Skip to main content
PYSPARK • LESSON 194

High-Volume Natural Key Deduplication

How do we reconstruct the latest snapshot of account records from an out-of-order changelog using window ranking?

Production3 Minutes1650 XP
🤔 THE QUESTION

How do we reconstruct the latest snapshot of account records from an out-of-order changelog using window ranking?

💡 WHAT IS IT?

Deduplicating changelog updates by natural account ID ordered by effective timestamp descending to isolate current state.

🎯 WHAT IS IT USED FOR?

Enterprise account master data reconstruction and handling at-least-once message delivery.

💻 EXAMPLE
from pyspark.sql.window import Window
from pyspark.sql.functions import col, row_number

history_window = Window.partitionBy("account_id").orderBy(col("effective_ts").desc())

current_account_state = raw_account_updates \
    .withColumn("version_rank", row_number().over(history_window)) \
    .filter(col("version_rank") == 1) \
    .drop("version_rank")

🎯 Mission Objectives

Practice typing production-grade PySpark code for High-Volume Natural Key Deduplication.

  • Partition history by account ID
  • Rank versions by effective timestamp
  • Isolate latest current account state