slilichenko / streaming-dataflow-examples

Streaming Dataflow Samples

Beam Pipelines - Streaming Analytics Techniques

This project is a demo for several Beam techniques to do streaming analytics.

Running the demo

1. Create a GCP project
2. Create a file in terraform directory named terraform.tfvars with the following content:

   project_id = "<GCP Project Id>"
   

   There are additional Terraform variables that can be overwritten; see variables.tf for details.
3. Run the following commands:

   export PROJECT_ID=<project-id>
   export GCP_REGION=us-central1
   export BIGQUERY_REGION=us-central1

4. Create BigQuery tables, Pub/Sub topics and subscriptions, and GCS buckets by running this script:

   source ./setup-env.sh

5. Start event generation process:

   ./start-event-generation.sh

6. Start the event processing pipeline:

   (cd pipeline; ./run-streaming-pipeline.sh)

7. Optionally, start the pipeline which will ingest the findings sent as pubsub messages into BigQuery:

   ./start-findings-to-bigquery-pipeline.sh

Cleaning up

1. Shutdown the pipelines via GCP console (TODO: add scripts)
2. Run this command:

   cd terraform; terraform destroy

Alternatively, delete the project you created.

Disclaimer

The techniques and code contained here are not supported by Google and is provided as-is (under Apache license). This repo provides some options you can investigate, evaluate and employ if you choose to.