データとAIの企業：未来をリードするデータインテリジェンスプラットフォーム |​ Databricks

Azure Databricks Lakehouse Architecture Explained

Databricks Lakehouse Platform

Anamika🦋 on Instagram: "Day 14: Understanding Autoloader Features in Databricks Today I learned about the key features that make Autoloader so powerful for streaming data ingestion. First, it provides Idempotency, which means it keeps track of files already processed using RocksDB at the checkpoint location — so no data gets reprocessed. Second, it offers Schema Inference, where Autoloader automatically detects the schema from source files when data is first loaded. If new columns appear later,

Azure Databricks & Spark For Data Engineers (PySpark / SQL)

Advanced Analytics using Apache Spark in Azure Databricks

Processing Streaming Data with Apache Spark on Databricks