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Enhanced Query Caching Mechanism in Hibernate 6.3.0

DZone

Efficient query caching is a critical part of application performance in data-intensive systems. Hibernate has supported query caching through its second-level cache and query cache mechanisms. released in December 2024, addresses these problems by introducing enhanced query caching mechanisms.

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Dive Into Tokenization, Attention, and Key-Value Caching

DZone

However, a significant challenge in deploying these models lies in optimizing their performance, particularly for tasks involving long text generation. One powerful technique to address this challenge is k ey-value caching (KV cache).

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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

When serving and storing files on the web, there are a number of different things we need to take into consideration in order to balance ergonomics, performance, and effectiveness. Caching them at the other end: How long should we cache files on a user’s device? Cache This is the easy one. main.af8a22.css main.af8a22.css

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Why Replace External Database Caches?

DZone

Teams often consider external caches when the existing database cannot meet the required service-level agreement (SLA). This is a clear performance-oriented decision. However, external caches are not as simple as they are often made out to be.

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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.

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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

In both bands, performance characteristics remain consistent for the entire uptime of the JVM on the node, i.e. nodes never jumped the bands. Luckily, the m5.12xl instance type exposes a set of core PMCs (Performance Monitoring Counters, a.k.a. We also see much higher L1 cache activity combined with 4x higher count of MACHINE_CLEARS.

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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

This counting service, built on top of the TimeSeries Abstraction, enables distributed counting at scale while maintaining similar low latency performance. Best Effort Regional Counter This type of counter is powered by EVCache , Netflix’s distributed caching solution built on the widely popular Memcached.

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