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PYSPARK โ€ข LESSON 20

Automatic Schema Inference with inferSchema

How can we instruct PySpark to inspect CSV values and automatically infer data types during exploration?

Beginnerโฑ 2 Minutesโญ 170 XP
๐Ÿค” THE QUESTION

How can we instruct PySpark to inspect CSV values and automatically infer data types during exploration?

๐Ÿ’ก WHAT IS IT?

inferSchema triggers an extra pass over the data to automatically cast integers, floats, and booleans from strings.

๐ŸŽฏ WHAT IS IT USED FOR?

Rapid exploratory data analysis and prototyping in development environments.

๐Ÿ’ป EXAMPLE
df = spark.read \
    .option("header", "true") \
    .option("inferSchema", "true") \
    .csv("data/logs.csv")

๐ŸŽฏ Mission Objectives

Practice typing production-grade PySpark code for Automatic Schema Inference with inferSchema.

  • โœ“ Enable automatic schema inference
  • โœ“ Chain multiple reader options
  • โœ“ Ingest typed log data