Serverless Data Processing with Dataflow - Writing an ETL pipeline using Apache Beam and Cloud Dataflow (Java)
Google via Google Skills
NY State-Licensed Certificates in Design, Coding & AI — Online
Learn AI, Data Science & Business — Earn Certificates That Get You Hired
Overview
Google, IBM & Meta Certificates – 40% Off
One Coursera Plus subscription covers most Professional Certificates on Coursera.
Unlock All Certificates
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