Implementation:DataExpert io Data engineer handbook DataFrame Write InsertInto

Overview

This page documents the DataFrame write with insertInto pattern used in the Data Engineer Handbook repository. This is an external PySpark API for persisting DataFrame contents to an existing catalog-managed table using column-position-based insertion with overwrite semantics.

Type

Wrapper Doc (PySpark external API)

Source

players_scd_job.py:L53

Signature

output_df.write.mode("overwrite").insertInto(table_name: str) -> None

Import

Implicit on DataFrame objects -- no separate import is required. The write property is available on all pyspark.sql.DataFrame instances.

from pyspark.sql import SparkSession  # DataFrame.write is available implicitly

Inputs / Outputs

Direction	Name	Type	Description
Input	DataFrame	DataFrame	The DataFrame whose contents will be written to the target table
Input	write mode	str	The write mode, e.g., `"overwrite"` to replace existing data
Input	table name	str	The fully qualified name of the target table (e.g., `"catalog.schema.table"`)
Output	(side effect)	None	Data is written to the specified table; no value is returned

Usage Example

# After performing the SCD transformation
output_df = do_player_scd_transformation(spark, input_df)

# Write the result to the target table, overwriting existing data
output_df.write.mode("overwrite").insertInto("players_scd")

Key Behavior Notes

Column matching is by position, not by name. The DataFrame column order must match the target table schema exactly.
overwrite mode replaces all data in the target table (or partition, if partitioning is configured).
The target table must already exist in the catalog. Unlike saveAsTable, insertInto does not create the table.

Related Pages

Knowledge Sources

Data Engineer Handbook

Metadata

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