<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[devin_hugh的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/devin_hugh</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; devin_hugh]]></copyright><item><title><![CDATA[pgsql 递归查询的实现方式]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/111563665</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/111563665</guid><author>devin_hugh</author><pubDate>Tue, 22 Dec 2020 18:14:55 +0800</pubDate><description><![CDATA[递归查询的实现方式
with recursive t(monthly_amt) as (
values(1)
union all
select
monthly_amt

from dm.dm_xxxxxx
where area = 'jp'

)
select
sum(monthly_amt)
from t ;




]]></description><category></category></item><item><title><![CDATA[常用邮箱后缀总结，常用邮箱域名信息汇总]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/109603931</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/109603931</guid><author>devin_hugh</author><pubDate>Tue, 10 Nov 2020 18:01:27 +0800</pubDate><description><![CDATA[常用邮箱后缀总结
外国邮箱后缀分类总结如下:
美国常用邮箱后缀@netzero.net,@twcny.rr.com,@comcast.net,@warwick.net,@comcast.net,@cs.com,@verizon.net
德国常用邮箱后缀@t-online.de,@multi-industrie.de
法国常用邮箱后缀@wannado.fr,@mindspring.com,@excite.com,@club-internet.fr
日本常用邮箱后缀@yahoo.co.jp,@candel.co]]></description><category></category></item><item><title><![CDATA[Postgresql error  could not pull up equivalence class using projected target list (pathkeys.c:1330)]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/108331750</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/108331750</guid><author>devin_hugh</author><pubDate>Mon, 31 Aug 2020 23:30:03 +0800</pubDate><description><![CDATA[最近在运行一个大sql时遇到了以下报错
[XX000] ERROR: could not pull up equivalence class using projected target list (pathkeys.c:1330)

网上没找到对这个错误的处理方法，经过多次实验之后。重要找到了解决问题的方法
报错出现的场景
我首先写了一个 union的查询，然后将这个查询作为一个子查询在外面嵌套了一层。但是单独运行union时，不会出现这个错误
找寻问题原因
经过多次反复试验后，发现是某个字段出现了问题。]]></description><category></category></item><item><title><![CDATA[pgsql实现中位数、众数和平均数的计算]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/105393165</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/105393165</guid><author>devin_hugh</author><pubDate>Wed, 08 Apr 2020 17:45:56 +0800</pubDate><description><![CDATA[pgsql实现中位数、众数和平均数的计算。
pgsql中不支持median函数，说以只能用percentile_disc实现
如下
select
-- 众数
mode() within group ( order by active_days ) as mode_active_days 
-- 中位数
 ,percentile_disc(0.5) within group ( order by a...]]></description><category></category></item><item><title><![CDATA[pgsql 时间戳转日期以及日期转时间戳]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/105199349</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/105199349</guid><author>devin_hugh</author><pubDate>Mon, 30 Mar 2020 16:15:07 +0800</pubDate><description><![CDATA[--时间戳转日期
SELECT TO_TIMESTAMP(1584764955)
--毫秒时间戳转日期（北京时间）
select date(to_timestamp(round(1584764955000/1000)) + interval '1 hour' * 8 )

--日期（datetime类型）转时间戳
SELECT EXTRACT(epoch FROM NOW()); 
SELECT ...]]></description><category></category></item><item><title><![CDATA[anaconda 安装 pystan 和 fbprophet 失败经验总结（时间序列分析python第三方库）采坑无数]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/102624054</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/102624054</guid><author>devin_hugh</author><pubDate>Fri, 18 Oct 2019 13:52:46 +0800</pubDate><description><![CDATA[1、首先安装pystan库

一定要使用conda命令，不要使用conda命令

我是这样写的


(base) PS C:\Users\xxxxx&gt; conda install pystan
Collecting package metadata (current_repodata.json): done
Solving environment: done

## Package P...]]></description><category></category></item><item><title><![CDATA[ETL postgresql 加减月份，在postgresql中实现period_diff/month_diff]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/91428162</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/91428162</guid><author>devin_hugh</author><pubDate>Tue, 11 Jun 2019 14:13:55 +0800</pubDate><description><![CDATA[case when extract(year from age(b.statdt , a.statdt) ) = 1 and
  extract(month from age(b.statdt , a.statdt) ) = 0 then 1 else 0 end Mon12,
case when extract(year from age(b.statdt , a.stat...]]></description><category></category></item><item><title><![CDATA[hive踩过的坑]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/86551498</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/86551498</guid><author>devin_hugh</author><pubDate>Sat, 19 Jan 2019 13:35:50 +0800</pubDate><description><![CDATA[ 

1、hive 中  between的是包括边界值的 

a between 1 and 10    =      a&amp;lt;=10 and a&amp;gt;=1

 

2、case when 只能限制一列的值。  一个 case后只能限制一列，其他的不行！！！...]]></description><category></category></item><item><title><![CDATA[MySQL 往向表中插入中文数值，数据库插入insert中文报错，插不进去怎么办]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/80757184</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/80757184</guid><author>devin_hugh</author><pubDate>Thu, 21 Jun 2018 10:55:29 +0800</pubDate><description><![CDATA[ALTER TABLE sort CONVERT TO CHARSET utf8;  -- 确保插入中文数值ALTER TABLE sort CONVERT TO CHARSET utf8;  -- 确保插入中文数值]]></description><category></category></item><item><title><![CDATA[python中pandas广播运算原则]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/80101969</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/80101969</guid><author>devin_hugh</author><pubDate>Fri, 27 Apr 2018 00:04:52 +0800</pubDate><description><![CDATA[pandas中有Series和DataFrame两种数组类型广播运算是指两个数组进行运算，一个是Series数组（即一维数组），另一个是DataFrame数组（多维数组）为方便理解 这里DataFrame用二维数组表示即 一维数组看成是一行分别与多维数组的每一行进行运算。需要注意的是，如果一维数组过短，结果每行的长度以最大值为准，超过的部分空值，即NaN...]]></description><category></category></item><item><title><![CDATA[Matplotlib库简单介绍，入门  pyplot应用]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79949696</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79949696</guid><author>devin_hugh</author><pubDate>Mon, 16 Apr 2018 00:37:25 +0800</pubDate><description><![CDATA[Matplotlib库由各种可视化类构成，内部结构复杂，受Matlab启发matplotlib.pyplot是绘制各类可视化图形的命令子库，相当于快捷方式一、import matplotlib.pyplot as plt  //引入模块的别名 import matplotlib.pyplot as plt


plt.plot([3,1,5,4,2],[0,2,4,6,8])  # 分别对应的x,...]]></description><category></category></item><item><title><![CDATA[图像的手绘效果代码演示以及原理，嵩天老师MOOC实例]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79948856</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79948856</guid><author>devin_hugh</author><pubDate>Sun, 15 Apr 2018 14:01:35 +0800</pubDate><description><![CDATA[我们平时所用的彩色图像是RGB色（即每个像素由红绿蓝#123456 组成）1. 可以把一张图像相当于一个二维矩阵，在矩阵中每一个一维数组相当于像素点，即（xx,yy,zz）. 2. 我们只需要改变对应像素点的对应一维数组的值，就可以对一张图像色彩进行操作实例：1.这是一个普通的把一张彩色图片通过对它每一个像素点的操作变成它的相反的颜色的from PIL import Image
import nu...]]></description><category></category></item><item><title><![CDATA[python中numpy库函数汇总（存取函数、随机函数、统计函数）]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79940409</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79940409</guid><author>devin_hugh</author><pubDate>Sat, 14 Apr 2018 17:19:20 +0800</pubDate><description><![CDATA[一、CSV 文件存取//需注意：CSV只能有效存储一维和二维数组np.savetxt() np.loadtxt()只能有效存取一维和二维数组np.savetxt(frame, array, fmt='%.18e', delimiter=None)   delimiter=','  delimter 加的是单引号 （）里面都是单引号

//frame : 文件、字符串或产生器，可以是.gz或.bz2...]]></description><category></category></item><item><title><![CDATA[axis维度 python中 numpy中数列维度的运算]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79934810</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79934810</guid><author>devin_hugh</author><pubDate>Fri, 13 Apr 2018 21:27:35 +0800</pubDate><description><![CDATA[axis=0维度是一从最外层开始算[  [9,0,1]  [1,2,3][4,5,6][7,8,9] ]也就是第一维度是4第二维度是 三运算第一维度数列时生成一个第一维度内的元素  即[x,y,z]]]></description><category></category></item><item><title><![CDATA[python函数中连续用两个while循环实例，同一个条件内用两个while，非嵌套]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79382050</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79382050</guid><author>devin_hugh</author><pubDate>Mon, 26 Feb 2018 21:40:43 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-
"""
Created on Tue Apr 30 18:38:23 2019

@author: ptmind
"""

def trim(s):

    if len(s)==0:

        return s

    else:
        while s[0:1]==' ':
            if s[0:1]!=' ...]]></description><category></category></item><item><title><![CDATA[Python赋值运算符]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79310142</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79310142</guid><author>devin_hugh</author><pubDate>Sun, 11 Feb 2018 13:42:16 +0800</pubDate><description><![CDATA[以下假设变量a为10，变量b为20：运算符描述实例=简单的赋值运算符c = a + b 将 a + b 的运算结果赋值为 c+=加法赋值运算符c += a 等效于 c = c + a-=减法赋值运算符c -= a 等效于 c = c - a*=乘法赋值运算符c *= a 等效于 c = c * a/=除法赋值运算符c /= a 等效于 c = c / a%=取模赋值运算符c %= a 等效于 c ...]]></description><category></category></item><item><title><![CDATA[python关键字参数与命名关键字参数的区别]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79309884</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79309884</guid><author>devin_hugh</author><pubDate>Sun, 11 Feb 2018 12:59:58 +0800</pubDate><description><![CDATA[关键字参数

转自https://www.liaoxuefeng.com/wiki/1016959663602400/1017261630425888 记录学习用

可变参数允许你传入0个或任意个参数，这些可变参数在函数调用时自动组装为一个tuple。而关键字参数允许你传入0个或任意个含参数名的参数，这些关键字参数在函数内部自动组装为一个dict。请看示例：


def person(name...]]></description><category></category></item><item><title><![CDATA[python中默认参数必须指为不变对象（多次调用实例以及演示）]]></title><link>https://blog.youkuaiyun.com/devin_hugh/article/details/79300497</link><guid>https://blog.youkuaiyun.com/devin_hugh/article/details/79300497</guid><author>devin_hugh</author><pubDate>Fri, 09 Feb 2018 17:25:38 +0800</pubDate><description><![CDATA[编译器为visual codedef asd(L=[]):
    L.append('END')
    return L
asd()
asd()
print(asd())

#输出为 ['END', 'END', 'END']def asf(K=[]):
    K.append('END')
    return K
asf(['2','4'])
asf(['2','4'])
print(a...]]></description><category></category></item></channel></rss>