|
You are here |
delta.io | ||
| | | | |
lakefs.io
|
|
| | | | | A comparison between data lake table formats: Hudi Iceberg and Delta Lake. With advice on how to pick the best one for a particular workload | |
| | | | |
www.ssp.sh
|
|
| | | | | You'll learn web-scraping with real-estates, uploading them to S3, Spark and Delta Lake, adding Data Science with Jupyter, ingesting into Druid, visualising with Superset and managing everything with Dagster. | |
| | | | |
jack-vanlightly.com
|
|
| | | | | In the previous post, I covered append-only tables, a common table type in analytics used often for ingesting data into a data lake or modeling streams between stream processor jobs. I had promised to cover native support for changelog streams, aka change data capture (CDC), but before I do so, I think we should first look at how the table formats support the ingestion of data with row-level operations (insert, update, delete) rather than query-level operations that are commonly used in SQL batch commands. | |
| | | | |
ml-ops.org
|
|
| | | Machine Learning Operations | ||