Build Data Pipelines with Lakeflow Spark Declarative Pipelines
This course introduces users to the essential concepts and skills needed to build data pipelines using Lakeflow Spark Declarative Pipelines (SDP) in Databricks for incremental batch or streaming ingestion and processing through multiple streaming tables and materialized views. Designed for data engineers new to Spark Declarative Pipelines, the course provides a comprehensive overview of core components such as incremental data processing, streaming tables, materialized views, and temporary views, highlighting their specific purposes and differences.
Topics covered include:
- Developing and debugging ETL pipelines with the multi-file editor in Spark Declarative Pipelines using SQL (with Python code examples provided)
- How Spark Declarative Pipelines track data dependencies in a pipeline through the pipeline graph
- Configuring pipeline compute resources, data assets, trigger modes, and other advanced options
Next, the course introduces data quality expectations in Spark Declarative Pipelines, guiding users through the process of integrating expectations into pipelines to validate and enforce data integrity. Learners will then explore how to put a pipeline into production, including scheduling options, and enabling pipeline event logging to monitor pipeline performance and health.
Finally, the course covers how to implement Change Data Capture (CDC) using the AUTO CDC INTO syntax within Spark Declarative Pipelines to manage slowly changing dimensions (SCD Type 1 and Type 2), preparing users to integrate CDC into their own pipelines.
⇾ Basic understanding of the Databricks Data Intelligence platform, including Databricks Workspaces, Apache Spark, Delta Lake, the Medallion Architecture and Unity Catalog.
⇾ Experience ingesting raw data into Delta tables, including using the read_files SQL function to load formats like CSV, JSON, TXT, and Parquet.
⇾ Proficiency in transforming data using SQL, including writing intermediate-level queries and a basic understanding of SQL joins.
Outline
Introduction to Data Engineering in Databricks
⇾ Data Engineering in Databricks
⇾ What are Lakeflow Spark Declarative Pipelines?
⇾ Course Setup and Creating a Pipeline
⇾ Course Project Overview
Lakeflow Spark Declarative Pipeline Fundamentals
⇾ Dataset Types Overview
⇾ Simplified Pipeline Development
⇾ Common Pipeline Settings
⇾ Developing a Simple Pipeline
⇾ Ensure Data Quality with Expectations
Building Lakeflow Spark Declarative Pipelines
⇾ Streaming Joins Overview
⇾ Deploying a Pipeline to Production
⇾ Change Data Capture (CDC) Overview
⇾ Change Data Capture with AUTO CDC INTO
⇾ Additional Features Overview
Upcoming Public Classes
Date | Time | Language | Price |
|---|---|---|---|
Dec 08 | 01 PM - 05 PM (Europe/London) | English | $750.00 |
Dec 08 | 01 PM - 05 PM (America/New_York) | English | $750.00 |
Dec 09 | 09 AM - 01 PM (Asia/Kolkata) | English | $750.00 |
Jan 12 | 01 PM - 05 PM (Australia/Sydney) | English | $750.00 |
Jan 12 | 09 AM - 01 PM (Europe/London) | English | $750.00 |
Jan 12 | 09 AM - 01 PM (America/New_York) | English | $750.00 |
Public Class Registration
If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.
Private Class Request
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