executeStoredProcedure:執行 SQL 預存程序
executeStoredProcedure
:執行向資料庫註冊的預存程序
使用方式
executeStoredProcedure(sqlSP, ..., connectionString = NULL)
引數
sqlSP
有效的 StoredProcedure 物件
...
預存程序的選擇性輸入和輸出參數。 必須提供未指派預設查詢或值的所有參數
connectionString
字元字串 (如果不使用連接字串建立 StoredProcedure 物件,則必須提供)。 此函數需要使用支援 ODBC 3.8 功能的 ODBC 驅動程式。
verbose
布林值。 是否印出用來執行預存程序的命令
值
成功則為 TRUE,失敗則為 FALSE
備註
此函數仰賴於使用的 ODBC 驅動程式支援 ODBC 3.8 功能, 否則將會失敗。
範例
## Not run:
# See ?StoredProcedure for creating the "cleandata" table.
############# Example 1 #############
# Create a linear model and store in the "rdata" table.
train <- function(in_df) {
factorLevels <- c("Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday")
in_df[,"DayOfWeek"] <- factor(in_df[,"DayOfWeek"], levels=factorLevels)
# The model formula
formula <- ArrDelay ~ CRSDepTime + DayOfWeek + CRSDepHour:DayOfWeek
# Train the model
mm <- rxLinMod(formula, data = in_df, transformFunc = NULL, transformVars = NULL)
# Store the model into the database
# rdata needs to be created beforehand
conStr <- paste0("Driver={ODBC Driver 13 for SQL Server};Server=.;",
"Database=RevoTestDB;Trusted_Connection=Yes;")
out.table = "rdata"
# write the model to the table
ds = RxOdbcData(table = out.table, connectionString = conStr)
rxWriteObject(ds, "linmod.v1", mm, keyName = "key",
valueName = "value")
return(NULL)
}
conStr <- "Driver={ODBC Driver 13 for SQL Server};Server=.;Database=RevoTestDB;Trusted_Connection=Yes;"
# create an InputData object for the input data frame in_df
indata <- InputData("in_df",
defaultQuery = paste0("select top 10000 ArrDelay,CRSDepTime,",
"DayOfWeek,CRSDepHour from cleanData"))
# create the sql server stored procedure object
trainSP1 <- StoredProcedure('train', "spTrain_df_to_df", indata,
dbName = "RevoTestDB",
connectionString = conStr,
filePath = ".")
# spRegisterSp and executeStoredProcedure do not require a connection string since we
# provided one when we created trainSP1
registerStoredProcedure(trainSP1)
executeStoredProcedure(trainSP1, verbose = TRUE)
############# Example 2 #############
# score1 makes a batch prediction given clean data(indata),
# model object(model_param), and the new name of the variable
# that is being predicted
score1 <- function(in_df, model_param, predVarNameInParam) {
factorLevels <- c("Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday")
in_df[,"DayOfWeek"] <- factor(in_df[,"DayOfWeek"], levels=factorLevels)
mm <- rxReadObject(as.raw(model_param))
# Predict
result <- rxPredict(modelObject = mm,
data = in_df,
outData = NULL,
predVarNames = predVarNameInParam,
extraVarsToWrite = c("ArrDelay"),
writeModelVars = TRUE,
overwrite = TRUE)
return(list(result = result, pvOutParam = mm$f.pvalue))
}
# create an InputData object for the input data frame in_df
indata <- InputData(name = "in_df", defaultQuery = "SELECT top 10 * from cleanData")
# create InputParameter objects for model_param and predVarNameInParam
model <- InputParameter("model_param", "raw",
defaultQuery = paste("select top 1 value from rdata",
"where [key] = 'linmod.v1'"))
predVarNameInParam <- InputParameter("predVarNameInParam", "character")
# create OutputData object for the data frame inside the return list
outData <- OutputData("result")
# create OutputParameter object for non data frame variable inside the return list
pvOutParam <- OutputParameter("pvOutParam", "numeric")
scoreSP1 <- StoredProcedure(score1, "spScore_df_param_df", indata, model, predVarNameInParam, outData, pvOutParam,
filePath = ".")
conStr <- "Driver={ODBC Driver 13 for SQL Server};Server=.;Database=RevoTestDB;Trusted_Connection=Yes;"
# connection string necessary for registrations and execution
# since we did not pass it to StoredProcedure
registerStoredProcedure(scoreSP1, conStr)
model <- executeStoredProcedure(scoreSP1, predVarNameInParam = "ArrDelayEstimate", connectionString = conStr, verbose = TRUE)
model$data
model$params[[1]]
## End(Not run)