Serverless Data Processing with Dataflow - Writing an ETL pipeline using Apache Beam and Cloud Dataflow (Java)
Offered By: Google via Google Cloud Skills Boost
Course Description
Overview
In this lab, you a) build a batch ETL pipeline in Apache Beam, which takes raw data from Google Cloud Storage and writes it to Google BigQuery b) run the Apache Beam pipeline on Cloud Dataflow and c) parameterize the execution of the pipeline.
Syllabus
- Overview
- Setup and requirements
- Apache Beam and Cloud Dataflow
- Lab part 1. Writing an ETL pipeline from scratch
- Task 1. Generate synthetic data
- Task 2. Read data from your source
- Task 3. Run your pipeline to verify that it works
- Task 4. Adding in a transformation
- Task 5. Writing to a sink
- Task 6. Run your pipeline
- Lab part 2. Parameterizing basic ETL
- Task 1. Creating a JSON schema file
- Task 2. Writing a JavaScript user-defined function
- Task 3. Running a Dataflow Template
- Task 4. Inspect the Dataflow Template code
- End your lab
Tags
Related Courses
Feature EngineeringGoogle Cloud via Coursera Feature Engineering 日本語版
Google Cloud via Coursera Feature Engineering em Português Brasileiro
Google Cloud via Coursera GCP: Complete Google Data Engineer and Cloud Architect Guide
Udemy Modeling Streaming Data for Processing with Apache Beam
Pluralsight