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让关系型数据库查询再飞一会儿
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<h1 id="背景"><a href="#背景" class="headerlink" title="背景"></a>背景</h1><p>有一个系统的业务正在膨胀中，某一些报表（报表数据在mysql中）数据量增长比较厉害，报表页面已经处于<code>卡爆了</code>的状态。中间经过mysql本身的优化，已经到了当前系统架构+存储模型的瓶颈。本文提供一种优化思路，抛砖引玉。<br>
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让Spark MLlib的预测性能再飞一会儿
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<h1 id="背景介绍"><a href="#背景介绍" class="headerlink" title="背景介绍"></a>背景介绍</h1><p>我们的系统有一小部分机器学习模型识别需求，因为种种原因，最终选用了Spark MLlib来进行训练和预测。MLlib的Pipeline设计很好地契合了一个机器学习流水线，在模型训练和效果验证阶段，pipeline可以简化开发流程，然而在预测阶段，MLlib pipeline的表现有点差强人意。</p>
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上帝的骰子游戏
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<span id="/2017/09/25/god-s-probable-game/" class="leancloud_visitors" data-flag-title="上帝的骰子游戏">
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<p>概率是一个很有意思的东西，通过上帝投掷出来的骰子，你能猜到上帝的意图。<br>这是一篇白话瞎文，并不是特别严谨。<br>
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word2vec在学历造假中的探索
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<h1 id="前言"><a href="#前言" class="headerlink" title="前言"></a>前言</h1><ol>
<li>如果你想了解word2vec的原理，这篇文章并不适合你，出门右转用google。</li>
<li>这篇文章的东西含金量不高，希望搞NLP，ML，DL的专业人士轻拍。</li>
<li>因为含金量不高，所以有一些诸如数据预处理的一些琐碎的东西，因此比较适合新手村的新手任务。
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