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https://issues.apache.org/jira/browse/BAHIR-213?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16893718#comment-16893718
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Steve Loughran commented on BAHIR-213:
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I've thought about doing this for a while. Note that the event queue is itself
inconsistent; you still need to scan for changes sporadically.
The other cloud infras provide similar event queues (at least Azure does); be
good to design this to be somewhat independent.
Testing will be fun.
> Faster S3 file Source for Structured Streaming with SQS
> -------------------------------------------------------
>
> Key: BAHIR-213
> URL: https://issues.apache.org/jira/browse/BAHIR-213
> Project: Bahir
> Issue Type: New Feature
> Components: Spark Structured Streaming Connectors
> Affects Versions: Spark-2.3.0, Spark-2.4.0
> Reporter: Abhishek Dixit
> Priority: Major
>
> Using FileStreamSource to read files from a S3 bucket has problems both in
> terms of costs and latency:
> * *Latency:* Listing all the files in S3 buckets every microbatch can be
> both slow and resource intensive.
> * *Costs:* Making List API requests to S3 every microbatch can be costly.
> The solution is to use Amazon Simple Queue Service (SQS) which lets you find
> new files written to S3 bucket without the need to list all the files every
> microbatch.
> S3 buckets can be configured to send notification to an Amazon SQS Queue on
> Object Create / Object Delete events. For details see AWS documentation here
> [Configuring S3 Event
> Notifications|https://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html]
>
> Spark can leverage this to find new files written to S3 bucket by reading
> notifications from SQS queue instead of listing files every microbatch.
> I hope to contribute changes proposed in [this pull
> request|https://github.com/apache/spark/pull/24934] to Apache Bahir as
> suggested by @[gaborgsomogyi|https://github.com/gaborgsomogyi]
> [here|https://github.com/apache/spark/pull/24934#issuecomment-511389130]
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