我想将数据(data.frame)从长格式转换为宽格式,并将“ITEM”的值作为列和值(“ITEM2”)(见下文):

Long format

Wide format

因此我使用包reshape2中的dcast-function:

df <= dcast(df,SEQUENCEID + EVENTID ~ ITEM, value.var="ITEM2")

这样做一切正常 .

但是在我的数据框架中有7m的数据记录,我在内存限制方面遇到了困难 . 因此我决定在ffdf中转换我的data.frame并使用包ffbase中的ffdfdply函数来转换帧 .

为了确保每个拆分具有相同顺序的相同列,我提前从“ITEM”中提取值,如果不存在则附加N / A列,并按字母顺序排列所有列 .

整个代码下面:

#Extract items 
item<-as.character(unique(lo_raw$ITEM))

#Transform to ffdf
ff_raw<-as.ffdf(lo_raw)
ff_raw$SEQUENCEID<-as.character.ff(ff_raw$SEQUENCEID)

#Function dcast
castff<-function(df,item){
   df=dcast(df,SEQUENCEID + EVENTID ~ ITEM, value.var="ITEM2")

   for(i in item){
      if (!(i %in% colnames(df))){
      df[,i]<-NA
   }
  }

  df<-df[,order(colnames(df))]
  df
}

#Apply dcast
ff_pivot<-ffdfdply(x=ff_raw,split=ff_raw$SEQUENCEID,FUN=function(df,item) castff(df,item),item=item,BATCHBYTES=1000000,trace=TRUE)

不幸的是,我将第二次拆分的结果附加到第一次(带跟踪)时出现以下错误:

2016-12-08 09:25:35, calculating split sizes
2016-12-08 09:25:37, building up split locations
2016-12-08 09:25:51, working on split 1/139, extracting data in RAM of 106 split elements, totalling, 0.00093 GB, while max specified data specified using BATCHBYTES is 0.00093 GB
2016-12-08 09:25:52, ... applying FUN to selected data
2016-12-08 09:25:55, ... appending result to the output ffdf
2016-12-08 09:26:02, working on split 2/139, extracting data in RAM of 172 split elements, totalling, 0.00093 GB, while max specified data specified using BATCHBYTES is 0.00093 GB
2016-12-08 09:26:03, ... applying FUN to selected data
2016-12-08 09:26:05, ... appending result to the output ffdf
Error in ff(vmode = "integer", length = length(x), levels = as.character(levs)) : unable to open
In addition: Warning message:
In is.na(levs) : is.na() applied to non-(list or vector) of type 'NULL'

只计算一个记录较少的分割而不附加工作正常 .

有人可以帮忙吗?

谢谢 .