Exam AWS Certified Data Analytics - Specialty topic 1 question 131 discussion

There are three ways to resolve this problem: Add more prefixes to the S3 bucket. Reduce the number of Amazon S3 requests. Increase the EMR File System (EMRFS) retry limit.

A - CORRECT, limit of S3 are defined on a per-prefix basis. ( https://docs.aws.amazon.com/AmazonS3/latest/userguide/optimizing-performance.html , "3,500 PUT/COPY/POST/DELETE or 5,500 GET/HEAD requests per second per partitioned prefix" ). If you "add" more prefixes, meaning you change the logic to make tasks write to "less shared" prefixes, then the limit is less likely to be hit. B - WRONG, limit of S3 are defined on a per-prefix basis. If you reduce the prefixes, then the limit is more likely to be hit. C - CORRECT, EMRFS uses an exponential backoff strategy to retry requests to Amazon S3 with default value 15. To increase the retry limit, change the value of fs.s3.maxRetries parameter. ( https://aws.amazon.com/premiumsupport/knowledge-center/emr-s3-503-slow-down/ ) D - WRONG, dynamic partition pruning decreases the number of requests to S3, because it helps select which prefixes to read E - WRONG, increasing the partitions increases the number of Spark tasks, hence the number of write requests to S3

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A C https://aws.amazon.com/premiumsupport/knowledge-center/emr-s3-503-slow-down/ This error occurs when you exceed the Amazon Simple Storage Service (Amazon S3) request rate. The request rate is 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per prefix in a bucket. There are three ways to resolve this problem: Add more prefixes to the S3 bucket. Reduce the number of Amazon S3 requests. Increase the EMR File System (EMRFS) retry limit.