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INTO, insert the first occurrence of a B-tuple into "B" saving the written ID likewise and finally insert the C-tuple into "C". My initial idea was to insert from the "A" data into table "A" only the first occurrence of a A-tuple saving the written ID by RETURNING. IE Integration Runtime configuration, Copy data settings I need to be setting for more tuning - I have read this.

Lastly are there any settings that I am missing that I can improve that I am not looking at.

With Attempt 2 - the Copy Activity to Parquet is not that bad but why do delta tables still have an issue if the parquet files are suppose to be more efficient? Currently they are not partitioned so do they need to be to perform tune the querying? New to Delta development so not understanding that even 190K parquet files dont really solve the performance if they are in as single container.

Is there something similar to an Databricks Autoloader where you can merge the files as they arrive as in readStream and writeStream and how to tell if the DIU will be cost effective?

With the Attempt 1 I am able to resolve my performance aggregation pipeline but the overhead to merge these files defeats the purpose of being able to aggregate the stream files.

Settings: As is - AutoResolve Standard Integration Runtime

Sink1: None Copy Behavior, ADLS Gen2, parquet

AutoResolve Standard Integration RuntimeĪttempt 2: Creating Parquet files to use as a delta table - but still too many small files issue for reading Settings: 100 DIU, parallelism seems to degrade it. Sink1: Merge Copy Behavior, ADLS Gen2, gzip with fastest compression level Very small files with not a lot of sub objects - maybe 4-5 the most. Because of client restrictions we are utilizing Azure Data Factory to ingest these streams of data that come from telemetry system that cannot combine these files into one. I am using the same Data Set to Copy Data into Azure SQL and Azure Data Lake Storage Gen2. Enavuio Asks: Azure Data Factory Performance tuning Copy Activity to SQL vs Azure Data Lake Gen2