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Amazon OpenSearch Service Under the Hood : OpenSearch Optimized Instances(OR1)

AWS Big Data

Amazon OpenSearch Service recently introduced the OpenSearch Optimized Instance family (OR1), which delivers up to 30% price-performance improvement over existing memory optimized instances in internal benchmarks, and uses Amazon Simple Storage Service (Amazon S3) to provide 11 9s of durability.

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Optimization Strategies for Iceberg Tables

Cloudera

This blog discusses a few problems that you might encounter with Iceberg tables and offers strategies on how to optimize them in each of those scenarios. Problem with too many snapshots Everytime a write operation occurs on an Iceberg table, a new snapshot is created. See Write properties.

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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. Note the last four newly added configurations in the following statement.

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How Amazon optimized its high-volume financial reconciliation process with Amazon EMR for higher scalability and performance

AWS Big Data

To optimize the reconciliation process, these users require high performance transformation with the ability to scale on demand, as well as the ability to process variable file sizes ranging from as low as a few MBs to more than 100 GB. Architecture before migration The following diagram illustrates our previous architecture.

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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

Internally, Apache Flink uses clever mechanisms to maintain exactly-once state consistency, while also optimizing for throughput and reduced latency. Each of the distributed components of an application asynchronously snapshots its state to an external persistent datastore. The application is coordinated by a job manager.

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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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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments. Why: Data Makes It Different.

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