BigData / Apache StreamPark Interview questions
What is the difference between Upload Jar and Flink SQL job development in StreamPark?
These are the two ways to define what a job actually runs, and they suit different kinds of work.
| Upload Jar | Flink SQL |
| You bring a pre-built jar (own build or via Project Management) | You write SQL directly in the console's Monaco editor |
| Full DataStream API flexibility, custom logic, ML/complex processing | Fast for standard filter/join/aggregate style ETL |
| Dependency management is the developer's responsibility | Connector dependencies are declared and resolved by StreamPark |
| Requires a Java/Scala build step | No separate build step required |
Teams commonly use both: SQL for straightforward pipelines that a data engineer can write and read at a glance, and Upload Jar for jobs whose logic genuinely needs general-purpose code.
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