Audience

Application development solution for DevOps teams

About PySpark

PySpark is an interface for Apache Spark in Python. It not only allows you to write Spark applications using Python APIs, but also provides the PySpark shell for interactively analyzing your data in a distributed environment. PySpark supports most of Spark’s features such as Spark SQL, DataFrame, Streaming, MLlib (Machine Learning) and Spark Core. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrame and can also act as distributed SQL query engine. Running on top of Spark, the streaming feature in Apache Spark enables powerful interactive and analytical applications across both streaming and historical data, while inheriting Spark’s ease of use and fault tolerance characteristics.

Integrations

API:
Yes, PySpark offers API access

Ratings/Reviews

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Company Information

PySpark
spark.apache.org/docs/latest/api/python/

Videos and Screen Captures

PySpark Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Support
Online

PySpark Frequently Asked Questions

Q: What kinds of users and organization types does PySpark work with?
Q: What languages does PySpark support in their product?
Q: What other applications or services does PySpark integrate with?
Q: Does PySpark have an API?
Q: What type of training does PySpark provide?

PySpark Product Features

Application Development

Software Development Not Supported
Debugging Not Supported
Testing Management Not Supported
Code Assistance Not Supported
Graphical User Interface Not Supported
Version Control Not Supported
Web App Development Not Supported
Mobile Development Not Supported
Data Modeling Not Supported
Deployment Management Not Supported
Collaboration Tools Not Supported
Access Controls/Permissions Not Supported
Source Control Not Supported
Reporting/Analytics Not Supported
Code Refactoring Not Supported
Compatibility Testing Not Supported
No-Code Not Supported