Skip to main content
DatabricksPySparkSnowflakeApache Airflow
Code Keys/PySpark Academy/Module 28/Lesson 230
PYSPARK • LESSON 230

Production CDC Deduplication Pipeline

How can we build a full Change Data Capture (CDC) deduplication pipeline handling inserts, updates, and deletes?

Advanced⏱ 3 Minutes⭐ 890 XP
🤔 THE QUESTION

How can we build a full Change Data Capture (CDC) deduplication pipeline handling inserts, updates, and deletes?

💡 WHAT IS IT?

Filtering for the latest record per primary key and removing soft-deleted records (op == 'D') produces the current valid snapshot.

🎯 WHAT IS IT USED FOR?

Maintaining an accurate real-time replica of relational databases (PostgreSQL, MySQL) in the data lake.

💻 EXAMPLE
w = Window.partitionBy("entity_id").orderBy(col("cdc_timestamp").desc())
df_current_state = df_cdc.withColumn("rn", row_number().over(w)).filter(col("rn") == 1).filter(col("op") != "DELETE").drop("rn")

🎯 Mission Objectives

Practice typing production-grade PySpark code for Production CDC Deduplication Pipeline.

  • ✓ CDC snapshot generation
  • ✓ Soft-delete handling
  • ✓ Production Lakehouse replication
🚀 Start Mission
← Prev (Deduplicating Nested Struct Sub-Records)Next Lesson (Cumulative Running Totals with Unbounded Frames) →