AWS AmazonS3 documentation change
Summary
Fixed broken URLs by adding double slashes in documentation links
Security assessment
The changes only correct URL formatting (e.g., changing '/what-is' to '//what-is') without altering security content. The existing security statement about S3 Block Public Access remains unchanged. No vulnerability fixes or security enhancements were introduced.
Diff
diff --git a/AmazonS3/latest/userguide/s3-tables.md b/AmazonS3/latest/userguide/s3-tables.md index 546cf39cd..21a54a910 100644 --- a//AmazonS3/latest/userguide/s3-tables.md +++ b//AmazonS3/latest/userguide/s3-tables.md @@ -52 +52 @@ S3 table buckets are specifically designed for tables. Table buckets provide hig -Tables in your table buckets are stored in [Apache Iceberg](https://aws.amazon.com/what-is/apache-iceberg/) format. You can query these tables using standard SQL in query engines that support Iceberg. Iceberg has a variety of features to optimize query performance, including schema evolution and partition evolution. +Tables in your table buckets are stored in [Apache Iceberg](https://aws.amazon.com//what-is/apache-iceberg/) format. You can query these tables using standard SQL in query engines that support Iceberg. Iceberg has a variety of features to optimize query performance, including schema evolution and partition evolution. @@ -64 +64 @@ To optimize your tables for querying, S3 continuously performs automatic mainten -You can manage access for both table buckets and individual tables with AWS Identity and Access Management (IAM) and [Service Control Policies](https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scps.html) in AWS Organizations. S3 Tables uses a different service namespace than Amazon S3: the _s3tables_ namespace. Therefore, you can design policies specifically for the S3 Tables service and its resources. You can design policies to grant access to individual tables, all tables within a table namespace, or entire table buckets. All Amazon S3 Block Public Access settings are always enabled for table buckets and cannot be disabled. +You can manage access for both table buckets and individual tables with AWS Identity and Access Management (IAM) and [Service Control Policies](https://docs.aws.amazon.com//organizations/latest/userguide/orgs_manage_policies_scps.html) in AWS Organizations. S3 Tables uses a different service namespace than Amazon S3: the _s3tables_ namespace. Therefore, you can design policies specifically for the S3 Tables service and its resources. You can design policies to grant access to individual tables, all tables within a table namespace, or entire table buckets. All Amazon S3 Block Public Access settings are always enabled for table buckets and cannot be disabled. @@ -75 +75 @@ You can use the following AWS services with S3 Tables to support your specific a - * [**Amazon Athena**](https://docs.aws.amazon.com/athena/latest/ug/what-is.html) – Athena is an interactive query service that you can use to analyze data directly in Amazon S3 by using standard SQL. You can also use Athena to interactively run data analytics by using Apache Spark without having to plan for, configure, or manage resources. When you run Apache Spark applications on Athena, you submit Spark code for processing and receive the results directly. + * [**Amazon Athena**](https://docs.aws.amazon.com//athena/latest/ug/what-is.html) – Athena is an interactive query service that you can use to analyze data directly in Amazon S3 by using standard SQL. You can also use Athena to interactively run data analytics by using Apache Spark without having to plan for, configure, or manage resources. When you run Apache Spark applications on Athena, you submit Spark code for processing and receive the results directly. @@ -77 +77 @@ You can use the following AWS services with S3 Tables to support your specific a - * [**AWS Glue**](https://docs.aws.amazon.com/glue/latest/dg/what-is-glue.html) – AWS Glue is a serverless data-integration service that allows you to discover, prepare, move, and integrate data from multiple sources. You can use AWS Glue for analytics, machine learning (ML), and application development. AWS Glue also includes additional productivity and data-operations tooling for authoring, running jobs, and implementing business workflows. + * [**AWS Glue**](https://docs.aws.amazon.com//glue/latest/dg/what-is-glue.html) – AWS Glue is a serverless data-integration service that allows you to discover, prepare, move, and integrate data from multiple sources. You can use AWS Glue for analytics, machine learning (ML), and application development. AWS Glue also includes additional productivity and data-operations tooling for authoring, running jobs, and implementing business workflows. @@ -79 +79 @@ You can use the following AWS services with S3 Tables to support your specific a - * [**Amazon EMR**](https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-what-is-emr.html) – Amazon EMR is a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark, on AWS to process and analyze vast amounts of data. + * [**Amazon EMR**](https://docs.aws.amazon.com//emr/latest/ManagementGuide/emr-what-is-emr.html) – Amazon EMR is a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark, on AWS to process and analyze vast amounts of data. @@ -81 +81 @@ You can use the following AWS services with S3 Tables to support your specific a - * [**Amazon Redshift**](https://docs.aws.amazon.com/redshift/latest/mgmt/welcome.html) – Amazon Redshift is a petabyte-scale data warehouse service in the cloud. You can use Amazon Redshift Serverless to access and analyze data without all of the configurations of a provisioned data warehouse. Resources are automatically provisioned and data warehouse capacity is intelligently scaled to deliver fast performance for even the most demanding and unpredictable workloads. You don't incur charges when the data warehouse is idle, so you only pay for what you use. You can load data and start querying right away in the Amazon Redshift query editor v2 or in your favorite business intelligence (BI) tool. + * [**Amazon Redshift**](https://docs.aws.amazon.com//redshift/latest/mgmt/welcome.html) – Amazon Redshift is a petabyte-scale data warehouse service in the cloud. You can use Amazon Redshift Serverless to access and analyze data without all of the configurations of a provisioned data warehouse. Resources are automatically provisioned and data warehouse capacity is intelligently scaled to deliver fast performance for even the most demanding and unpredictable workloads. You don't incur charges when the data warehouse is idle, so you only pay for what you use. You can load data and start querying right away in the Amazon Redshift query editor v2 or in your favorite business intelligence (BI) tool. @@ -83 +83 @@ You can use the following AWS services with S3 Tables to support your specific a - * [**Quick Suite**](https://docs.aws.amazon.com/quicksight/latest/user/welcome.html) – Quick Suite is a business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data. Quick Suite seamlessly discovers AWS data sources and delivers fast and responsive query performance by using the Quick Suite Super-fast, Parallel, In-Memory, Calculation Engine (SPICE). + * [**Quick Suite**](https://docs.aws.amazon.com//quicksight/latest/user/welcome.html) – Quick Suite is a business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data. Quick Suite seamlessly discovers AWS data sources and delivers fast and responsive query performance by using the Quick Suite Super-fast, Parallel, In-Memory, Calculation Engine (SPICE). @@ -85 +85 @@ You can use the following AWS services with S3 Tables to support your specific a - * [**AWS Lake Formation**](https://docs.aws.amazon.com/lake-formation/latest/dg/what-is-lake-formation.html.html) – Lake Formation is a managed service that streamlines the process to set up, secure, and manage your data lakes. Lake Formation helps you discover your data sources and then catalog, cleanse, and transform the data. With Lake Formation, you can manage fine-grained access control for your data lake data on Amazon S3 and its metadata in AWS Glue Data Catalog. + * [**AWS Lake Formation**](https://docs.aws.amazon.com//lake-formation/latest/dg/what-is-lake-formation.html.html) – Lake Formation is a managed service that streamlines the process to set up, secure, and manage your data lakes. Lake Formation helps you discover your data sources and then catalog, cleanse, and transform the data. With Lake Formation, you can manage fine-grained access control for your data lake data on Amazon S3 and its metadata in AWS Glue Data Catalog.