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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. For more information on streaming applications on AWS, refer to Real-time Data Streaming and Analytics. with Spark 3.3.2, and JupyterEnterpriseGateway 2.6.0.

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Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 2

AWS Big Data

We’ve already discussed how checkpoints, when triggered by the job manager, signal all source operators to snapshot their state, which is then broadcasted as a special record called a checkpoint barrier. When barriers from all upstream partitions have arrived, the sub-task takes a snapshot of its state.

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Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 1

AWS Big Data

Amazon Managed Service for Apache Flink , formerly known as Amazon Kinesis Data Analytics, is the AWS service offering fully managed Apache Flink. Internally, Apache Flink uses clever mechanisms to maintain exactly-once state consistency, while also optimizing for throughput and reduced latency. This is a two-phase operation.

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Find the best Amazon Redshift configuration for your workload using Redshift Test Drive

AWS Big Data

Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. In this post, we answer that question by using Redshift Test Drive , an open-source tool that lets you evaluate which different data warehouse configurations options are best suited for your workload.

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. AWS Glue is a serverless data integration service that makes it easy for analytics users to discover, prepare, move, and integrate data from multiple sources.

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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

Amazon Redshift is a cloud data warehousing service that provides high-performance analytical processing based on a massively parallel processing (MPP) architecture. In this post, we look into an optimal and cost-effective way of incorporating dbt within Amazon Redshift. For more information, refer SQL models.

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Top 20 most-asked questions about Amazon RDS for Db2 answered

IBM Big Data Hub

Answer : Along with standard RDS features, Amazon RDS for Db2 supports key Db2 features, such as row and column organized tables for mixed and analytic workloads, the Adaptive Workload Optimizer to for better resource management, and rules-based access controls for advanced data protection.   13.