java - spark-submit dependency resolution for spark-csv -


i doing small scala program converts csv parquet. using databricks spark-csv. here's build.sbt

name: = "tst"  version: = "1.0"  scalaversion: = "2.10.5"  librarydependencies++ = seq(   "org.apache.spark" % % "spark-core" % "1.6.1" % "provided",   "org.apache.spark" % % "spark-sql" % "1.6.1",   "com.databricks" % "spark-csv_2.10" % "1.5.0",   "org.apache.spark" % % "spark-hive" % "1.6.1",   "org.apache.commons" % "commons-csv" % "1.1",   "com.univocity" % "univocity-parsers" % "1.5.1",   "org.slf4j" % "slf4j-api" % "1.7.5" % "provided",   "org.scalatest" % % "scalatest" % "2.2.1" % "test",   "com.novocode" % "junit-interface" % "0.9" % "test",   "com.typesafe.akka" % "akka-actor_2.10" % "2.3.11",   "org.scalatest" % % "scalatest" % "2.2.1",   "com.holdenkarau" % % "spark-testing-base" % "1.6.1_0.3.3",   "com.databricks" % "spark-csv_2.10" % "1.5.0",   "org.joda" % "joda-convert" % "1.8.1"  )

after sbt package, when run command

spark-submit --master local[*] target/scala-2.10/tst_2.10-1.0.jar

i following error.

exception in thread "main" java.lang.classnotfoundexception: failed find data source: com.databricks.spark.csv. please find packages @ http://spark-packages.org

i can see com.databricks_spark-csv_2.10-1.5.0.jar file in ~/.ivy2/jars/ downloaded sbt package command

the source code of dataconversion.scala

import org.apache.spark.sql.sqlcontext  import org.apache.spark.sparkcontext  import org.apache.spark.sparkcontext._  import org.apache.spark.sparkconf    object dataconversion {    def main(args: array[string]) {      val conf =        new sparkconf()        .setappname("clusterscore")        .set("spark.storage.memoryfraction", "1")        val sc = new sparkcontext(conf)      val sqlc = new sqlcontext(sc)      val df = sqlc.read        .format("com.databricks.spark.csv")        .option("header", "true") // use first line of files header        .option("inferschema", "true") // automatically infer data types        .load("/tmp/cars.csv")      println(df.printschema)    }    }

i can spark-submit without error if specify --jars option explicit jar path. that's not ideal. please suggest.

use sbt-assembly plugin build "fat jar" containing all dependencies sbt assembly, , call spark-submit on that.

in general, when classnotfoundexception, try exploding jar created see what's in jar tvf target/scala-2.10/tst_2.10-1.0.jar. checking what's in ivy cache meaningless; tells sbt found it. mathematicians say, that's necessary not sufficient.


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