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我正在执行大型 ffdf 对象的子集，我注意到当我使用subset.ff时，它会生成大量的 NA。我通过使用ffwhich尝试了另一种方法，结果更快，并且没有生成 NA。这是我的测试：

library(ffbase)
# deals is the ffdf I would like to subset
unique(deals$COMMODITY)
ff (open) integer length=7 (7) levels: CASH CO2 COAL ELEC GAS GCERT OIL
  [1]   [2]   [3]   [4]   [5]   [6]   [7] 
CASH  CO2   COAL  ELEC  GAS   GCERT OIL   

# Using subset.ff
started.at=proc.time()
deals0 <- subset.ff(deals,deals$COMMODITY %in% c("CASH","COAL","CO2","ELEC","GCERT"))
cat("Finished in",timetaken(started.at),"\n")
Finished in 12.640sec
# NAs are generated
unique(deals0$COMMODITY)
ff (open) integer length=8 (8) levels: CASH CO2 COAL ELEC GAS GCERT OIL <NA>
  [1]   [2]   [3]   [4]   [5]   [6]   [7]   [8] 
CASH  CO2   COAL  ELEC  GAS   GCERT OIL   NA    

# Subset using ffwhich
started.at=proc.time()
idx <- ffwhich(deals,COMMODITY %in% c("CASH","COAL","CO2","ELEC","GCERT"))
deals1 <- deals[idx,]
cat("Finished in",timetaken(started.at),"\n")
Finished in 3.130sec
# No NAs are generated
unique(deals1$COMMODITY)
ff (open) integer length=7 (7) levels: CASH CO2 COAL ELEC GAS GCERT OIL
  [1]   [2]   [3]   [4]   [5]   [6]   [7] 
CASH  CO2   COAL  ELEC  GAS   GCERT OIL

知道为什么会这样吗？

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1 回答 1

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subset.ff可能正在使用[和您的标准，但不包括!is.na(.)子句。“[”的默认值是返回标准向量为 TRUE 或 NA 的项目。常规的子集函数添加了一个!is.na(.)子句，但也许 ffbase 的作者没有解决这个问题。

于 2012-11-23T16:33:02.447 回答