wt

需求 每小时进行一次查询统计数据，并将数据插入到自定义的表当中 效果 创建存储过程 create or replace procedure summary_data as v_dcppv number; v_jd12h number; v_dby number; v_xby number; v_bj number; v_bn number; v_zdzf number; v_wxzf number; v_jfzf number; v_yhdj number; v_dgzs number; v_tds number; v_tds2 number; begin --单次 select count(1) into v_dcppv from iptvsp_wt_req a where servicecode = 'JK0008' and a.instime between trunc(sysdate, 'hh') - 1 / 24 and trunc(sysdate, 'hh') - 1 / 86400 and orderstatus = 1 and order_type in (0, 1) and order_time IN (48, 30) and a.user_id like '116%'; --酒店 select count(1) into v_jd12h from iptvsp

I am familiar with both Python and C++ as a programmer. I was thinking of writing my own simple web application and I wanted to know which language would be more appropriate for server-side web development. Some things I'm looking for: It has to be intuitive. I recognize that Wt exists and it follows the model of Qt. The one thing I hate about Qt is that they encourage strange syntax through obfuscated means (e.g. the "public slots:" idiom). If I'm going to write C++, I need it to be standard, recognizable, clean code. No fancy shmancy silliness that Qt provides. The less non-C++ or Python

on namespace ceilometer.$cmd failed: Authentication failed. UserNotFound: Could not find user ceilometer@ceilometer 背景介绍 1、 Ceilometer 项目是 OpenStack 中用来做计量计费功能的一个组件，后来又逐步发展增加了部分监控采集、告警的功能。 2、 MongoDB 是一个基于分布式文件存储的数据库。由 C++ 语言编写。旨在为 WEB 应用提供可扩展的高性能数据存储解决方案。 3、前几年的一个项目就使用到了 Ceilometer 和 MongoDB （ 3.2.9 版本） 结合，用于存储性能和告警数据。 问题说明 最近，在某个现场环境上，MongoDB 挂载的存储设备出现了故障。但是，存储设备故障恢复后，MongoDB服务无法正常启动。 启动日志报错如下： 2019-10-31T16:33:27.651+0800 I CONTROL [main] ***** SERVER RESTARTED ***** 2019-10-31T16:33:27.658+0800 I CONTROL [initandlisten] MongoDB starting : pid=5097 port=27017 dbpath=/var/lib/mongodb 64-bit

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: 3 plots arranged in 2 rows and 2 columns attach(mtcars) par(mfrow=c(2,2)) plot(wt,mpg, main="Scatterplot of wt vs. mpg") plot(wt,disp, main="Scatterplot of wt vs disp") boxplot(wt, main="Boxplot of wt") But how do I create a panel with just text and then add it to the fourth position in the grid. Apologies. I see now that like many quesioners I was asking you to read my mind or intuit from my code that I expected the text to be arranged left-justified in a grid of locations in the blank space. (For some reason this seemed perfectly

作为一个刚刚入门NLP的学生，希望在阅读每一篇论文后都进行一定的记录，提炼文中观点，写出自己的理解，如有任何解读错误之处敬请指出，Ｏ（∩＿∩）Ｏ谢谢！ 先放出paper的网址　 https://arxiv.org/pdf/1806.08730.pdf key words Multitask Learning Zero-shot Learning Transfer Learning Meta-Learning 前言 当今QA问题在NLP领域可以说是炽手可热，SQUAD数据集的出现，大量RNN，Attention的模型出现将SQUAD1.0的简单问题准确度提高至超越人类。我的同学也有在做SQUAD的，基本上是在别人模型的输入和encoder端上面做些小trick，提升那么1、2个百分点的EM/F1，在我看来这些工作真的是毫无意义。 本篇文章的作者的一句话直中要害： The quirk of the dataset does not hold for question answering in general, so recent models for SQUAD are not necessarily general QA models. 数据集的“怪癖”并不对普遍的QA问题适用，所以当前的QA Model都不是通用模型。 然而跳出SQUAD的局限

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Using the package dplyr and the function sample_frac it is possible to sample a percentage from every group. What I need is to first sort the elements in every group and then select top x% from every group? There is a function top_n , but here I can only determine the number of rows, and I need a relative value. For example the following data is grouped by gear and sorted by wt within each group: library(dplyr) mtcars %>% select(gear, wt) %>% group_by(gear) %>% arrange(gear, wt) gear wt 1 3 2.465 2 3 3.215 3 3 3.435 4 3 3.440 5 3 3.460 6 3 3

resize在modules/imgproc/src/文件件中,首先看resize API的函数实现: void resize(InputArray src, OutputArray dst, Size dsize, double fx= 0 , double fy= 0 , int interpolation=INTER_LINEAR ) 参数说明: src:输入图像 dst:输出图像,dst的数据类型与src相同. dsize:这个参数是输出图像的尺寸,两种情况,如果该参数设置为0,api会自动计算 输出参数,否则按照输入尺寸.dst的计算公式: d s i z e = S i z e ( r o u n d ( f x × s r c . c o l s ) , r o u n d ( f y × s r c . r o w s ) ) d s i z e = S i z e ( r o u n d ( f x × s r c . c o l s ) , r o u n d ( f y × s r c . r o w s ) ) 所以当dsize为0的时候,fx和fy不能为0. fx: ( d o u b l e ) d s i z e . w i d t h / s r c . c o l s ( d o u b l e ) d s i z e . w i d t h /

# 选取数据框中的元素 --------------------------------------------------------------- patientdata [ c ( 'diabetes' , 'status' )] patientdata [ 1 : 2 ] patientdata [, 1 : 2 ] patientdata$age table ( patientdata$diabetes , patientdata$status ) summary ( mtcars$mpg ) plot ( mtcars$mpg , mtcars$wt ) attach ( mtcars ) summary ( mpg ) plot ( mpg , wt ) detach ( mtcars ) mpg = c ( 25 , 36 , 47 ) attach ( mtcars ) plot ( mpg , wt ) with ( mtcars ,{ print ( summary ( mpg )) plot ( mpg , disp ) # plot(mpg,wt) }) with ( mtcars ,{ local_var <- summary ( mpg ) global_var <<- summary ( mpg ) }) local_var global_var