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

AWS Big Data

Systems of this nature generate a huge number of small objects and need attention to compact them to a more optimal size for faster reading, such as 128 MB, 256 MB, or 512 MB. As of this writing, only the optimize-data optimization is supported. For our testing, we generated about 58,176 small objects with total size of 2 GB.

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In-place version upgrades for applications on Amazon Managed Service for Apache Flink now supported

AWS Big Data

The next recommended step is to test your application locally with the newly upgraded Apache Flink runtime. After you have sufficiently tested your application with the new runtime version, you can begin the upgrade process. Refer to General best practices and recommendations for more details on how to test the upgrade process itself.

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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

Managing the SQL files, integrating cross-team work, incorporating all software engineering principles, and importing external utilities can be a time-consuming task that requires complex design and lots of preparation. In this post, we look into an optimal and cost-effective way of incorporating dbt within Amazon Redshift.

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Defining Simplicity for Enterprise Software as “a 10 Year Old Can Demo it”

Cloudera

Watch this: Enterprise Software that is so easy a 10 year old can demo it. It is hard for an enterprise infrastructure software company to create simple products. Yet, users of those products want a consumer level of simplicity in enterprise software. the time it took to deploy their software end-to-end. .

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. Your Chance: Want to test a professional logistics analytics software? A testament to the rising role of optimization in logistics.

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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.

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Getting Started With Incremental Sales – Best Practices & Examples

datapine

Explore our sales analytics software for a 14-days free trial today! It gives you a panoramic snapshot of the performance of particular pages of your website and offers you insights into how to optimize your content for increased sales success. Explore our sales analytics software for a 14-days free trial today!

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