Look up in adf

Question

Hi, What is the difference between data flow look up transformation and normal look up transformation.. Any screen appreciated

Answer 1

Hi Vineet S,

Thanks for reaching out to Microsoft Q&A.

The key differences between the lookup transformation in Azure Data Factory (ADF) mapping data flows and a normal lookup transformation are:

1. Join Type: The lookup transformation in adf mapping data flows is similar to a left outer join, where all rows from the primary stream will exist in the output stream with additional columns from the lookup stream. This is different from a regular sql join, which can have different join types (inner, left, right, full).
2. Handling Multiple Matches: In the adf lookup transformation, you can specify how to handle multiple matches - either take the first, last, or any match. This is not a common feature in a regular lookup.
3. Broadcast Optimization: The adf lookup transformation allows you to optimize performance by broadcasting one or both data streams to the worker nodes, if the data fits in memory. This is a unique optimization feature not found in a regular lookup.
4. Cached Lookup: The adf lookup transformation supports a cached lookup, where you can cache the lookup data and reuse it across multiple lookups, improving performance. This is a specialized use case not typically found in a regular lookup.
5. Syntax and Configuration: The syntax and configuration options for the adf lookup transformation are specific to the data flow framework, with parameters like multiple, pickup, broadcast etc. This is different from how a regular lookup would be configured.

to sum up, the lookup transformation is tailored for the data flow paradigm, with specialized features around join handling, performance optimization, and caching that go beyond a standard lookup operation. This makes it a more powerful and flexible transformation compared to a regular lookup, but also requires understanding its unique configuration options.

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