A naukri.com initiative
Amazon
2M
137
Image Credit: Amazon
Achieve the best price-performance in Amazon Redshift with elastic histograms for selectivity estimation
- Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.
- Amazon Redshift’s advanced Query Optimizer is a crucial part of that leading performance.
- As data is ingested into the Redshift data warehouse over time, statistics could become stale, which in turn causes inaccurate selectivity estimations, leading to sub-optimal query plans that impact query performance.
- Amazon Redshift introduced a new selectivity estimation technique in Amazon Redshift patch release P183 (v1.0.75379) to address the situation — having up-to-date statistics on temporal columns improving query plans and thereby performance.
- The new technique captures real-time statistical metadata gathered during data ingestion without incurring additional computational overhead.
- Amazon Redshift users will benefit with better query response times for their workloads.
- The new selectivity estimation enhancement has already improved the performance of hundreds of thousands of customer queries in the Amazon Redshift fleet since its introduction in the patch release P183.
- Amazon Redshift now offers enhanced query performance with optimizations such as Enhanced Histograms for Selectivity Estimation in the absence of fresh statistics by relying on metadata statistics gathered during ingestion.
- Optimizations are enabled by default and Amazon Redshift is on a mission to continuously improve performance and therefore overall price-performance.
- We invite you to try the numerous new features introduced in Amazon Redshift together with the new performance enhancements.
Read Full Article
8 Likes
For uninterrupted reading, download the app