How do workflow orchestration tools handle dependencies between tasks in a data pipeline?
- By assigning tasks to different worker nodes
- By defining dependencies explicitly in DAG configurations
- By executing all tasks simultaneously
- By randomizing task execution order
Workflow orchestration tools handle dependencies between tasks in a data pipeline by allowing users to define dependencies explicitly in DAG (Directed Acyclic Graph) configurations. Users specify the relationships between tasks, such as task A depending on the completion of task B, within the DAG definition. The orchestration tool then ensures that tasks are executed in the correct order based on these dependencies, optimizing the flow of data through the pipeline and ensuring the integrity of data processing operations.
Loading...
Related Quiz
- ________ is a distributed computing model where a large problem is divided into smaller tasks, each solved by a separate node.
- Which data cleansing method involves correcting misspellings, typos, and grammatical errors in textual data?
- The process of optimizing the performance of SQL queries by creating indexes, rearranging tables, and tuning database parameters is known as ________.
- In the context of data loading, what does "incremental loading" mean?
- What are some common technologies used for stream processing in real-time data processing systems?