Writes a Spark DataFrame into a JDBC table
spark_write_jdbc
Description
Writes a Spark DataFrame into a JDBC table
Usage
spark_write_jdbc(
x,
name,
mode = NULL,
options = list(),
partition_by = NULL,
...
)Arguments
| Arguments | Description |
|---|---|
| x | A Spark DataFrame or dplyr operation |
| name | The name to assign to the newly generated table. |
| mode | A character element. Specifies the behavior when data or table already exists. Supported values include: ‘error’, ‘append’, ‘overwrite’ and ignore. Notice that ‘overwrite’ will also change the column structure. For more details see also https://spark.apache.org/docs/latest/sql-programming-guide.html#save-modes for your version of Spark. |
| options | A list of strings with additional options. |
| partition_by | A character vector. Partitions the output by the given columns on the file system. |
| … | Optional arguments; currently unused. |
See Also
Other Spark serialization routines: collect_from_rds(), spark_insert_table(), spark_load_table(), spark_read(), spark_read_avro(), spark_read_binary(), spark_read_csv(), spark_read_delta(), spark_read_image(), spark_read_jdbc(), spark_read_json(), spark_read_libsvm(), spark_read_orc(), spark_read_parquet(), spark_read_source(), spark_read_table(), spark_read_text(), spark_save_table(), spark_write_avro(), spark_write_csv(), spark_write_delta(), spark_write_json(), spark_write_orc(), spark_write_parquet(), spark_write_source(), spark_write_table(), spark_write_text()
Examples
sc <- spark_connect(
master = "local",
config = list(
`sparklyr.shell.driver-class-path` = "/usr/share/java/mysql-connector-java-8.0.25.jar"
)
)
spark_write_jdbc(
sdf_len(sc, 10),
name = "my_sql_table",
options = list(
url = "jdbc:mysql://localhost:3306/my_sql_schema",
driver = "com.mysql.jdbc.Driver",
user = "me",
password = "******",
dbtable = "my_sql_table"
)
)