Dynamic task mapping

Q: How deeply does Data Pipelines with Apache Airflow, Second Edition cover dynamic task mapping?

Explains the runtime model, partial operator syntax, Taskflow API, TaskGroups, XCom-based outputs, and UI inspection.

As explained in Data Pipelines with Apache Airflow, Second Edition

Dynamic task mapping is an Apache Airflow feature that creates task instances at runtime from iterable input values for a DAG run.

Dynamic task mapping lets an Apache Airflow DAG create task instances at runtime from iterable values produced during a DAG run. It suits pipelines whose workload changes, such as fetching a variable number of daily movie reviews. Instead of processing every review in one task, Airflow can create one mapped instance per review, improving atomicity and enabling independent retries and parallel processing. section 12.1.8 section 12.5

Movie-review processing

A fetch_ratings task requests /reviews/latest and returns the reviews. A mapped print_rating task expands over that output, printing each movie and rating separately. The same pattern can be written with the Taskflow API as print_rating.expand(rating=fetch_ratings()), or wrapped in a mapped TaskGroup when each review needs a small workflow.

How Data Pipelines with Apache Airflow, Second Edition covers it

Cover of Data Pipelines with Apache Airflow, Second Edition

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Related concepts

directed acyclic graphaddresses · A directed acyclic graph is a graph with directed edges and no directed cycles.
partial applicationhas part · Partial application is the creation of a new function by binding some arguments of an existing function while leaving the remaining arguments to be supplied later.
expand()has part · expand() is an Airflow task-mapping method that specifies the iterable values for which separate mapped task instances are created.
XComuses · XCom is an Apache Airflow mechanism for storing and exchanging small task results through the Airflow metastore.
task mappingkind of · Task mapping is the association of each task or sequence element with a function or processing resource.
parallelismproduces · Parallelism is the concurrent execution of multiple computational operations, often across multiple processing resources.

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