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Impact of Querying Table Information From information_schema

Percona

Disclaimer : This blog post is meant to show a less-known problem but is not meant to be a serious benchmark. The percentage in degradation will vary depending on many factors {hardware, workload, number of tables, configuration, etc.}. Setup The setup consists of creating 10K tables with sysbench and adding 20 FKs to 20 tables.

Cache 105
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HammerDB v4.3 New Features Pt1: Graphical Metrics for PostgreSQL

HammerDB

This enables the user to compare and contrast performance across different benchmark scenarios. By clicking on the Metrics Display option, HammerDB will connect to the target database and start monitoring the performance, note that if the pg_active_session_history table is empty the viewer will report an error and refuse to start.

Metrics 62
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What Adrian Did Next?—?Part 2?—?Sun Microsystems

Adrian Cockcroft

I became the Sun UK local specialist in performance and hardware, and as Sun transitioned from a desktop workstation company to sell high end multiprocessor servers I was helping customers find and fix scalability problems. I had attended these events when I was based in the UK, but became one of the organizers.

Tuning 52
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HammerDB v4.0 New Features Pt1: TPROC-C & TPROC-H

HammerDB

A full understanding of why this is important requires some knowledge of the evolution of database hardware and software. The HammerDB TPROC-C workload by design intended as CPU and memory intensive workload derived from TPC-C – so that we get to benchmark at maximum CPU performance at a much smaller database footprint.

C++ 40
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Kubernetes for Big Data Workloads

Abhishek Tiwari

support for logging, monitoring, and observability. A recent performance benchmark completed by Intel and BlueData using the BigBench benchmarking kit has shown that the performance ratios for container-based Hadoop workloads on BlueData EPIC are equal to and in some cases, better than bare-metal Hadoop [7]. Performance.

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10 tips for migrating from monolith to microservices

Dynatrace

Unsurprisingly, organizations are breaking away from monolithic architectures and moving toward event-driven microservices. Security should be an integral part of each stage of the software delivery lifecycle, from development to monitoring in real time. However, the move to microservices comes with its own challenges and complexities.

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Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Last time around we looked at the DeathStarBench suite of microservices-based benchmark applications and learned that microservices systems can be especially latency sensitive, and that hotspots can propagate through a microservices architecture in interesting ways. When available, it can use hardware level performance counters.