When submitting a Spark job using "spark-submit," you have multiple options for adding additional JAR files:
Options like "--driver-class-path" and "--spark.executor.extraClassPath" are used to modify the ClassPath. Adding a JAR to the ClassPath allows your code to find and load the classes within that JAR.
The separator for multiple JAR files in ClassPath settings depends on the operating system. On Linux, it's a colon (':'), while on Windows, it's a semicolon (';').
JAR files added via "--jars" or "SparkContext.addJar()" are automatically distributed to all worker nodes in client mode. In cluster mode, you need to ensure the JAR files are accessible to all nodes via an external source like HDFS or S3. "SparkContext.addFile()" is useful for distributing non-dependency files.
"spark-submit" accepts JAR files using various URI schemes, including local file paths, HDFS, HTTP, HTTPS, and FTP.
Additional JAR files are copied to the working directory of each SparkContext on worker nodes, typically under "/var/run/spark/work."
Properties set directly on the SparkConf have the highest precedence, followed by flags passed to "spark-submit," and then options in "spark-defaults.conf."
In client mode, it's safe to use multiple options to add JAR files to both the driver and worker nodes. However, in cluster mode, you may need to use additional methods to ensure the JAR files are available to all worker nodes.
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