Discrepancy in ADF Pipeline Duration Despite Optimizations

Question

We are encountering a performance issue with an Azure Data Factory (ADF) pipeline used to sync data between Azure SQL and an On-premise SQL Server. Despite optimizations, the pipeline shows discrepancies in reported durations for a specific Copy Data activity, and additional time is being consumed without clear attribution.

Observed Behavior:

• The Copy Data activity reports a Duration of 7 seconds, but:

  - **Queue Time** and **Transfer Time** account for only **4 seconds**.
  
        - An unexplained **3 seconds** remains unaccounted for.
  
           - The overall pipeline execution time exceeds the **7 seconds** reported for the Copy Data activity.
  

• Steps Taken:
  • Increased Data Integration Units (DIU):
    • Raised DIUs from auto to 356 for the Copy Data activity.
  • Enabled Concurrency:
    • Configured pipeline concurrency settings to 2 to parallelize execution.
    • Despite these optimizations, additional time remains unaccounted for in the pipeline duration.

Pipeline Details:

• 

• Integration Runtime: Self-Hosted
• Source: Azure SQL Database
• Sink: On-Premise SQL Server
• Region: Both Source and Sink are in same region

Impact:

• The unexplained time affects performance monitoring and SLA evaluation.
• Attempts to optimize the pipeline using DIUs and concurrency have not yielded the expected reduction in overall execution time.

Request:

• Investigate the root cause of the unexplained additional time in the pipeline and activity durations.
• Suggest any further optimizations to reduce pipeline execution time.
• Clarify how the activity duration and pipeline duration metrics are calculated to ensure accurate performance monitoring.

Answer 1

Hi @Sneha Agashe
Greetings! and welcome to the Q&A platform. Thanks for your question.

The discrepancy in the reported duration of your Azure Data Factory (ADF) pipeline, particularly in the Copy Data activity, can arise from several factors. Here are some insights and suggestions based on the context provided:

Investigate the root cause of the unexplained additional time in the pipeline and activity durations.

The unexplained 3 seconds could be attributed to:

Initialization Overhead - Time taken to initialize the integration runtime or establish connections to the source and sink.

Post-Transfer Processing - Any additional processing that occurs after the data transfer, such as committing transactions or executing post-copy scripts.

Concurrency and Resource Contention - Even with increased DIUs and concurrency settings, if there are resource constraints or contention, it could lead to additional delays.

Suggest any further optimizations to reduce pipeline execution time.

Review Integration Runtime Capacity: Ensure that your self-hosted integration runtime has sufficient resources and is not under heavy load. Scaling up or out may help.

Pipeline Optimization - Reduce unnecessary dependencies between activities. Adjust concurrency settings to maximize resource utilization. Identify and remove any unnecessary activities.

Additionally, you can follow this documentation: Troubleshoot copy activity performance

Clarify how the activity duration and pipeline duration metrics are calculated to ensure accurate performance monitoring.

Activity Duration - This is calculated based on the start and end time of the activity execution.

Pipeline Duration - This includes the total time taken for all activities in the pipeline, including any waiting time, initialization, and execution time.

For more details refer to this: To improve the performance of the Copy activity

Hope this helps. Do let us know if you have any further queries.

Answer 2

Hello @Sneha Agashe

I suggest checking the logs for the pipeline run to see if there are any errors or warnings that might explain the unaccounted time.

You can also try enabling diagnostic logging for the pipeline to get more detailed information about the pipeline run. Regarding the activity duration and pipeline duration metrics, the activity duration is the time it takes for the activity to complete, while the pipeline duration is the time it takes for the entire pipeline to complete, including all activities.

The pipeline duration includes any time spent waiting in the queue, transferring data, and executing activities.

As for further optimizations, you can try optimizing the source and sink databases to improve data transfer speeds. You can also try using a different integration runtime, such as Azure Integration Runtime, to see if that improves performance.

Additionally, you can try breaking up the pipeline into smaller, more manageable chunks to improve concurrency and reduce overall execution time.

I hope these steps help you further in your journey.