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Keeping Small Queries Fast – Short query optimizations in Apache Impala

Cloudera

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. Query optimization in databases is a long standing area of research, with much emphasis on finding near optimal query plans.

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Amazon EMR 7.5 runtime for Apache Spark and Iceberg can run Spark workloads 3.6 times faster than Spark 3.5.3 and Iceberg 1.6.1

AWS Big Data

Amazon EMR on EC2 , Amazon EMR Serverless , Amazon EMR on Amazon EKS , Amazon EMR on AWS Outposts and AWS Glue all use the optimized runtimes. This is a further 32% increase from the optimizations shipped in Amazon EMR 7.1 In this post, we demonstrate the performance benefits of using the Amazon EMR 7.5 with Iceberg 1.6.1 q14b-v2.13,q15-v2.13,q16-v2.13,

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What Does 2000 Year Old Concrete Have to Do with Knowledge Graphs?

Ontotext

Knowledge graphs enable content, data and knowledge-centric enterprises to improve repeated monetization of their assets by optimizing their reuse and repurposing as well as creating new products such as books, apps, reports, journal articles, content, and data feeds. The post What Does 2000 Year Old Concrete Have to Do with Knowledge Graphs?

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Write queries faster with Amazon Q generative SQL for Amazon Redshift

AWS Big Data

With Amazon Q, you can spend less time worrying about the nuances of SQL syntax and optimizations, allowing you to concentrate your efforts on extracting invaluable business insights from your data. Refer to Easy analytics and cost-optimization with Amazon Redshift Serverless to get started. For this post, we use Redshift Serverless.

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Optimized joins & filtering with Bloom filter predicate in Kudu

Cloudera

Pushing down column predicate filters to Kudu allows for optimized execution by skipping reading column values for filtered out rows and reducing network IO between a client, like the distributed query engine Apache Impala, and Kudu. One of the ways Apache Kudu achieves this is by supporting column predicates with scanners. Join Queries.

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Amazon EMR Serverless observability, Part 1: Monitor Amazon EMR Serverless workers in near real time using Amazon CloudWatch

AWS Big Data

For example, underutilization of vCPUs or memory can reveal resource wastage, allowing you to optimize worker sizes to achieve potential cost savings. Optimize resource utilization When running Spark jobs, you often start with the default configurations. The second job took 4 minutes, 54 seconds.

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Strategic planning: How CIOs can build the best possible future

CIO Business Intelligence

For twenty years, from approximately 1980 to 2000, the primary objective of IT strategy was to solicit funding. years) is becoming the optimal temporal “chunk” inside which to do career and strategic planning. The most important questions about the future are who will we be and when will we be.