write.jdbc: Save the content of SparkDataFrame to an external database...

In SparkR: R Front End for 'Apache Spark'

Description

Save the content of the SparkDataFrame to an external database table via JDBC. Additional JDBC database connection properties can be set (...)

Usage

write.jdbc(x, url, tableName, mode = "error", ...)

## S4 method for signature 'SparkDataFrame,character,character'
write.jdbc(x, url, tableName, mode = "error", ...)

Arguments

x	a SparkDataFrame.
url	JDBC database url of the form jdbc:subprotocol:subname.
tableName	the name of the table in the external database.
mode	one of 'append', 'overwrite', 'error', 'errorifexists', 'ignore' save mode (it is 'error' by default)
...	additional JDBC database connection properties.

Details

Also, 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 SparkDataFrame are expected to be appended to existing data.

• 'overwrite': Existing data is expected to be overwritten by the contents of this SparkDataFrame.

• 'error' or 'errorifexists': An exception is expected to be thrown.

• 'ignore': The save operation is expected to not save the contents of the SparkDataFrame and to not change the existing data.

Note

write.jdbc since 2.0.0

See Also

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(), 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.json(), write.orc(), write.parquet(), write.stream(), write.text()

Examples

## Not run: 
sparkR.session()
jdbcUrl <- "jdbc:mysql://localhost:3306/databasename"
write.jdbc(df, jdbcUrl, "table", user = "username", password = "password")

## End(Not run)

SparkR documentation built on June 3, 2021, 5:05 p.m.