filter {SparkR} | R Documentation |
Filter the rows of a SparkDataFrame according to a given condition.
filter(x, condition) where(x, condition) ## S4 method for signature 'SparkDataFrame,characterOrColumn' filter(x, condition) ## S4 method for signature 'SparkDataFrame,characterOrColumn' where(x, condition)
x |
A SparkDataFrame to be sorted. |
condition |
The condition to filter on. This may either be a Column expression or a string containing a SQL statement |
A SparkDataFrame containing only the rows that meet the condition.
filter since 1.4.0
where since 1.4.0
Other SparkDataFrame functions: SparkDataFrame-class
,
agg
, arrange
,
as.data.frame
,
attach,SparkDataFrame-method
,
cache
, checkpoint
,
coalesce
, collect
,
colnames
, coltypes
,
createOrReplaceTempView
,
crossJoin
, dapplyCollect
,
dapply
, describe
,
dim
, distinct
,
dropDuplicates
, dropna
,
drop
, dtypes
,
except
, explain
,
first
, gapplyCollect
,
gapply
, getNumPartitions
,
group_by
, head
,
hint
, histogram
,
insertInto
, intersect
,
isLocal
, isStreaming
,
join
, limit
,
merge
, mutate
,
ncol
, nrow
,
persist
, printSchema
,
randomSplit
, rbind
,
registerTempTable
, rename
,
repartition
, sample
,
saveAsTable
, schema
,
selectExpr
, select
,
showDF
, show
,
storageLevel
, str
,
subset
, take
,
toJSON
, union
,
unpersist
, withColumn
,
with
, write.df
,
write.jdbc
, write.json
,
write.orc
, write.parquet
,
write.stream
, write.text
Other subsetting functions: select
,
subset
## Not run:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D filter(df, "col1 > 0")
##D filter(df, df$col2 != "abcdefg")
## End(Not run)