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Back to hanzichi/underscore-analysis

Open-source alternatives to Underscore Analysis

30 open-source projects similar to hanzichi/underscore-analysis, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Underscore Analysis alternative.

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  • dagnygus/ng-queuexdagnygus avatar

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    This project is a collection of educational resources and technical guides focused on Go performance optimization. It provides instruction on improving execution speed and reducing memory usage through code and architectural refinements. The guides cover advanced strategies for low-level programming, including the use of assembly for SIMD instructions and unsafe pointers for direct memory manipulation. It also details concurrency optimization techniques such as lock sharding and cache-line padding to reduce contention and improve hardware utilization. The material encompasses broad capabilit

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  • didi/boosterdidi avatar

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    Booster is an Android app build optimizer and bytecode manipulator designed to reduce binary size, fix system-level crashes, and improve application performance. It functions as an extensible build process plugin that modifies compiled class files and build artifacts to inject stability fixes and optimizations without altering the original source code. The project differentiates itself through low-level bytecode manipulation to patch OS-level bugs and manage thread pools during the compilation phase. It also provides a performance profiling toolkit to identify main-thread blocking operations

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    A lightweight Angular service to monitor network status: online/offline, connection quality (2G/3G/4G/5G), and ping latency.

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    qiurunze123/memoryoptimization

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    在项目上线之初,我们应该如何设置JVM的参数配置,我们如何分配内存空间会使效率最大化,当项目上线后我们如何监控项目的内存情况呢? 我们又如何来查看内存的溢出情况,分析GC日志呢?...... 这个项目就是为了这些研究这些可能大家平时不会考虑的东西来应运而生? 此项目仍为进阶课程,一些简单的请提前预习!

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    three-high-import 项目意义在于利用多线程进行千万级别导入,实现可扩展,高性能,高可用,高可靠三个高,本项目可以在千万级别数据实现无差别高性能数据上报 与导入,与普通导入相比性能提高10倍左右,而且规避风险在偶尔的机器宕机,网络波动等情况出现时,仍能够实现数据一致,数据可靠,数据重试,数据报警等功能,在一些重要数据 例如: 对账 , 账户金额,账单等,需要每日定时任务而且有高风险的数据实现数据无错误! 多线程从基础到进阶,分析入坑出坑,以及工作实操,最后会分享一个项目,针对如何进行大数据量(经测试几亿数据完全搞的定)进行安全高可用的策略, 示例为高可用高可靠高性能…

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