scala – java.sql.SQLException：在将DataFrame加载到Spark SQL

我在笔记本电脑上尝试过几个Spark集群 – YARN,独立集群和伪分布式模式.它可以在Spark 1.3.0和1.3.1上重现.在spark-shell和spark-submit执行代码时都会出现此问题.我试过MySQL& MS SQL JDBC驱动程序没有成功.

考虑以下示例：

val driver = "com.mysql.jdbc.Driver"
val url = "jdbc:mysql://localhost:3306/test"

val t1 = {
  sqlContext.load("jdbc",Map(
    "url" -> url,"driver" -> driver,"dbtable" -> "t1","partitionColumn" -> "id","lowerBound" -> "0","upperBound" -> "100","numPartitions" -> "50"
  ))
}

到目前为止,这个模式得到了很好的解决：

t1: org.apache.spark.sql.DataFrame = [id: int,name: string]

但是当我评估DataFrame时：

t1.take(1)

发生以下异常：

15/04/29 01:56:44 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0,192.168.1.42): java.sql.SQLException: No suitable driver found for jdbc:mysql://<hostname>:3306/test
    at java.sql.DriverManager.getConnection(DriverManager.java:689)
    at java.sql.DriverManager.getConnection(DriverManager.java:270)
    at org.apache.spark.sql.jdbc.JDBCRDD$$anonfun$getConnector$1.apply(JDBCRDD.scala:158)
    at org.apache.spark.sql.jdbc.JDBCRDD$$anonfun$getConnector$1.apply(JDBCRDD.scala:150)
    at org.apache.spark.sql.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:317)
    at org.apache.spark.sql.jdbc.JDBCRDD.compute(JDBCRDD.scala:309)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
    at org.apache.spark.scheduler.Task.run(Task.scala:64)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

当我尝试在执行器上打开JDBC连接时：

import java.sql.DriverManager

sc.parallelize(0 until 2,2).map { i =>
  Class.forName(driver)
  val conn = DriverManager.getConnection(url)
  conn.close()
  i
}.collect()

它的工作完美：

res1: Array[Int] = Array(0,1)

当我在本地Spark上运行相同的代码时,它也可以很好地工作：

scala> t1.take(1)
...
res0: Array[org.apache.spark.sql.Row] = Array([1,one])

我正在使用Spark预制的Hadoop 2.4支持.

重现问题的最简单的方法是使用start-all.sh脚本以伪分布式模式启动Spark,并运行以下命令：

/path/to/spark-shell --master spark://<hostname>:7077 --jars /path/to/mysql-connector-java-5.1.35.jar --driver-class-path /path/to/mysql-connector-java-5.1.35.jar

有没有办法呢？它看起来像一个严重的问题,所以很奇怪,谷歌搜索在这里没有帮助.