spark-submit can accept any Spark property using the -conf/-cįlag, but uses special flags for properties that play a part in launching the Spark application.
Tool support two ways to load configurations dynamically. bin/spark-submit -name "My app" -master local -conf = false -conf "=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps" myApp.jar Then, you can supply configuration values at runtime. Spark allows you to simply create an empty conf: val sc = new SparkContext ( new SparkConf ()) Instance, if you’d like to run the same application with different masters or differentĪmounts of memory. In some cases, you may want to avoid hard-coding certain configurations in a SparkConf. See documentation of individual configuration properties. While numbers without units are generally interpreted as bytes, a few are interpreted as KiB or MiB. Properties that specify some time duration should be configured with a unit of time. Note that we can have more than 1 thread in local mode, and in cases like Spark Streaming, we mayĪctually require more than 1 thread to prevent any sort of starvation issues. setAppName ( "CountingSheep" ) val sc = new SparkContext ( conf ) Which can help detect bugs that only exist when we run in a distributed context. Note that we run with local, meaning two threads - which represents “minimal” parallelism, For example, we could initialize an application with two threads as follows: master URL and application name), as well as arbitrary key-value pairs through the SparkConf allows you to configure some of the common properties These properties can be set directly on a Spark properties control most application settings and are configured separately for eachĪpplication. Logging can be configured through log4j2.properties.The IP address, through the conf/spark-env.sh script on each node. Environment variables can be used to set per-machine settings, such as.Spark properties control most application parameters and can be set by using.Spark provides three locations to configure the system: External Shuffle service(server) side configuration options.Custom Resource Scheduling and Configuration Overview.Inheriting Hadoop Cluster Configuration.
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