Partition-Pruned Incremental Daily Ingestion

How do we filter for a specific calendar partition (year, month, day) to minimize S3 data transfer costs?

Production⏱ 2 Minutes⭐ 1440 XP

🤔 THE QUESTION

How do we filter for a specific calendar partition (year, month, day) to minimize S3 data transfer costs?

💡 WHAT IS IT?

Filtering directly on partition directory keys to trigger Spark partition pruning and avoid reading non-target directories.

🎯 WHAT IS IT USED FOR?

Daily reconciliation jobs, targeted backfills, and reducing cloud storage egress costs.

💻 EXAMPLE

from pyspark.sql.functions import col

daily_partition = spark.read \
    .parquet("lakehouse/events") \
    .filter((col("year") == 2026) & (col("month") == 8) & (col("day") == 30))

🎯 Mission Objectives

Practice typing production-grade PySpark code for Partition-Pruned Incremental Daily Ingestion.

✓ Filter on partition columns (year, month, day)
✓ Trigger physical partition pruning
✓ Minimize cloud storage I/O

🚀 Start Mission

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