<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[okkkay的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/okkkay</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; okkkay]]></copyright><item><title><![CDATA[Linux miniconda3安装superset 2.1.0可能遇到的一些问题]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/131483353</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/131483353</guid><author>okkkay</author><pubDate>Fri, 30 Jun 2023 20:29:51 +0800</pubDate><description><![CDATA[确定目录，例如我这里是 /opt/module/miniconda3。cd后发现该目录下有一个bin目录，即PYTHONPATH。记录一下Linux miniconda3安装superset 2.1.0遇到的一些问题。解决办法：sqlparse降级处理。环境：python3.9。新建一个文件，添加内容。]]></description><category></category></item><item><title><![CDATA[hive 3.1.3 on spark 3.0.0 安装教程 (内附重新编译好的jar包)]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/131091808</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/131091808</guid><author>okkkay</author><pubDate>Wed, 07 Jun 2023 18:14:49 +0800</pubDate><description><![CDATA[一步一步教会你如何部署 hive 3.1.3 on spark 3.0.0，文章还提供了修改好的源码包~]]></description><category></category></item><item><title><![CDATA[spark hive 本地调试 & 提交任务到yarn cluster]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/130658995</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/130658995</guid><author>okkkay</author><pubDate>Sat, 13 May 2023 16:51:58 +0800</pubDate><description><![CDATA[本文讲述spark部署在远程服务器的yarn环境下时，如何进行本地调试以及提交任务到yarn cluster首先，]]></description><category></category></item><item><title><![CDATA[ZooKeeper源码 Sources not found for: org.apache.zookeeper:zookeeper:3.5.7]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/130360377</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/130360377</guid><author>okkkay</author><pubDate>Tue, 25 Apr 2023 11:19:36 +0800</pubDate><description><![CDATA[查看ZooKeeper源码，发现Download Sources无法下载，报。下载箭头指向的文件apache-zookeeper-3.5.7.tar.gz。找到zookeeper目录，根据自己的版本进入文件夹，例如我的是3.5.7。点击源码右上角Choose Sources，选择zip压缩包。完成上述操作后，zk源码中就能看到相关说明。，放到一个方便管理的目录下。]]></description><category></category></item><item><title><![CDATA[ZooKeeper创建节点报错：KeeperErrorCode = ConnectionLoss for]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/130359603</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/130359603</guid><author>okkkay</author><pubDate>Tue, 25 Apr 2023 10:49:10 +0800</pubDate><description><![CDATA[由于jdk向下兼容，因此Project下的SDK无需修改，仅调整Modules版本即可。完成以上修改后，重新执行代码，成功创建zk节点。观察idea和集群的jdk版本是否一致。idea下jdk为Java 12。集群jdk为 Java 1.8。调整idea下jdk版本。]]></description><category></category></item><item><title><![CDATA[scala安装报错：此时不应有 \scala\scala-2.12.17\bin\..\lib\jline-2.14.6.jar]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/130229828</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/130229828</guid><author>okkkay</author><pubDate>Tue, 18 Apr 2023 20:00:13 +0800</pubDate><description><![CDATA[查阅资料后发现是因为安装目录中带空格的缘故。重新配置环境变量即可。]]></description><category></category></item><item><title><![CDATA[云服务器hadoop踩坑史：java.io.IOException: Got error, status=ERROR, status message , ack with firstBadLink]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/129844565</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/129844565</guid><author>okkkay</author><pubDate>Wed, 29 Mar 2023 20:59:49 +0800</pubDate><description><![CDATA[解决云服务器搭建hadoop报错：java.io.IOException: Got error, status=ERROR, status message , ack with firs]]></description><category></category></item><item><title><![CDATA[latex二级目录字母改编号(IEEE TRANS)]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/126329147</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/126329147</guid><author>okkkay</author><pubDate>Sun, 14 Aug 2022 10:47:41 +0800</pubDate><description><![CDATA[IEEE TRANS latex模板二级目录subsection编号字母改数字]]></description><category></category></item><item><title><![CDATA[Pandas多列分组计算时长]]></title><link>https://blog.youkuaiyun.com/okkkay/article/details/118549899</link><guid>https://blog.youkuaiyun.com/okkkay/article/details/118549899</guid><author>okkkay</author><pubDate>Wed, 07 Jul 2021 16:34:13 +0800</pubDate><description><![CDATA[Pandas多列分组计算时长
马上要读研了，暑假期间找了一份数据分析岗的实习，算是找点事情做，老大建议我工作上遇到的问题可以记录在博客里，遂第一篇博客诞生了。
数据由多列组成，目的是根据其中两列来划分数据，此处使用ID和name来分组，对time进行求和获取总时长
df['time'] = df['time'].apply(pd.to_numeric)  # 转换数据类型
grouped = df['time'].groupby([df['ID'],df['name']])  # 按照ID和name列分组
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