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BootStarpMedian.R

+
+
+# BootStarpMedian function 
+BootStarpMedian <- function(x) {
+  x <- as.vector(x)
+  n <- length(x)
+  med_vec <- replicate(n=1000,median(base::sample(x=x,size=n,replace=T)))
+  return(mean(med_vec))
+}
+
+#----------------------
+# app std
+#----------------------
+
+# loading data 
+
+app_query_sql <- "select appid,
+                         category_id,
+                         isgame ,
+                         ds,
+                         sum(num_install) / sum(dupnum_click_all) as ins_rate
+                   from tkdm.tkdm_data_active_detial_day
+                   where ds between '2017-02-20' and '2017-02-26'
+                   group by appid,category_id,isgame,ds
+"
+
+# app_query_result
+app_query_result <- sql(app_query_sql)
+# 
+app_schema <-  structType(structField("category_id_app", "integer"), 
+                      structField("isgame_app", "integer"),
+                      structField("ins_rate_std", "double") )
+# aggregate
+app <- gapply(x=app_query_result,
+         cols=c('category_id','isgame'),
+         function(key,x){
+              data.frame(key,BootStarpMedian(x$ins_rate),stringsAsFactors = FALSE )
+              },
+         schema=app_schema)
+
+# collect(yy)
+app_output <- join(x=app_query_result,
+                   y=app,
+                   joinExpr=app_query_result$category_id==app$category_id_app & app_query_result$isgame==app$isgame_app,
+                   joinType='inner'
+                   )
+
+
+app_output <- select(app_output,'appid','category_id','isgame','ins_rate_std','ds')
+
+#----------------------
+# cid std
+#----------------------
+
+# loading data 
+cid_query_sql <- "select appid,
+                     cid, 
+                     category_id,
+                     isgame ,
+                     ins_rate 
+                   from tkdm.tkdm_data_active_detial_day
+                   where ds between '2017-02-20' and '2017-02-26'
+
+"
+# result of query sql
+aa <- sql(cid_query_sql)
+# output schema
+cid_schema <-  structType(structField("category_id_cid", "integer"), 
+                      structField("isgame_cid", "integer"),
+                      structField("cid_cid", "integer"),
+                      structField("ins_rate_std", "double") )
+# aggregate
+cid <- gapply(x=aa,
+         cols=c('category_id','isgame','cid'),
+         function(key,x){
+              data.frame(key,BootStarpMedian(x$ins_rate),stringsAsFactors = FALSE )
+              },
+         schema=cid_schema)
+
+# collect(cid)
+cid_output <- join(x=aa,y=cid,
+                   joinExpr=aa$category_id==cid$category_id_cid & aa$isgame==cid$isgame_cid & aa$cid==cid$cid_cid,
+                   joinType='inner'
+                   )
+
+# cid_output <- cid_output[,c('appid','cid','category_id','isgame','ins_rate_std')]
+
+cid_output <- select(cid_output,'appid','cid','category_id','isgame','ins_rate_std','ds')
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