| unionAll {SparkR} | R Documentation |
Return a new DataFrame containing the union of rows in this DataFrame and another DataFrame. This is equivalent to 'UNION ALL' in SQL. Note that this does not remove duplicate rows across the two DataFrames.
Returns a new DataFrame containing rows of all parameters.
## S4 method for signature 'DataFrame,DataFrame' unionAll(x, y) ## S4 method for signature 'DataFrame' rbind(x, ..., deparse.level = 1) unionAll(x, y) rbind(..., deparse.level = 1)
x |
A Spark DataFrame |
y |
A Spark DataFrame |
A DataFrame containing the result of the union.
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; ncol;
persist; printSchema;
registerTempTable,
registerTempTable; rename,
rename, withColumnRenamed,
withColumnRenamed;
repartition; sample,
sample, sample_frac,
sample_frac;
saveAsParquetFile,
saveAsParquetFile,
write.parquet, write.parquet;
saveAsTable, saveAsTable;
saveDF, saveDF,
write.df, write.df;
selectExpr; showDF,
showDF; show,
show,
show,GroupedData-method;
take; transform,
withColumn, withColumn;
unpersist; write.json,
write.json
## Not run:
##D sc <- sparkR.init()
##D sqlContext <- sparkRSQL.init(sc)
##D df1 <- read.json(sqlContext, path)
##D df2 <- read.json(sqlContext, path2)
##D unioned <- unionAll(df, df2)
## End(Not run)