The Amazon S3 Tables Catalog for Apache Iceberg is an open-source library that bridges S3 Tables operations to engines like Apache Spark, when used with the Apache Iceberg Open Table Format.
This library can:
- Translate Apache Iceberg operations such as table discovery, metadata reads, and updates
- Add and removes tables in Amazon S3 Tables
Amazon S3 Tables are built for storing tabular data, such as daily purchase transactions, streaming sensor data, or ad impressions. Tabular data represents data in columns and rows, like in a database table. Tabular data is most commonly stored in the Apache Parquet format.
The tabular data in Amazon S3 Tables is stored in a new S3 bucket type: a table bucket, which stores tables as subresources. S3 Tables has built-in support for tables in the Apache Iceberg format. Using standard SQL statements, you can query your tables with query engines that support Apache Iceberg, such as Amazon Athena, Amazon Redshift, and Apache Spark.
Amazon S3 Tables Catalog for Apache Iceberg is generally available. We're always interested in feedback on features, performance, and compatibility. Please send feedback by opening a GitHub issue.
If you discover a potential security issue in this project we ask that you notify Amazon Web Services (AWS) Security via our vulnerability reporting page. Please do not create a public GitHub issue.
To get started with Amazon S3 Tables, see Tutorial: Getting started with S3 Tables in the Amazon S3 User Guide.
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<catalog_name> is your Iceberg Spark session catalog name. Replace it with the name of your catalog, and remember to change the references throughout all configurations that are associated with this catalog. In your code, you should then refer to your Iceberg tables with the fully qualified table name, including the Spark session catalog name, as follows: <catalog_name>.<database_name>.<table_name>.
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<catalog_name>.warehouse points to the Amazon S3 Tables path
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<catalog_name>.catalog-impl = "software.amazon.s3tables.iceberg.S3TablesCatalog" This key is required to point to an implementation class for any custom catalog implementation.
Add the lines below to your pom.xml:
<dependency>
<groupId>software.amazon.awssdk</groupId>
<artifactId>s3tables</artifactId>
<version>2.29.26</version>
</dependency>
<dependency>
<groupId>software.amazon.s3tables</groupId>
<artifactId>s3-tables-catalog-for-iceberg</artifactId>
<version>0.1.4</version>
</dependency>
Or if you using a BOM just add a dependency on the s3 tables sdk:
<dependencyManagement>
<dependencies>
<dependency>
<groupId>software.amazon.awssdk</groupId>
<artifactId>bom</artifactId>
<version>2.29.26</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
Or for Gradle:
dependencies {
implementation 'software.amazon.awssdk:s3tables:2.29.26'
implementation 'software.amazon.s3tables:s3-tables-catalog-for-iceberg:0.1.4'
}
And finally start a spark session:
spark = SparkSession.builder()
.config("spark.sql.catalog.<catalog_name>", "org.apache.iceberg.spark.SparkCatalog")
.config("spark.sql.catalog.<catalog_name>.catalog-impl","software.amazon.s3tables.iceberg.S3TablesCatalog")
.config("spark.sql.catalog.<catalog_name>.warehouse", <TABLE_BUCKET_ARN>)
.getOrCreate();
We welcome contributions to Amazon S3 Tables Catalog for Apache Iceberg! Please see the contributing guidelines for more information on how to report bugs, build from source code, or submit pull requests.
If you discover a potential security issue in this project we ask that you notify Amazon Web Services (AWS) Security via our vulnerability reporting page. Please do not create a public GitHub issue.
This project is licensed under the Apache-2.0 License.