| write.df {SparkR} | R Documentation |
The data source is specified by the 'source' and a set of options (...). If 'source' is not specified, the default data source configured by spark.sql.sources.default will be used.
## S4 method for signature 'DataFrame,character' write.df(df, path, source = NULL, mode = "error", ...) ## S4 method for signature 'DataFrame,character' saveDF(df, path, source = NULL, mode = "error", ...) write.df(df, path, ...) saveDF(df, path, source = NULL, mode = "error", ...) write.df(df, path, ...)
df |
A SparkSQL DataFrame |
path |
A name for the table |
source |
A name for external data source |
mode |
One of 'append', 'overwrite', 'error', 'ignore' save mode (it is 'error' by default) |
Additionally, mode is used to specify the behavior of the save operation when
data already exists in the data source. There are four modes:
append: Contents of this DataFrame are expected to be appended to existing data.
overwrite: Existing data is expected to be overwritten by the contents of this DataFrame.
error: An exception is expected to be thrown.
ignore: The save operation is expected to not save the contents of the DataFrame
and to not change the existing data.
Other DataFrame functions: $,
$<-, select,
select,
select,DataFrame,Column-method,
select,DataFrame,list-method,
selectExpr; DataFrame-class,
dataFrame, groupedData;
[, [, [[,
subset; agg,
agg,
count,GroupedData-method,
summarize, summarize;
arrange, arrange,
arrange, orderBy,
orderBy; as.data.frame,
as.data.frame,DataFrame-method;
attach,
attach,DataFrame-method;
cache; collect;
colnames, colnames,
colnames<-, colnames<-,
columns, names,
names<-; coltypes,
coltypes, coltypes<-,
coltypes<-; columns,
dtypes, printSchema,
schema, schema;
count, nrow;
describe, describe,
describe, summary,
summary,
summary,PipelineModel-method;
dim; distinct,
unique; dropna,
dropna, fillna,
fillna, na.omit,
na.omit; dtypes;
except, except;
explain, explain;
filter, filter,
where, where;
first, first;
groupBy, groupBy,
group_by, group_by;
head; insertInto,
insertInto; intersect,
intersect; isLocal,
isLocal; join;
limit, limit;
merge, merge;
mutate, mutate,
transform, transform;
ncol; persist;
printSchema; rbind,
rbind, unionAll,
unionAll; registerTempTable,
registerTempTable; rename,
rename, withColumnRenamed,
withColumnRenamed;
repartition; sample,
sample, sample_frac,
sample_frac;
saveAsParquetFile,
saveAsParquetFile,
write.parquet, write.parquet;
saveAsTable, saveAsTable;
selectExpr; showDF,
showDF; show,
show,
show,GroupedData-method; str;
take; unpersist;
withColumn, withColumn;
write.json, write.json;
write.text, write.text
## Not run:
##D sc <- sparkR.init()
##D sqlContext <- sparkRSQL.init(sc)
##D path <- "path/to/file.json"
##D df <- read.json(sqlContext, path)
##D write.df(df, "myfile", "parquet", "overwrite")
##D saveDF(df, parquetPath2, "parquet", mode = saveMode, mergeSchema = mergeSchema)
## End(Not run)