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Fine-Tuning Performance, Resolving Common Issues in FinTech Application With MySQL

DZone

This article will explore the FinTech case study, which has built a Lending Platform. This foundational component in any application architecture usually poses challenges around scaling as the business expands rapidly. The company uses the MySQL database hosted in AWS as part of the AWS RDS service.

FinTech 262
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Java Parallel GC Tuning

DZone

Parallel GC aims to reduce the impact of GC pauses by utilizing multiple threads to perform garbage collection in parallel. In this article, we will delve into the realm of Parallel GC tuning specifically. However, if you want to learn more basics of Garbage Collection tuning, you may watch this JAX London conference talk.

Tuning 249
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Speed Trino Queries With These Performance-Tuning Tips

DZone

In this article, we will show you how to tune Trino by helping you identify performance bottlenecks and provide tuning tips that you can practice. But how do we do that?

Tuning 162
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SQL Performance Tuning tips for newbies

SQL Shack

The purpose of this article is to give newbies some basic advice about SQL performance tuning that helps to improve their query tuning skills in SQL Server.

Tuning 52
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Fine Tune Your Salesforce Queries

DZone

Writing efficient queries is crucial to maintaining the performance of these applications and ensuring that we don't run into Salesforce limits. This article will shed light on those techniques. This article will also walk you through tools you could use to measure query performance in Salesforce.

Tuning 173
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Bayesian Optimization and Hyperband (BOHB) Hyperparameter Tuning With an Example

DZone

Machine learning models often require tuning of hyperparameters to achieve their best performance. Hyperparameter tuning can be a daunting and time-consuming task, as it involves experimenting with different parameter combinations to find the optimal settings. What Is BOHB? BOHB stands for Bayesian Optimization and Hyperband.

Tuning 147
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A Comprehensive Guide to Hyperparameter Tuning: Exploring Advanced Methods

DZone

Hyperparameter tuning is an essential practice in optimizing the performance of machine learning models. This article provides an in-depth exploration of advanced hyperparameter tuning methods, including Population-Based Training (PBT), BOHB, ASHA, TPE, Optuna, DEHB, Meta-Gradient Descent, BOSS, and SNIPER.

Tuning 147