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Accelerate Amazon Redshift Data Lake queries with AWS Glue Data Catalog Column Statistics

AWS Big Data

Over the last year, Amazon Redshift added several performance optimizations for data lake queries across multiple areas of query engine such as rewrite, planning, scan execution and consuming AWS Glue Data Catalog column statistics. Some of the queries in our benchmark experienced up to 12x speed up.

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Improving Data Processing with Spark 3.0 & Delta Lake

Smart Data Collective

Delta lake allows thousands of data to run in parallel, address optimization and partition challenges, faster metadata operations, maintains a transactional log and continuously keeps updating the data. Apart from leveraging the benefits of Delta Lake, migrating to Spark 3.0 Optimization. Advantages of using Delta Lakes.

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New AI Advances Increase User Reach with Advanced Targeting

Smart Data Collective

A growing number of marketers are using AI to optimize and automate marketing campaigns in fantastic ways. Jason Hall, Founder and CEO of FiveChannels described some of the phenomenal benefits of leveraging AI in digital marketing in a post in Forbes. There are a number of benefits of using AI for improved targeting.

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Machine Learning Improves Mesh Networks & Fights Dead Zones

Smart Data Collective

One of the benefits of machine learning is that it can help improve mesh networks, which can minimize the risk of Internet connectivity problems. In order to appreciate the benefits of using machine learning to address these problems, it is necessary to first appreciate the issues caused by dead zones and how they emerge in the first place.

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AI Advances Are Reshaping Video Streaming Protocols

Smart Data Collective

Some of the largest video streaming services, such as Netflix and Hulu use AI to provide the highest quality video streaming benefits to their customers. To optimize your viewing experience, online video transmission uses streaming-specific and HTTP-based protocols. Cost Depending on the protocol, you might incur licensing fees.

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Filter more pay less with the latest Cloudera Data Warehouse runtime!

Cloudera

One of the most effective ways to improve performance and minimize cost in database systems today is by avoiding unnecessary work, such as data reads from the storage layer (e.g., MapJoins can directly benefit from the probedecode feature. Introduction. className: VectorMapJoinInnerBigOnlyLongOperator. Performance.

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Amazon EMR 7.1 runtime for Apache Spark and Iceberg can run Spark workloads 2.7 times faster than Apache Spark 3.5.1 and Iceberg 1.5.2

AWS Big Data

In this post, we explore the performance benefits of using the Amazon EMR runtime for Apache Spark and Apache Iceberg compared to running the same workloads with open source Spark 3.5.1 Additionally, the cost efficiency improves by 2.2 times, with the total cost decreasing from $16.09 on Iceberg tables. In Run Apache Spark 3.5.1