Skip to main content
PYSPARK โ€ข LESSON 177

Initializing Ingestion with readStream

How do we initialize a real-time streaming DataFrame from incoming Parquet file events with explicit schema?

Productionโฑ 2 Minutesโญ 1100 XP
๐Ÿค” THE QUESTION

How do we initialize a real-time streaming DataFrame from incoming Parquet file events with explicit schema?

๐Ÿ’ก WHAT IS IT?

spark.readStream.format('parquet').schema(schema).load(path) creates an unbound streaming DataFrame.

๐ŸŽฏ WHAT IS IT USED FOR?

Real-time event processing, IoT telemetry ingestion, and continuous file landing pipelines.

๐Ÿ’ป EXAMPLE
streaming_df = spark.readStream \
    .format("parquet") \
    .schema(event_schema) \
    .load("streaming_landing/events")

๐ŸŽฏ Mission Objectives

Practice typing production-grade PySpark code for Initializing Ingestion with readStream.

  • โœ“ Use spark.readStream reader API
  • โœ“ Enforce explicit streaming schema
  • โœ“ Instantiate continuous streaming DataFrame