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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2019/06/21 13:13:00 UTC
[jira] [Assigned] (SPARK-28124) Faster S3 file source with SQS
[ https://issues.apache.org/jira/browse/SPARK-28124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-28124:
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Assignee: (was: Apache Spark)
> Faster S3 file source with SQS
> ------------------------------
>
> Key: SPARK-28124
> URL: https://issues.apache.org/jira/browse/SPARK-28124
> Project: Spark
> Issue Type: New Feature
> Components: Structured Streaming
> Affects Versions: 2.4.3
> 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.
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