Decides which rows a stateful Structured Streaming query writes out at each trigger: append, the default, for finalised rows only; update for rows that changed, which Delta sinks don't support; or complete for the entire result.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains Output mode in context, with comparison tables and the common traps.
Terms in this definition
- Structured Streaming
Spark's engine for near real-time data: you write a batch-like query and it processes new data incrementally, recording progress in a checkpoint with exactly-once guarantees. Auto Loader and streaming tables run on it.
- Azure Functions trigger
Every function is started by exactly one thing. That thing might be a web call over HTTP, a schedule, the arrival of a blob, a message landing in a queue or a change in a database.
- Append
Policy effect in Azure that inserts fields only while a resource is being created or updated; resources that already exist are not corrected by it.
- CRUD
Shorthand for create, read, update and delete, the four basic things you do with data. Data-plane roles in Azure Cosmos DB, for instance, authorise those operations on items.
- Deployment modes
The two ways ARM can deploy: Incremental, the default, creates or updates what the template lists and ignores everything else; Complete also removes resource group contents absent from the template.
Related terms
- Real-time Mode
A Structured Streaming mode in Spark, set with Trigger.RealTime on Fabric Runtime 2.0, where tasks stay running and handle each record on arrival rather than working in microbatches. Its output mode must be update, and its sources and sinks are limited to Kafka-compatible ones or a foreach sink, so files and Delta tables can't be used.