Databricks on Google Cloud: Cloud Architecture and System Integration

Summary

Learn how Databricks fits into the Google Cloud ecosystem through integrations with first-party services.

Description

While the Databricks Unified Analytics Platform provides a broad range of functionality to many members of data teams, it is through integrations with other services that most cloud-native applications will achieve results desired by customers. This course is a series of demos designed to help students understand the portions of cloud workloads appropriate for Databricks. Within these demos, we'll highlight integrations with first-party services in Google Cloud to build scalable and secure applications.

Learning objectives

  • Describe where Databricks fits into a cloud-based architecture on Google Cloud.

  • Authenticate to Google Cloud resources with service account credentials.

  • Read and write data to Cloud Storage using Databricks secrets.

  • Mount a GCS bucket to DBFS using cluster-wide service accounts.

  • Configure a cluster to read and write data to BigQuery using credentials in DBFS.

Prerequisites

  • Familiarity with the Databricks on Google Cloud workspace

  • Beginning knowledge of Spark programming (reading/writing data, batch and streaming jobs, transformations and actions)

  • Beginning-level experience using Python or Scala to perform basic control flow operations.

  • Familiarity with navigation and resource configuration in the Databricks on Google Cloud Console.

Learning path

  • This course is part of the Platform Administrator learning path.

Proof of completion

  • Upon 80% completion of this course, you will receive a proof of completion.