Return a vector of column names.
colnames(x, do.NULL = TRUE, prefix = "col")colnames(x) <- value
columns(x)
# S4 method for SparkDataFrame
columns(x)
# S4 method for SparkDataFrame
names(x)
# S4 method for SparkDataFrame
names(x) <- value
# S4 method for SparkDataFrame
colnames(x)
# S4 method for SparkDataFrame
colnames(x) <- value
a SparkDataFrame.
currently not used.
currently not used.
a character vector. Must have the same length as the number of columns to be renamed.
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
attach,SparkDataFrame-method,
broadcast(),
cache(),
checkpoint(),
coalesce(),
collect(),
coltypes(),
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(),
unionAll(),
unionByName(),
union(),
unpersist(),
withColumn(),
withWatermark(),
with(),
write.df(),
write.jdbc(),
write.json(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
# NOT RUN {
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
columns(df)
colnames(df)
# }
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