Skip to main content
DatabricksPySparkSnowflakeApache Airflow
Code Keys/PySpark Academy/Module 33/Lesson 272
PYSPARK • LESSON 272

Fault-Tolerant Checkpointing with writeStream

How can we ensure exactly-once processing guarantees and fault recovery using writeStream checkpointing?

Production⏱ 3 Minutes⭐ 810 XP
🤔 THE QUESTION

How can we ensure exactly-once processing guarantees and fault recovery using writeStream checkpointing?

💡 WHAT IS IT?

The checkpointLocation option stores streaming offsets and state in write-ahead logs, enabling seamless restart after failures.

🎯 WHAT IS IT USED FOR?

Mission-critical real-time processing where no events can be dropped or processed multiple times.

💻 EXAMPLE
query = streaming_df.writeStream.format("parquet").option("checkpointLocation", "s3://lakehouse/checkpoints/events/").option("path", "s3://lakehouse/silver/events/").start()

🎯 Mission Objectives

Practice typing production-grade PySpark code for Fault-Tolerant Checkpointing with writeStream.

  • ✓ checkpointLocation option
  • ✓ Write-ahead log offset tracking
  • ✓ Exactly-once fault recovery
🚀 Start Mission
← Prev (Structured Streaming Source with readStream)Next Lesson (Streaming Output Modes: Append vs Complete vs Update) →