Fan-in
Fan-in is a pattern in which outputs from multiple concurrent or upstream sources converge into a single stream, task, or operation.
Distributed Machine Learning Patterns
A workflow pattern that combines results from multiple upstream processing branches before downstream processing.
- How it is used
- Combines outputs from multiple model-serving branches in complex machine-learning workflows.
- How deep it goes
- Defines fan-in through an aggregation workflow and discusses independence, ordering, and ensemble-training limitations.
- Examples
- Uses YouTube-8M entity tagging with selected models whose serving predictions are aggregated.
- What you can do after
- Apply it to join independent, order-independent branch results in a machine-learning workflow.
Read how Distributed Machine Learning Patterns explains fan-in →
Learn Concurrent Programming with Go
A fan-in pattern merges values from multiple concurrent sources into a single stream.
- How it is used
- Connects multiple concurrent pipeline outputs to one downstream input while preserving independently pluggable stages.
- How deep it goes
- Explains fixed-source select fan-in and dynamic-source forwarding, including cancellation and coordinated channel closure.
- Examples
- Uses an accounting stream and a web-page pipeline with twenty downloaders feeding extractWords through FanIn.
- What you can do after
- Build it from scratch with forwarding goroutines, a shared output channel, cancellation, and WaitGroup-based closure.
Read how Learn Concurrent Programming with Go explains fan-in →
Related concepts
- channeluses · A channel is a typed Go communication and synchronization mechanism through which goroutines send and receive values.
- data aggregationuses · Data aggregation is the combination of multiple values, records, observations, or results into a consolidated or summarized output.
- machine learning workflowuses · A machine learning workflow is an organized sequence of activities for formulating, developing, evaluating, deploying, operating, and maintaining a machine learning system.
- dependencykind of · A software dependency is a component, resource, or prerequisite on which another software component or operation relies to function or proceed.
- select statementimplemented by · A select statement is a language construct that retrieves selected data or chooses among alternative operations or cases according to the language's rules.
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