14

I think it looks like you need to have the pipeline in __default__. e.g.

Source https://stackoverflow.com/questions/60355240

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

Vulnerabilities

No vulnerabilities reported

Install data_engineering

You can download it from GitHub.
You can use data_engineering like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the data_engineering component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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 .

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