| repartition {SparkR} | R Documentation |
The following options for repartition are possible:
1. Return a new SparkDataFrame that has exactly numPartitions.
2. Return a new SparkDataFrame hash partitioned by
the given columns into numPartitions.
3. Return a new SparkDataFrame hash partitioned by the given column(s),
using spark.sql.shuffle.partitions as number of partitions.
repartition(x, ...)
## S4 method for signature 'SparkDataFrame'
repartition(x, numPartitions = NULL, col = NULL, ...)
x |
a SparkDataFrame. |
... |
additional column(s) to be used in the partitioning. |
numPartitions |
the number of partitions to use. |
col |
the column by which the partitioning will be performed. |
repartition since 1.4.0
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
attach,SparkDataFrame-method,
broadcast(),
cache(),
checkpoint(),
coalesce(),
collect(),
colnames(),
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(),
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:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D newDF <- repartition(df, 2L)
##D newDF <- repartition(df, numPartitions = 2L)
##D newDF <- repartition(df, col = df$"col1", df$"col2")
##D newDF <- repartition(df, 3L, col = df$"col1", df$"col2")
## End(Not run)