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Redis性能问题排查-slowlog和排队延时
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<p>本文介绍以下几点:<br> 1 Redis slowlog不完全可靠<br> 2 请求的排队延迟<br> 3 Redis Single-threads<br>希望对大家排查Redis性能问题时有所帮助。</p>
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细说Redis监控和告警
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2016-08-20
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<p>对于任何应用服务和组件，都需要一套完善可靠谱监控方案。<br>尤其redis这类敏感的纯内存、高并发和低延时的服务，一套完善的监控告警方案，是精细化运营的前提。<br>本文分几节，细说Redis的监控和告警：<br>1.Redis监控告警的价值<br>2.Redis监控的数据采集<br>3.Redis告警策略<br>4.基于Open Falcon的Redis监控告警方案</p>
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Redis数据“丢失”问题
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2016-08-14
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<p>Redis大部分应用场景是纯缓存服务，请求后端有Primary Storage的组件,如MySQL,HBase;请求Redis的键未命中，会从primary Storage中获取数据返回，同时更新Redis缓存。<br>如果少量数据丢失，相当于请求”缓冲未命中“； 一般对业务的影响是无感知的。<br>但现在Redis用作存储的业务场景变多，数据丢失对业务是致命的影响。<br>本文简单讨论Redis常见数据”丢失“现象，以及怎么规避；会列举几个生产中有意思的情节。</p>
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Redis复制主从数据不-致
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2016-08-13
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<p>很多常见的数据库，都采用逻辑异步(或半同步)的方式复制，数据是最终一致性的；<br>这就可能导致复制主从的数据不一致。<br>对MySQL这种关系数据库，如果复制数据出现不一致，这种故障对业务而言，往往是影响极大的。<br>但Redis的缓存场景来说，主从数据不一致或丢失，其对业务影响都很小，一般不被大家所重视。<br>随着Redis用于存储场景越来越多，数据量也越大；这就使保证Redis复制数据一致会比较重要。<br>本文简单讨论Redis复制数据不一致性的影响、常见故障场景和如何避免等</p>
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如何优雅地删除Redis大键
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2016-08-13
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<p>关于Redis大键(Key)，我们从[空间复杂性]和访问它的[时间复杂度]两个方面来定义大键。<br>前者主要表示Redis键的占用内存大小；后者表示Redis集合数据类型(set/hash/list/sorted set)键，所含有的元素个数。以下两个示例：</p>
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<p>1个大小200MB的String键(String Object最大512MB)；内存空间角度占用较大<br> 1个包含100000000(1kw)个字段的Hash键，对应访问模式(如hgetall)时间复杂度高</p>
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<p>因为内存空间复杂性处理耗时都非常小，测试 del 200MB String键耗时约1毫秒，<br>而删除一个含有1kw个字段的Hash键，却会阻塞Redis进程十余秒。所以本文只从时间复杂度分析大的集合类键。删除这种大键的风险，以及怎么优雅地删除。</p>
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细说MySQL Explain和Optimizer Trace简介
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<p>在开发过程中，对每个上线的SQL查询指纹(query figerprint)的质量都应有估算；而估算DB查询质量最直接的方法，就是分析其查询执行计划( Query Execution Plan ,即QEP)。<br>MySQL数据库，通过Explain指令查看SELECT(5.6.3+版本开始支持update/delete/insert等)，下图为sakila.actor的表结构和一个主建过滤查询的执行计划。<br><img src="/images/explain/explain_1.png" alt="explain_1"><br>本文细说从以下三个方面:<br> 1.如何读取EXPLAIN的输出结果<br> 2.简介MySQL5.6的 EXPLAIN FORMAT = JSON和MySQL Workbench的Visual Explain<br> 3.简介MySQL的CBO和Optimizer Trace</p>
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