Tip
|
Refer to Spark Configuration in the official documentation for an extensive coverage of how to configure Spark and user programs. |
Caution
|
TODO
|
There are three ways to configure Spark and user programs:
-
Spark Properties - use Web UI to learn the current properties.
-
…
There are two mandatory settings of any Spark application that have to be defined before this Spark application could be run — spark.master and spark.app.name.
Every user program starts with creating an instance of SparkConf
that holds the master URL to connect to (spark.master
), the name for your Spark application (that is later displayed in web UI and becomes spark.app.name
) and other Spark properties required for proper runs. The instance of SparkConf
can be used to create SparkContext.
Tip
|
Start Spark shell with
Use |
You can query for the values of Spark properties in Spark shell as follows:
scala> sc.getConf.getOption("spark.local.dir")
res0: Option[String] = None
scala> sc.getConf.getOption("spark.app.name")
res1: Option[String] = Some(Spark shell)
scala> sc.getConf.get("spark.master")
res2: String = local[*]
There are the following ways to set up properties for Spark and user programs (in the order of importance from the least important to the most important):
-
conf/spark-defaults.conf
- the default -
--conf
or-c
- the command-line option used byspark-shell
andspark-submit
-
SparkConf
The default Spark configuration is created when you execute the following code:
import org.apache.spark.SparkConf
val conf = new SparkConf
It simply loads spark.*
system properties.
You can use conf.toDebugString
or conf.getAll
to have the spark.*
system properties loaded printed out.
scala> conf.getAll
res0: Array[(String, String)] = Array((spark.app.name,Spark shell), (spark.jars,""), (spark.master,local[*]), (spark.submit.deployMode,client))
scala> conf.toDebugString
res1: String =
spark.app.name=Spark shell
spark.jars=
spark.master=local[*]
spark.submit.deployMode=client
scala> println(conf.toDebugString)
spark.app.name=Spark shell
spark.jars=
spark.master=local[*]
spark.submit.deployMode=client