Getting Started with Delta Lake
summary
Delta Lake adds an ACID layer over cloud object storage, storing a Delta log of JSON/parquet commits so tables support time travel and consistent concurrent writes. Demos show Python and Spark writers (five rows appended to ten), conditional UPDATE/DELETE and MERGE semantics, streaming ingest with checkpointed offsets, and a Rust stack that reads metadata, runs DataFusion SQL, and exposes a low-latency HTTP SQL API on localhost 8080. Integrations mentioned include Kafka ingestion and Delta Sharing as an open protocol.
AI-written summary · about
chapters (5)
- 0:00Start
- 1:26What Matters to Data Platform Users?
- 6:12Delta: Key Technology Enabling Lakehouse
- 7:14A DELTA LAKE
- 14:50Tutorial requirements
related talks
39mDelta Lake: Diving into Data Lakes Without the Downsides
20mDelta Lake: Turn your Data Lake into a Lakehouse
30mDelta Lake and Delta Sharing
19mOpen Source Reliability for Data Lakes
01h 28mBuilding Reliable, Open Lakehouses with Delta Lake
58mBuild reliable data lakes with Delta Lake & Databricks
31mDelta Lake: Open Source Reliability and Quality for Data Lakes
28mLakehouse Architecture with Delta Lake and Databricks