Forum Discussion
Huge Data Volume_490Million records
Hi Folks,
We are trying to pull data from onpremsql to fabriclakehouse which is around 490million records with 24 columns..
I have two options
1. Pipeline - I did this scenario it is taking 8hours
2. Dataflow - Fastcopy.
Need your suggestion on dataflow with fast copy how much time will it takes and how much will be the cost?
Hi Ananth_Bhirappa
It will be difficult to give an exact estimate for how long a Dataflow with Fast Copy would take or its precise cost for your specific scenario. However, let me try to get some insights on the potential benefits and considerations of using Dataflow with Fast Copy:
Performance Improvement: Fast Copy can potentially reduce the ingestion time compared to standard Dataflow or Pipeline operations. In some cases, it has been reported to process billions of rows in minutes rather than hours- Cost Efficiency: Fast Copy generally consumes fewer Capacity Units (CUs) compared to standard Dataflow operations. This can lead to lower costs, especially for large data volumes.
- Limitations: Fast Copy has some restrictions, such as limited support for transformations and specific file formats (.csv and .parquet)
Cost Considerations
The cost for Dataflow Gen2 with Fast Copy is calculated based on the following:
- Standard Compute: 16 CUs per hour
- High Scale Dataflows Compute: 6 CUs per hour
- Data movement: 1.5 CUs per hour
Points to consider :
- Test with a Subset: Before running the full 490 million records, test Fast Copy with a smaller subset to gauge performance and cost.
- Monitor with Fabric Metrics App: Use the Fabric Metrics App to accurately measure CU consumption and duration for your specific scenario.
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
ThanksNilendra
2 Replies
Hi Ananth_Bhirappa
It will be difficult to give an exact estimate for how long a Dataflow with Fast Copy would take or its precise cost for your specific scenario. However, let me try to get some insights on the potential benefits and considerations of using Dataflow with Fast Copy:
Performance Improvement: Fast Copy can potentially reduce the ingestion time compared to standard Dataflow or Pipeline operations. In some cases, it has been reported to process billions of rows in minutes rather than hours- Cost Efficiency: Fast Copy generally consumes fewer Capacity Units (CUs) compared to standard Dataflow operations. This can lead to lower costs, especially for large data volumes.
- Limitations: Fast Copy has some restrictions, such as limited support for transformations and specific file formats (.csv and .parquet)
Cost Considerations
The cost for Dataflow Gen2 with Fast Copy is calculated based on the following:
- Standard Compute: 16 CUs per hour
- High Scale Dataflows Compute: 6 CUs per hour
- Data movement: 1.5 CUs per hour
Points to consider :
- Test with a Subset: Before running the full 490 million records, test Fast Copy with a smaller subset to gauge performance and cost.
- Monitor with Fabric Metrics App: Use the Fabric Metrics App to accurately measure CU consumption and duration for your specific scenario.
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
ThanksNilendra
Hi Ananth_Bhirappa ,
Using Dataflow with Fast Copy in Microsoft Fabric may be more efficient than traditional pipelines. It utilizes the fabric compute engine to significantly reduce the time required for data ingestion and transformation.
For more details, you can refer to below document:
Fast copy in Dataflows Gen2 - Microsoft Fabric | Microsoft Learn
Best Regards,
Adamk KongIf this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
