自动将数据从sql传输到R [英] Automatic transfer data from the sql to R

问题描述

我从sql服务器获取数据以执行回归分析，然后将回归结果返回到另一个sql表。

I get the data from the sql server to perform regression analysis, and then the regression results i return back to another sql table.

library("RODBC")
library(sqldf)

dbHandle <- odbcDriverConnect("driver={SQL Server};server=MYSERVER;database=MYBASE;trusted_connection=true")

sql <- 
  "select
Dt
,CustomerName
,ItemRelation
,SaleCount
,DocumentNum
,DocumentYear
,IsPromo

from dbo.mytable"

df <- sqlQuery(dbHandle, sql)

reg=lm(SaleCount~IsPromo,data=df)

#save to sql table
sqlSave(dbHandle, as.data.frame(reg), "dbo.mytableforecast", verbose = TRUE)  # use "append = TRUE" to add rows to an existing table

odbcClose(dbHandle)

问题：

脚本自动运行，即在调度程序中有在特定时间启动脚本的任务。
如何在下次运行脚本时执行此操作，该脚本不能与所有表一起使用，而只能与sql中加载的数据一起使用？

The script works automatically, i.e. in the scheduler there is task that script in certain time was launched. How to do that in the next time, when the script runs, it must work not with all table, but only the data that was loaded in sql?

例如，今天加载了100个观测值。
从01.01.2017-10.04.2017
脚本执行了回归并将数据返回到sql表。
明天将加载新的100个观察值。
11.04.2017-20.07.2017
I.E.明天何时将加载数据并且脚本将在晚上10点开始运行，则该脚本必须仅适用于2017年4月11日至20.07.2017的数据，而不适用于2017年1月1日至20.07.2017的数据。

For example, today was loaded 100 observations. From 01.01.2017-10.04.2017 Script performed regression and returned data to sql table. Tomorrow will loaded new 100 observations. 11.04.2017-20.07.2017 I.E. when tomorrow the data will loaded and the script will start at 10 pm, it must work only with data from 11.04.2017-20.07.2017, and not from 01.01.2017-20.07.2017

我该怎么做？

sql中的数据示例

df=structure(list(Dt = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
8L, 9L, 9L, 10L, 10L, 11L, 11L, 12L, 12L, 13L, 13L, 14L, 14L, 
15L, 15L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 
18L, 19L), .Label = c("2017-10-12 00:00:00.000", "2017-10-13 00:00:00.000", 
"2017-10-14 00:00:00.000", "2017-10-15 00:00:00.000", "2017-10-16 00:00:00.000", 
"2017-10-17 00:00:00.000", "2017-10-18 00:00:00.000", "2017-10-19 00:00:00.000", 
"2017-10-20 00:00:00.000", "2017-10-21 00:00:00.000", "2017-10-22 00:00:00.000", 
"2017-10-23 00:00:00.000", "2017-10-24 00:00:00.000", "2017-10-25 00:00:00.000", 
"2017-10-26 00:00:00.000", "2017-10-27 00:00:00.000", "2017-10-28 00:00:00.000", 
"2017-10-29 00:00:00.000", "2017-10-30 00:00:00.000"), class = "factor"), 
    CustomerName = structure(c(1L, 11L, 12L, 13L, 14L, 15L, 16L, 
    17L, 18L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 11L, 12L, 
    13L, 14L, 15L, 16L, 17L, 18L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
    9L, 10L), .Label = c("x1", "x10", "x11", "x12", "x13", "x14", 
    "x15", "x16", "x17", "x18", "x2", "x3", "x4", "x5", "x6", 
    "x7", "x8", "x9"), class = "factor"), ItemRelation = c(13322L, 
    13322L, 13322L, 13322L, 13322L, 13322L, 13322L, 11706L, 13322L, 
    11706L, 13322L, 11706L, 13322L, 11706L, 13322L, 11706L, 13322L, 
    11706L, 13322L, 11706L, 13322L, 11706L, 13322L, 11706L, 13163L, 
    13322L, 158010L, 11706L, 13163L, 13322L, 158010L, 11706L, 
    13163L, 13322L, 158010L, 11706L), SaleCount = c(10L, 3L, 
    1L, 0L, 9L, 5L, 5L, 11L, 7L, 0L, 5L, 11L, 1L, 0L, 0L, 19L, 
    10L, 0L, 1L, 12L, 1L, 11L, 6L, 0L, 167L, 7L, 0L, 16L, 165L, 
    1L, 0L, 0L, 29L, 0L, 0L, 11L), DocumentNum = c(36L, 36L, 
    36L, 36L, 36L, 36L, 36L, 51L, 36L, 51L, 36L, 51L, 36L, 51L, 
    36L, 51L, 36L, 51L, 36L, 51L, 36L, 51L, 36L, 51L, 131L, 36L, 
    89L, 51L, 131L, 36L, 89L, 51L, 131L, 36L, 89L, 51L), DocumentYear = c(2017L, 
    2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
    2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
    2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 
    2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L), 
    IsPromo = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("Dt", "CustomerName", 
"ItemRelation", "SaleCount", "DocumentNum", "DocumentYear", "IsPromo"
), class = "data.frame", row.names = c(NA, -36L))

推荐答案

添加日期到您的结果sql表 dbo.mytableforecast

Add a date to your result sql table dbo.mytableforecast

更改select SQL语句，使其仅选择

Change the select SQL statement such that it only selects data after

select
Dt
,CustomerName
,ItemRelation
,SaleCount
,DocumentNum
,DocumentYear
,IsPromo

from dbo.mytable

where Dt > (select max(Dt) from dbo.mytableforecast)

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