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  • GET STARTED
    • Core Concepts
      • Core Components
      • Deployment Models
      • Entities Overview
      • Upsolver Timeline
      • Schema Detection and Evolution
    • Pipeline Basics
    • Understanding Sync and Non-Sync Jobs
  • DATA
    • Optimization Processes for Iceberg Tables in Upsolver
    • Column Case Sensitivity
    • Column Transformations
    • Compaction Process
    • Expectations
    • Field Name Encoding
    • Iceberg Adaptive Clustering
    • Schema Evolution
      • Iceberg Schema Evolution
      • Snowflake Schema Evolution
      • Redshift Schema Evolution
    • System Columns
    • Working with Date Patterns
  • JOBS
    • Ingest Data Using CDC
      • Performing Snapshots
      • MySQL Binlog Retention
      • PostgreSQL Partitioned Tables
      • CDC Known Limitations
    • Transformation
      • Flattening Arrays
      • Working with Arrays
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  1. JOBS

Transformation

Last updated 11 months ago

Transformation jobs use INSERT and MERGE statements, enabling you to insert and update the data in your table. Using a MERGE statement in your jobs provides the additional ability to delete data if specified conditions are met.

In this section, learn how to work with arrays in transformation jobs:

Flattening Arrays
Working with Arrays