[SPARK-44076] SPIP: Python Data Source API

• Type: New Feature
• Status: Open
• Priority: Major
• Resolution: Unresolved
• Affects Version/s: 4.0.0
• Component/s: PySpark
• Assignee: Unassigned
• Reporter: Allison Wang
• Shepherd: Hyukjin Kwon
• Created: 16/Jun/23 04:05
• Updated: 10/Oct/23 18:20

Description

This proposal aims to introduce a simple API in Python for Data Sources. The idea is to enable Python developers to create data sources without having to learn Scala or deal with the complexities of the current data source APIs. The goal is to make a Python-based API that is simple and easy to use, thus making Spark more accessible to the wider Python developer community. This proposed approach is based on the recently introduced Python user-defined table functions (SPARK-43797) with extensions to support data sources.

SPIP: https://docs.google.com/document/d/1oYrCKEKHzznljYfJO4kx5K_Npcgt1Slyfph3NEk7JRU/edit?usp=sharing

Sub-Tasks

• Initial support for Python data source read API: Resolved
• Support registering Python data sources: Resolved
• Support loading Python data sources in DataFrameReader: Resolved
• Add InputPartition to DataSourceReader interface: Resolved
• Add Python data source write API: Resolved
• Make Python data source registration session level: Resolved
• Support spark.read.schema(...) for Python data source API: Open
• Initial support for Python data source write API: Open
• Support spark.read.load() with non-empty path for Python data source API: Open
• Support creating table using a Python data source in SQL: Open
• Support `commit` and `abort` API for Python data source write: Open
• Investigate runtime registration and feasibility of overwriting the datasource: Open
• Statically register Python Data Source: Open
• Update `path` handling in Python data source: Resolved
• Allow non-deterministic Python UDFs in MapInPandas/MapInArrow: Resolved
• Support create table using DSv2 sources: Open