Remove Blog Remove Optimization Remove Snapshot Remove Testing
article thumbnail

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.

article thumbnail

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

AWS Big Data

To learn more about the features supported in each Apache Flink version, you can consult the Apache Flink blog , which discusses at length each of the Flink Improvement Proposals (FLIPs) incorporated into each of the versioned releases. The next recommended step is to test your application locally with the newly upgraded Apache Flink runtime.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Materialized Views in Hive for Iceberg Table Format

Cloudera

Overview This blog post describes support for materialized views for the Iceberg table format. Queries containing joins, filters, projections, group-by, or aggregations without group-by can be transparently rewritten by the Hive optimizer to use one or more eligible materialized views.

article thumbnail

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. Backup and restore 11.

article thumbnail

Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes

AWS Big Data

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. Update your-iceberg-storage-blog in the following configuration with the bucket that you created to test this example.

article thumbnail

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.

Big Data 275
article thumbnail

Keeping Small Queries Fast – Short query optimizations in Apache Impala

Cloudera

This is part of our series of blog posts on recent enhancements to Impala. Impala Optimizations for Small Queries. We’ll discuss the various phases Impala takes a query through and how small query optimizations are incorporated into the design of each phase. The entire collection is available here. Query Planner Design.