Receive daily AI-curated summaries of engineering articles from top tech companies worldwide.
Endigest AI Core Summary
Pinterest describes its next-generation database ingestion framework built on CDC, Kafka, Flink, Spark, and Iceberg to replace legacy batch-based pipelines.
•Legacy batch systems suffered from 24+ hour data latency, full-table scans despite <5% daily change rates, no row-level deletion support, and fragmented pipelines
•The new unified CDC-based framework uses Debezium/TiCDC to capture changes, writes events to Kafka in under one second, and processes them via Flink into CDC Iceberg tables on S3
•Spark jobs run every 15 minutes using MERGE INTO statements to upsert a base Iceberg table, reducing latency from hours to 15 minutes–1 hour
•Merge-on-Read (MOR) was chosen over Copy-on-Write (COW) due to significantly lower storage and compute costs
•
Partitioning base tables by primary key hash (bucket function) parallelizes upserts across partitions; WRITE DISTRIBUTED BY PARTITION was added to mitigate small file explosion
This summary was automatically generated by AI based on the original article and may not be fully accurate.
Pinterest
Google Cloud
Databricks