AWS emr documentation change
Summary
Minor editorial changes including grammatical simplifications ('you can persist' to 'persist'), replacing 'see' with 'refer to' in documentation links, and removing redundant pronouns in instructions
Security assessment
Changes are purely editorial/grammatical with no mention of security vulnerabilities, access controls, encryption, or authentication mechanisms. The cross-account access section retains the same security guidance without modifications to security implications.
Diff
diff --git a/emr/latest/EMR-Serverless-UserGuide/metastore-config.md b/emr/latest/EMR-Serverless-UserGuide/metastore-config.md index b71de3be0..a26e6aabd 100644 --- a//emr/latest/EMR-Serverless-UserGuide/metastore-config.md +++ b//emr/latest/EMR-Serverless-UserGuide/metastore-config.md @@ -9 +9 @@ Using the AWS Glue Data Catalog as a metastore -A _Hive metastore_ is a centralized location that stores structural information about your tables, including schemas, partition names, and data types. With EMR Serverless, you can persist this table metadata in a metastore that has access to your jobs. +A _Hive metastore_ is a centralized location that stores structural information about your tables, including schemas, partition names, and data types. With EMR Serverless, persist this table metadata in a metastore that has access to your jobs. @@ -22 +22 @@ You have two options for a Hive metastore: -You can configure your Spark and Hive jobs to use the AWS Glue Data Catalog as its metastore. We recommend this configuration when you require a persistent metastore or a metastore shared by different applications, services, or AWS accounts. For more information about the Data Catalog, see [Populating the AWS Glue Data Catalog](https://docs.aws.amazon.com/glue/latest/dg/populate-data-catalog.html). For information about AWS Glue pricing, see [AWS Glue pricing](https://aws.amazon.com/glue/pricing). +You can configure your Spark and Hive jobs to use the AWS Glue Data Catalog as its metastore. We recommend this configuration when you require a persistent metastore or a metastore shared by different applications, services, or AWS accounts. For more information about the Data Catalog, refer to [Populating the AWS Glue Data Catalog](https://docs.aws.amazon.com/glue/latest/dg/populate-data-catalog.html). For information about AWS Glue pricing, refer to [AWS Glue pricing](https://aws.amazon.com/glue/pricing). @@ -35 +35 @@ When you use EMR Studio to run your jobs with EMR Serverless Spark applications, -When you use SDKs or AWS CLI, you can set the `spark.hadoop.hive.metastore.client.factory.class` configuration to `com.amazonaws.glue.catalog.metastore.AWSGlueDataCatalogHiveClientFactory` in the `sparkSubmit` parameters of your job run. The following example shows how to configure the Data Catalog with the AWS CLI. +When you use SDKs or AWS CLI, set the `spark.hadoop.hive.metastore.client.factory.class` configuration to `com.amazonaws.glue.catalog.metastore.AWSGlueDataCatalogHiveClientFactory` in the `sparkSubmit` parameters of your job run. The following example shows how to configure the Data Catalog with the AWS CLI. @@ -78 +78 @@ To access the Hive metastore tables, add the required AWS Glue policies outlined -To set up cross-account access for EMR Serverless, you must first sign in to the following AWS accounts: +To set up cross-account access for EMR Serverless, first sign in to the following AWS accounts: @@ -213 +213 @@ Set the `hive.metastore.glue.catalogid` property in the `hive-site` classificati -You can add auxiliary JARs with `ADD JAR` in your Hive scripts. For additional considerations, see [Considerations when using AWS Glue Data Catalog](https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hive-metastore-glue.html#emr-hive-glue-considerations-hive). +You can add auxiliary JARs with `ADD JAR` in your Hive scripts. For additional considerations, refer to [Considerations when using AWS Glue Data Catalog](https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hive-metastore-glue.html#emr-hive-glue-considerations-hive).