spark_connect_method: Function that negotiates the connection with the Spark...

In rstudio/sparklyr: R Interface to Apache Spark

Function that negotiates the connection with the Spark back-end

Description

Function that negotiates the connection with the Spark back-end

Usage

spark_connect_method(
  x,
  method,
  master,
  spark_home,
  config,
  app_name,
  version,
  hadoop_version,
  extensions,
  scala_version,
  ...
)

Arguments

x	A dummy method object to determine which code to use to connect
method	The method used to connect to Spark. Default connection method is "shell" to connect using spark-submit, use "livy" to perform remote connections using HTTP, or "databricks" when using a Databricks clusters.
master	Spark cluster url to connect to. Use "local" to connect to a local instance of Spark installed via spark_install.
spark_home	The path to a Spark installation. Defaults to the path provided by the SPARK_HOME environment variable. If SPARK_HOME is defined, it will always be used unless the version parameter is specified to force the use of a locally installed version.
config	Custom configuration for the generated Spark connection. See spark_config for details.
app_name	The application name to be used while running in the Spark cluster.
version	The version of Spark to use. Required for "local" Spark connections, optional otherwise.
hadoop_version	Version of Hadoop to use
extensions	Extension R packages to enable for this connection. By default, all packages enabled through the use of sparklyr::register_extension will be passed here.
scala_version	Load the sparklyr jar file that is built with the version of Scala specified (this currently only makes sense for Spark 2.4, where sparklyr will by default assume Spark 2.4 on current host is built with Scala 2.11, and therefore ‘scala_version = ’2.12'' is needed if sparklyr is connecting to Spark 2.4 built with Scala 2.12)
...	Additional params to be passed to each 'spark_disconnect()' call (e.g., 'terminate = TRUE')

rstudio/sparklyr documentation built on April 30, 2024, 4:01 p.m.