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"contents": "/*Queries*/\n\nSELECT table_name \nFROM all_tables \nWHERE owner='LOYALTY';\n\n##Errores \n\nSELECT DISTINCT ODI_ERR_MESS\nFROM E$_STAGINGPB;\n\nSELECT count(1)\nFROM E$_STAGINGPB;\n\nSELECT count(1)\nFROM E$_STAGINGPE\nUNION ALL\nSELECT count(1)\nFROM E$_STAGINGPB; \n\n\nSELECT count(1)\nFROM PUNTOSEXITO;\n\nSELECT count(1)\nFROM PUNTOSBANCOLOMBIA;\n\nSELECT count(1)\nFROM STAGINGPE;\n\nSELECT count(1)\nFROM STAGINGPB;\n\n\nSELECT NRODOCUMENTO, count(NRODOCUMENTO) as VECES\nFROM E$_STAGINGPB\nGROUP BY NRODOCUMENTO;\n\n\nSELECT NRODOCUMENTO, NOMBRES, APELLIDOS\nFROM E$_STAGINGPB\nWHERE NRODOCUMENTO=39004476;\n\nSELECT OrigenInfo, count(OrigenInfo) as VECES\nFROM PuntosLoyalty\nGROUP BY OrigenInfo;\n\n\nTRUNCATE TABLE PuntosLoyalty;\nTRUNCATE TABLE E$_STAGINGPB;\nTRUNCATE TABLE E$_STAGINGPE;\n\n",
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"contents": " \n \nlibrary(RODBC)\n# Connect via RODBC with configured DSN\ndb <- odbcConnect(\"teradata64\", uid = \"uid\", pwd = \"pwd\")\n \n \n# Read results\nquery <-\n \n\"SELECT \n A.ID_FECHA,\n A.ID_UOP,\n A.ID_ITEM,\n A.CANTIDAD,\n A.VALOR_DESCUENTO,\n B.NOM_FECHA,\n C.COD_ITEM_SIC,\n C.NOM_CLASE_MERC,\n C.COD_DEPTO,\n D.FERIADO,\n D.ID_FERIADO\nFROM SUPER.TLOG_V2 A\nINNER JOIN SUPER.DIM_FECHA B\nON A.ID_FECHA = B.ID_FECHA\nINNER JOIN SUPER.DIM_ITEM C\nON A.ID_ITEM = C.ID_ITEM\nLEFT JOIN SUPER.FERIADOS D\nON D.FECHA= B.NOM_FECHA;\"\n \n#No existe la table TLOG_V2. Seria FAC_VENTA. Tampoco esta la tabla FERIADOS. 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1, paste( \"lead.1.\", h, sep = \"\" ) ] <- 1\n b.item[ is.na( b.item[, paste( \"lead.1.\", h, sep = \"\" ) ]) , paste( \"lead.1.\", h, sep = \"\" ) ] <- 0\n \n b.item[which(b.item[, h] > 0) - 2, paste( \"lead.2.\", h, sep = \"\" ) ] <- 1\n b.item[ is.na( b.item[, paste( \"lead.2.\", h, sep = \"\" ) ]) , paste( \"lead.2.\", h, sep = \"\" ) ] <- 0\n \n b.item[which(b.item[, h] > 0) - 3, paste( \"lead.3.\", h, sep = \"\" )] <- 1\n b.item[ is.na( b.item[, paste( \"lead.3.\", h, sep = \"\" ) ]) , paste( \"lead.3.\", h, sep = \"\" ) ] <- 0\n \n }\n }, error = function(e) {\n \n })\n \n n.b <- names(b.item)\n \n lag <- n.b[(grep(\"lag.\", names(b.item) ))]\n lead <- n.b[(grep(\"lead.\", names(b.item) ))]\n \n # defino variables para modelos\n \n \n v.mod.1 <- c(dias, me, an, fe, \"promo\", lag, lead)\n \n # defino periodo para el forecast\n periodo <- 14\n \n #Lm con step\n if (length(b.item[,1]) <= 20){\n \n #print(\"check\")\n \n fecha.n <- seq.Date(fecha.base, fecha.base + periodo , by = 1)[-1]\n \n res.par <- data.frame( nom_fec = fecha.n,\n NOM_CLASE_MERC = rep(unique(b.item$NOM_CLASE_MERC)[1], length(fecha.n) ) ,\n COD_DEPTO = rep(unique(b.item$COD_DEPTO)[1], length(fecha.n) ),\n ID_UOP = rep(unique(b.item$ID_UOP)[1], length(fecha.n) ),\n ID_ITEM = rep(unique(b.item$COD_ITEM_SIC)[1], length(fecha.n) ),\n PRED = rep(mean(b.item$CANTIDAD), length(fecha.n) ) )\n res.par\n \n } else {\n \n \n lm.mod.1 <- tryCatch( {\n \n lm(b.item$CANTIDAD ~ ., data = b.item[, v.mod.1 ])\n \n }, error = function(e) {\n \n lm.mod.1 <- lm(b.item$CANTIDAD ~ ., data = b.item[, v.mod.1 ])\n }\n \n )\n \n \n nombres <- attr(lm.mod.1$terms,\"term.labels\")\n #print(nombres)\n \n #armo nueva data para pred\n fecha.n <- seq.Date(fecha.base, fecha.base + periodo , by = 1)[-1]\n nueva <- data.frame( nom_fec = fecha.n )\n nueva[,\"anio\"] <- as.numeric(format(nueva$nom_fec,'%Y'))\n nueva[,\"mes\"] <- as.numeric(format(nueva$nom_fec,'%m'))\n nueva[,\"dia.sem\"] <- weekdays(nueva$nom_fec, abbreviate = T)\n \n # binario de nombres\n \n for (y in nombres){\n \n nueva[, y] <- 0\n \n }\n \n \n \n # binario de dias\n dias.n <- unique(nueva$dia.sem)\n \n for (d in dias.n){\n \n nueva[, d ] <- ifelse(nueva$dia.sem == d, 1, 0)\n \n }\n \n # binario de meses\n \n for (m in meses){\n \n nueva[, paste( \"mes.\", m, sep = \"\" ) ] <- 0\n \n }\n \n meses.n <- unique(nueva$mes)\n \n for (m in meses.n){\n \n nueva[, paste( \"mes.\", m, sep = \"\" ) ] <- ifelse(nueva$mes == m, 1, 0)\n \n }\n \n # binario de anios\n \n \n for (a in anios){\n \n nueva[, paste( \"anio.\", a, sep = \"\" ) ] <- 0\n \n }\n \n anios.n <- unique(nueva$anio)\n \n for (a in anios.n){\n \n nueva[, paste( \"anio.\", a, sep = \"\" ) ] <- ifelse(nueva$anio == a, 1, 0)\n \n }\n \n # binario de feriados\n \n for (f in feria){\n \n nueva[, paste( \"fer.\", f, sep = \"\" ) ] <- 0\n \n }\n \n \n \n # modelo predictivo\n nueva.p <- data.frame(nueva[, nombres ])\n names(nueva.p) <- nombres\n \n f.mod.1 <- round(predict(lm.mod.1, h = periodo, newdata = nueva.p),0)\n \n fecha.n <- seq.Date(fecha.base, fecha.base + periodo , by = 1)[-1]\n \n res.par <- data.frame( nom_fec = fecha.n,\n NOM_CLASE_MERC = rep(unique(b.item$NOM_CLASE_MERC)[1], length(fecha.n) ) ,\n COD_DEPTO = rep(unique(b.item$COD_DEPTO)[1], length(fecha.n) ),\n ID_UOP = rep(unique(b.item$ID_UOP)[1], length(fecha.n) ),\n ID_ITEM = rep(unique(b.item$COD_ITEM_SIC)[1], length(fecha.n) ),\n PRED = rep(mean(b.item$CANTIDAD), length(fecha.n) ) )\n res.par\n }\n }\n \n data_c <- lapply(item.list, f.items )\n \n resultado <- data.frame(do.call(\"rbind\", data_c))\n resultado\n \n}\n \n#funcion para locales - para paralelizar por local -\n####\n \n locales <- unique(b.prueba$ID_UOP)\n \n l.local <- list()\n \n system.time(\n \n for (l in locales){\n \n print(l)\n b.local <- b.prueba[b.prueba$ID_UOP == l, ]\n l.local[[which(locales == l)]] <- p.item(b.local)\n \n }\n \n )\n \n \n#data final con el forecast a 14 dias\n resultado <- data.frame(do.call(\"rbind\", l.local))\n \n \n \n# Guardar resultados en Teradata\n \n # Connect via RODBC with configured DSN\n db <- odbcConnect(\"teradata64\", uid = \"uid\", pwd = \"pwd\") \n \ntabla.db <-\n \n \" CREATE TABLE SUPER.RESULTADO (\n NOM_CLASE_MERC CHAR(40) UTF8, \n COD_DEPTO DOUBLE PRECISION,\n NOM_FEC CHAR(20),\n ID_UOP NUMBER,\n ID_ITEM NUMBER,\n PRED NUMBER\n ); \"\n \nsqlQuery(db, tabla.db)\nodbcClose(db)\n",
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"contents": "library(RODBC)\nlibrary(forecast)\n# Connect via RODBC with configured DSN\ndb <- odbcConnect(\"teradata64\", uid = \"uid\", pwd = \"pwd\")\n \n \n# Read results\nquery <- \n \n\"SELECT \n A.ID_FECHA,\n A.ID_UOP,\n A.ID_ITEM,\n A.CANTIDAD,\n A.VALOR_DESCUENTO,\n B.NOM_FECHA,\n C.COD_ITEM_SIC,\n C.NOM_CLASE_MERC,\n C.COD_DEPTO,\n D.FERIADO,\n D.ID_FERIADO\nFROM SUPER.TLOG_V2 A\nINNER JOIN SUPER.DIM_FECHA B\nON A.ID_FECHA = B.ID_FECHA \nINNER JOIN SUPER.DIM_ITEM C\nON A.ID_ITEM = C.ID_ITEM\nLEFT JOIN SUPER.FERIADOS D\nON D.FECHA= B.NOM_FECHA;\"\n \n \n## connect to Teradata and extraxt data\nb.prueba <- sqlQuery(db, query )\n \nodbcClose(db)\n \n####\n \n \n#### Funcion simple\nb.prueba <- b.prueba[, c(\"NOM_FECHA\", \"CANTIDAD\", \"COD_ITEM_SIC\")]\n \n f.items <- function(b.item){\n \n if (is.na( x <- as.Date(b.item$NOM_FECHA, format = \"%Y-%m-%d\")[1]) == T ){\n \n b.item[,\"fecha\"] <- as.Date(b.item$NOM_FECHA, format = \"%m/%d/%Y\")\n \n } else { \n \n b.item[,\"fecha\"] <- as.Date(b.item$NOM_FECHA, format = \"%Y-%m-%d\")\n \n }\n \n \n periodo <- 14\n \n fecha.base <- max(b.item$fecha)\n #ch <- ifelse( (length(b.item[,1]) <= 20), \"si\", \"no\")\n \n #print(paste(\"local: \", l, \", item: \", unique(b.item$ID_ITEM), \", < 20: \", ch ))\n \n # defino periodo para el forecast\n \n #Lm con step\n if (length(b.item[,1]) <= 20){\n \n #print(\"check\")\n \n fecha.n <- seq.Date(fecha.base, fecha.base + periodo , by = 1)[-1]\n \n res.par <- data.frame( nom_fec = fecha.n,\n PRED = round(rep(mean(b.item$CANTIDAD),2), length(fecha.n) ) )\n \n #res.par <- paste(res.par[,1], res.par[,2], res.par[,3], res.par[,4], res.par[,5], res.par[,6], sep = \";\")\n \n res.par\n \n } else {\n \n \n lm.mod.1 <- forecast(auto.arima(b.item$CANTIDAD, trace = F), h = periodo)\n \n fecha.n <- seq.Date(fecha.base, fecha.base + periodo , by = 1)[-1]\n \n res.par <- data.frame( nom_fec = fecha.n,\n PRED = round(as.numeric( lm.mod.1$mean, 2) ) )\n \n #res.par <- paste(res.par[,1], res.par[,2], res.par[,3], res.par[,4], res.par[,5], res.par[,6], sep = \";\")\n \n res.par\n } \n }\n \n \n \n#funcion para locales - para paralelizar por local -####\n \n \n item.list <- split(b.prueba, b.prueba$COD_ITEM_SIC)\n system.time(data_c <- lapply(item.list, f.items ))\n \n#data final con el forecast a 14 dias \n \n resultado <- data.frame(do.call(\"rbind\", data_c))\n resultado\n \n \n \n# Guardar resultados en Teradata\n \n # Connect via RODBC with configured DSN\n db <- odbcConnect(\"teradata64\", uid = \"uid\", pwd = \"pwd\") \n \ntabla.db <- \n \n \" CREATE TABLE SUPER.RESULTADO (\n NOM_CLASE_MERC CHAR(40) UTF8, \n COD_DEPTO DOUBLE PRECISION,\n NOM_FEC CHAR(20),\n ID_UOP NUMBER,\n ID_ITEM NUMBER,\n PRED NUMBER\n ); \"\n \nsqlQuery(db, tabla.db)\nodbcClose(db) \n",
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