data engineering
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Databricks SQL: Build Idempotent Recovery and Backfill Queries
Databricks SQL: Idempotent Recovery & Backfill Databricks SQL: Build Idempotent Recovery and Backfill Queries This tutorial demonstrates building idempotent recovery and backfill queries within Databricks SQL. We will focus on the mechanics of these operations, using a simplified scenario and progressively complex queries. Idempotent recovery ensures that a query that is executed multiple times produces…
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Databricks SQL: Validate Production Tables before Publication
Databricks SQL: Validate Production Tables Before Publication Databricks SQL: Validate Production Tables Before Publication This tutorial guides you through a crucial data engineering task: validating production tables before publishing them to downstream consumers. We’ll use Databricks SQL to ensure data quality and consistency, building a robust data pipeline. This approach aligns with Data Platform Engineering…
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Databricks Data Platform: Promote Changes across Environments
Databricks Data Platform: Promote Changes Across Environments Databricks Data Platform: Promote Changes Across Environments This tutorial demonstrates how to promote changes across different environments (e.g., Development, Staging, Production) within a Databricks Data Platform. We will focus on using Databricks Repos and Notebooks, along with Delta Live Tables, to streamline this process. This approach aligns with…
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Databricks Data Platform: Plan Backup and Disaster Recovery
Databricks Backup & Disaster Recovery Tutorial Databricks Data Platform: Plan Backup and Disaster Recovery This tutorial guides you through implementing a basic backup and disaster recovery plan for a Databricks workspace. We’ll cover data snapshotting, versioning, and simple recovery scenarios. This setup focuses on a single cluster and Delta Lake tables, suitable for a small…
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Databricks Production: Use Broadcast Joins Appropriately
Databricks Production: Broadcast Joins Databricks Production: Broadcast Joins Appropriately Broadcast joins in Databricks are a powerful optimization technique to speed up joins between a large table (the “reducer”) and a smaller table (the “broadcaster”). They’re especially effective when the smaller table can fit comfortably in the memory of each worker node. This tutorial will guide…
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