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File Arrival Trigger - Reduce Listing

ChristianRRL
Valued Contributor II

Hi there, the file arrival trigger seems handy, but I have questions about the performance and cost implications of using it. Per file arrival trigger documentation:

"File arrival triggers do not incur additional costs other than cloud provider costs associated with listing files in the storage location."

This is potentially concerning. For example, let's say we have a data extraction pipeline that on a given year loads 100k .json files to a landing path. If we are using the file arrival trigger to monitor when files arrive (e.g. checks every minute), then this would mean that when there is a new file, all other 100k files would still need to be scanned/listed in order to acquire only the new file, incurring both a cost and performance impact. Worst still, whether there is a new file or not, this file scan/listing is done every minute, so regardless of there being new data we would still be incurring compute costs due to the file listing operation.

I would like some assistance to understand if my above example/assumptions are correct. If so, can I get some help to understand in what context does it make sense to leverage a file arrival trigger? Or else, if my example/assumptions are incorrect, please let me know how so!

1 ACCEPTED SOLUTION

Accepted Solutions

lingareddy_Alva
Honored Contributor II

Hi @ChristianRRL 

Your Assumptions - Partially Correct
You're correct about several key points:

1. File listing overhead: Yes, the trigger does need to list files in the monitored location to detect new arrivals
2. Cloud provider costs: Listing operations do incur costs (though typically minimal per operation)
3. Continuous polling: The trigger checks at regular intervals regardless of whether new files arrive

However, there are some optimizations and considerations that affect the impact:
How File Arrival Triggers Actually Work
Optimization Mechanisms:
1. Incremental Detection: Most implementations use timestamps or other metadata to avoid full scans
2. Efficient Listing: Cloud providers optimize listing operations for performance
3. Batching: Multiple file arrivals within a short window are often batched together

Cost Perspective:
-- Storage listing costs are typically very low (e.g., AWS S3 LIST requests cost $0.0004 per 1,000 requests)
-- For your 100k files example: Even with minute-by-minute checks, the listing cost would be negligible compared to compute costs

When File Arrival Triggers Make Sense
Good Use Cases:
1. Low to Moderate File Volumes (hundreds to low thousands of files)
2. Predictable Arrival Patterns (files arrive regularly but not constantly)
3. Near Real-time Requirements (need to process files within minutes of arrival)
4. Event-driven Architectures (want to trigger downstream processes immediately)

 

 

LR

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1 REPLY 1

lingareddy_Alva
Honored Contributor II

Hi @ChristianRRL 

Your Assumptions - Partially Correct
You're correct about several key points:

1. File listing overhead: Yes, the trigger does need to list files in the monitored location to detect new arrivals
2. Cloud provider costs: Listing operations do incur costs (though typically minimal per operation)
3. Continuous polling: The trigger checks at regular intervals regardless of whether new files arrive

However, there are some optimizations and considerations that affect the impact:
How File Arrival Triggers Actually Work
Optimization Mechanisms:
1. Incremental Detection: Most implementations use timestamps or other metadata to avoid full scans
2. Efficient Listing: Cloud providers optimize listing operations for performance
3. Batching: Multiple file arrivals within a short window are often batched together

Cost Perspective:
-- Storage listing costs are typically very low (e.g., AWS S3 LIST requests cost $0.0004 per 1,000 requests)
-- For your 100k files example: Even with minute-by-minute checks, the listing cost would be negligible compared to compute costs

When File Arrival Triggers Make Sense
Good Use Cases:
1. Low to Moderate File Volumes (hundreds to low thousands of files)
2. Predictable Arrival Patterns (files arrive regularly but not constantly)
3. Near Real-time Requirements (need to process files within minutes of arrival)
4. Event-driven Architectures (want to trigger downstream processes immediately)

 

 

LR

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