| coltypes {SparkR} | R Documentation |
Get column types of a SparkDataFrame
Set the column types of a SparkDataFrame.
coltypes(x) coltypes(x) <- value ## S4 method for signature 'SparkDataFrame' coltypes(x) ## S4 replacement method for signature 'SparkDataFrame,character' coltypes(x) <- value
x |
A SparkDataFrame |
value |
A character vector with the target column types for the given SparkDataFrame. Column types can be one of integer, numeric/double, character, logical, or NA to keep that column as-is. |
value A character vector with the column types of the given SparkDataFrame
coltypes since 1.6.0
coltypes<- since 1.6.0
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
attach,SparkDataFrame-method,
broadcast(),
cache(),
checkpoint(),
coalesce(),
collect(),
colnames(),
createOrReplaceTempView(),
crossJoin(),
cube(),
dapplyCollect(),
dapply(),
describe(),
dim(),
distinct(),
dropDuplicates(),
dropna(),
drop(),
dtypes(),
exceptAll(),
except(),
explain(),
filter(),
first(),
gapplyCollect(),
gapply(),
getNumPartitions(),
group_by(),
head(),
hint(),
histogram(),
insertInto(),
intersectAll(),
intersect(),
isLocal(),
isStreaming(),
join(),
limit(),
localCheckpoint(),
merge(),
mutate(),
ncol(),
nrow(),
persist(),
printSchema(),
randomSplit(),
rbind(),
rename(),
repartitionByRange(),
repartition(),
rollup(),
sample(),
saveAsTable(),
schema(),
selectExpr(),
select(),
showDF(),
show(),
storageLevel(),
str(),
subset(),
summary(),
take(),
toJSON(),
unionByName(),
union(),
unpersist(),
withColumn(),
withWatermark(),
with(),
write.df(),
write.jdbc(),
write.json(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
## Not run:
##D irisDF <- createDataFrame(iris)
##D coltypes(irisDF) # get column types
## End(Not run)
## Not run:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D coltypes(df) <- c("character", "integer") # set column types
##D coltypes(df) <- c(NA, "numeric") # set column types
## End(Not run)