AWS emr documentation change
Summary
Updated Spark configuration parameter's credentials resolver class path
Security assessment
Corrects a package path for credential resolution but does not explicitly address a security vulnerability. The change ensures proper Lake Formation integration, which has security implications, but no evidence of a specific security issue being fixed.
Diff
diff --git a/emr/latest/EMR-Serverless-UserGuide/lake-formation-unfiltered-access.md b/emr/latest/EMR-Serverless-UserGuide/lake-formation-unfiltered-access.md index 74389e6de..984184e4b 100644 --- a//emr/latest/EMR-Serverless-UserGuide/lake-formation-unfiltered-access.md +++ b//emr/latest/EMR-Serverless-UserGuide/lake-formation-unfiltered-access.md @@ -115 +115 @@ Iceberg - * `spark.hadoop.fs.s3.credentialsResolverClass=com.amazonaws.glue.accesscontrol.s3a.AWSLakeFormationCredentialResolver`: Configure EMR Filesystem (EMRFS) to use AWS Lake Formation S3 credentials for Lake Formation registered tables. If the table is not registered, use the job's runtime role credentials. + * `spark.hadoop.fs.s3.credentialsResolverClass=com.amazonaws.glue.accesscontrol.AWSLakeFormationCredentialResolver`: Configure EMR Filesystem (EMRFS) to use AWS Lake Formation S3 credentials for Lake Formation registered tables. If the table is not registered, use the job's runtime role credentials.