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Use Amazon Athena with Spark SQL for your open-source transactional table formats

AWS Big Data

These formats enable ACID (atomicity, consistency, isolation, durability) transactions, upserts, and deletes, and advanced features such as time travel and snapshots that were previously only available in data warehouses. It will never remove files that are still required by a non-expired snapshot.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

An in-place migration can be performed in either of two ways: Using add_files : This procedure adds existing data files to an existing Iceberg table with a new snapshot that includes the files. Unlike migrate or snapshot, add_files can import files from a specific partition or partitions and doesn’t create a new Iceberg table.

Data Lake 105
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Apache Iceberg optimization: Solving the small files problem in Amazon EMR

AWS Big Data

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 105
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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. At the top of the hierarchy is the metadata file, which stores information about the table’s schema, partition information, and snapshots. Choose Advanced options.

Data Lake 120
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Interact with Apache Iceberg tables using Amazon Athena and cross account fine-grained permissions using AWS Lake Formation

AWS Big Data

The Iceberg table keeps track of the snapshots. consumer_iceberg$snapshots" limit 10; We can observe that we have generated multiple snapshots. Note down one of the committed_at values to use in the next steps (for this example, 2023-01-29 21:35:02.176 UTC ). Use time travel to find the table snapshot.

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Amazon OpenSearch Service H1 2023 in review

AWS Big Data

Since its release in January 2021, the OpenSearch project has released 14 versions through June 2023. In this post, we provide a review of all the exciting features releases in OpenSearch Service in the first half of 2023. In July 2023, we previewed support for a third collection type: vector search.