databricks-migration-deep-dive（数据块迁移深入探讨）

Databricks Migration Deep Dive

Contents

• Overview
• Prerequisites
• Instructions
• Output
• Error Handling
• Examples
• Resources

Overview

Comprehensive migration strategies for moving to Databricks from Hadoop, Snowflake, Redshift, Synapse, or legacy data warehouses.

Prerequisites

• Access to source and target systems
• Understanding of current data architecture
• Migration timeline and stakeholder alignment

Migration Patterns

Instructions

Step 1: Discovery and Assessment

Inventory all source tables with metadata (size, partitions, dependencies, data classification). Generate prioritized migration plan with wave assignments.

Step 2: Schema Migration

Convert source schemas to Delta Lake compatible types. Handle type conversions (char->string, tinyint->int). Enable auto-optimize on target tables.

Step 3: Data Migration

Batch large tables by partition. Validate row counts and schema match after each table migration.

Step 4: ETL/Pipeline Migration

Convert spark-submit/Oozie jobs to Databricks jobs. Update paths, remove Hive metastore references, adapt for Unity Catalog.

Step 5: Cutover Planning

Execute 6-step cutover: validate -> disable source -> final sync -> enable Databricks -> update apps -> monitor. Each step has rollback procedure.

See detailed implementation for assessment scripts, schema conversion, data migration with batching, ETL conversion, and cutover plan generation.

Output

• Migration assessment with prioritized plan
• Schema migration automated
• Data migration pipeline with validation
• Cutover plan with rollback procedures

Error Handling

Examples

Quick Validation

SELECT 'source' as system, COUNT(*) FROM hive_metastore.db.table
UNION ALL SELECT 'target' as system, COUNT(*) FROM migrated.db.table;

Resources

• Databricks Migration Guide
• Delta Lake Migration
• Unity Catalog Migration

Completion

Provides coverage for Databricks platform migrations.