pysparkling | pure Python implementation of Apache Spark
kandi X-RAY | pysparkling Summary
kandi X-RAY | pysparkling Summary
pysparkling is a Python library typically used in Big Data, Spark applications. pysparkling has no bugs, it has no vulnerabilities, it has build file available and it has low support. However pysparkling has a Non-SPDX License. You can install using 'pip install pysparkling' or download it from GitHub, PyPI.
A pure Python implementation of Apache Spark's RDD and DStream interfaces.
A pure Python implementation of Apache Spark's RDD and DStream interfaces.
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Quality
Security
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pysparkling has a low active ecosystem.
It has 235 star(s) with 45 fork(s). There are 8 watchers for this library.
It had no major release in the last 12 months.
There are 6 open issues and 21 have been closed. On average issues are closed in 225 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of pysparkling is 0.6.2
Quality
pysparkling has 0 bugs and 0 code smells.
Security
pysparkling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
pysparkling code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
pysparkling has a Non-SPDX License.
Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
Reuse
pysparkling releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
pysparkling saves you 1859 person hours of effort in developing the same functionality from scratch.
It has 14875 lines of code, 2103 functions and 121 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed pysparkling and discovered the below as its top functions. This is intended to give you an instant insight into pysparkling implemented functionality, and help decide if they suit your requirements.
- Return a commandclass instance based on the given cmdclass
- Build a ConfigParser from root
- Get the version information from the VCS
- Get the project root directory
- Take a sample of elements from the RDD
- Shuffle an array
- Compute the fractional distribution for a given sample size
- Read data from a Spark record
- Take a sequence of samples from the RDD
- Create the versioneer config file
- Install versioneer
- Save the RDD as text file
- Write the given items to the csv file
- Convert an object to JSON
- Create a new grouped dataframe
- Persist the database
- Load a dataset from a file
- Return a custom JSON encoder
- Compute the crosstab
- Generates the months between start and end
- Convert timestamps to timezone
- Prints n lines to stdout
- Plot CPU performance
- Convert to Pandas DataFrame
- Read data from csv files
- Get the versioned version information
- Create a grouping ID
Get all kandi verified functions for this library.
pysparkling Key Features
No Key Features are available at this moment for pysparkling.
pysparkling Examples and Code Snippets
No Code Snippets are available at this moment for pysparkling.
Community Discussions
Trending Discussions on pysparkling
QUESTION
H2OGridSearch H2OGBM pyspark: NullPointerException in extractH2OParameters
Asked 2020-Feb-18 at 13:42
I'm trying to run a grid search for Gradient Boosting Machine in pyspark with H2O Sparkling Water.
Produced a reproducible example with the famous iris dataset.
...ANSWER
Answered 2020-Feb-15 at 13:34Why not use a workaround and utilize H2O UI to create the grid? There's a checkbox to make your chosen parameter griddable, and you can supply the parameter values as a comma-separated list via the web form where you would normally put a single value.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install pysparkling
You can install using 'pip install pysparkling' or download it from GitHub, PyPI.
You can use pysparkling 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.
You can use pysparkling 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 .
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