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

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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
Debugging
Testing Management
Code Assistance
Graphical User Interface
Version Control
Web App Development
Mobile Development
Data Modeling
Deployment Management
Collaboration Tools
Access Controls/Permissions
Source Control
Reporting/Analytics
Code Refactoring
Compatibility Testing
No-Code