bug 8670579

MySQL官方发布了稳定版5.6.36，此版本修复了17年第一季度的远程漏洞bug，是生产环境推荐使用的版本。

在本篇指南中，我们将详细介绍RocketMQ与Spark Streaming的集成流程，特别是如何手动打包第三方库并修复GitHub代码中的BUG，从而支持RocketMQ 4.2与Spark 2.2.1的兼容性。 主要步骤 打包第三方库：手动将RocketMQ相关的依赖打包成第三方库，确保在Spark Streaming中可以正确加载使用。 修复BUG：针对GitHub上的已知问题，手动修改源码，使其与RocketMQ 4.2和Spark 2.2.1版本兼容。 兼容性测试：执行完整的集成测试，确保整个流数据处理链路正常运行，数据传输稳定可靠。 通过以上操作步骤，开发者可以实现RocketMQ与Spark Streaming的流处理集成，为实时大数据分析提供支持。

PSNR Calculation MATLAB Code for PIRM-SR Challenge The PIRM-SR challenge aims to compare and rank perceptual single-image super-resolution methods. In terms of perceptual quality, state-of-the-art methods often perform poorly when evaluated with 'simple' distortion metrics like PSNR and SSIM. Hence, in contrast to previous challenges, the evaluation and ranking will focus on perceptual quality, adopting a unified approach that combines algorithm accuracy with perceptual quality. This allows perceptual-driven methods to compete with those designed to maximize PSNR. To self-verify your method, use this MATLAB code to compute RMSE and perceptual scores for your output on a self-validation set. Here's how to quickly get started: Copy your output to the your_results folder in the base directory. Copy only the HR images to the self_validation_HR folder. Download and extract the SR-Metric toolbox into the utils/sr-metric-master folder. Run the evaluate_results.m script. Troubleshooting Depending on your operating system, you might need to recompile the MEX files in the matlabPyrTools toolbox. If that's the case, follow these steps:- Navigate to utils/sr-metric-master/external/matlabPyrTo and recompile the MEX files.

经过亲自测试，发现p8670579_112010_LINUX.zip可以正常使用，并且在实际操作中表现出色。