3/17/2023 0 Comments Denny lees magic maps google![]() ![]() Combined, we refer to these tables as a “multi-hop” architecture. Building a Machine Learning Data Pipeline with Delta Lake Multi-Hop ArchitectureĪ common architecture uses tables that correspond to different quality levels in the data engineering pipeline, progressively adding structure to the data: data ingestion (“Bronze” tables), transformation/feature engineering (“Silver” tables), and machine learning training or prediction (“Gold” tables). These features of Delta Lake allow data engineers and scientists to design reliable, resilient, automated data pipelines and machine learning models faster than ever. Integration with MLflow, enabling experiments to be tracked and reproduced by automatically logging experimental parameters, results, models and plots.data versioning, allowing changes to any Delta Lake table to be audited, reproduced, or even rolled back if needed in the event of unintentional changes made due to user error. Schema evolution, which allows new columns to be added to existing data tables, even while those tables are being used in production, without causing breaking changes. ![]() Schema enforcement, which ensures that tables are kept clean and tidy, free from column contamination, and ready for machine learning.Tables that can continuously process new data flows from both historical and real-time streaming sources, greatly simplifying the data science production pipeline.Along the way, we’ll demonstrate how Delta Lake is the ideal platform for the machine learning life cycle because it offers tools and features that unify data science, data engineering, and production workflows, including: In this article, we’ll walk through the process of building a production data science pipeline step-by-step. The vast majority of their time is spent doing the less-than-glamorous (but crucial) work of performing ETL, building data pipelines, and putting models into production. Try out this notebook series in Databricks - part 1 (Delta Lake), part 2 (Delta Lake + ML)įor many data scientists, the process of building and tuning machine learning models is only a small portion of the work they do every day. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |