如何处理异常：运行spark-submit时出现“没有合适的驱动程序”

我正在尝试运行一个火花代码，该代码将读取postgres数据库上的表并将其插入HDFS上的Hive表中。为此，我在属性文件中设置了连接属性，如下所示：

devUserName=usrname
devPassword=pwd
gpDriverClass=org.postgresql.Driver
gpDevUrl=jdbc:postgresql://ip:port/dbname?ssl=true&sslfactory=org.postgresql.ssl.NonValidatingFactory

并将属性文件读取为：

  val conFile       = "testconnection.properties"
  val properties    = new Properties()
  properties.load(new FileInputStream(conFile))

  // GP Properties
  val connectionUrl = properties.getProperty("gpDevUrl")
  val devUserName   = properties.getProperty("devUserName")
  val devPassword   = properties.getProperty("devPassword")
  val driverClass   = properties.getProperty("gpDriverClass")

我通过以下方式提交jar文件：

SPARK_MAJOR_VERSION=2 spark-submit --conf spark.ui.port=4090 --driver-class-path /home/usrname/jars/postgresql-42.1.4.jar --master=yarn --deploy-mode=cluster --driver-memory 40g --driver-cores 3 --executor-memory 40g --executor-cores 20 --num-executors 5  --files /usr/hdp/current/spark2-client/conf/hive-site.xml,testconnection.properties --jars /home/usrname/jars/postgresql-42.1.4.jar --class com.partition.source.YearPartition splinter_2.11-0.1.jar  --keytab /home/usrname/usrname.keytab --principal [email protected] --name Splinter --conf spark.executor.extraClassPath=/home/usrname/jars/postgresql-42.1.4.jar

作业失败，并显示以下错误消息：

client token: Token { kind: YARN_CLIENT_TOKEN, service:  }
     diagnostics: User class threw exception: java.sql.SQLException: No suitable driver
     ApplicationMaster host: 10.230.137.190
     ApplicationMaster RPC port: 0
     queue: default
     start time: 1537545547309
     final status: FAILED
     tracking URL: http://ip:port/proxy/application_123456789_76/
     user: fdlhdpetl
18/09/21 15:59:38 INFO Client: Deleted staging directory hdfs://dev/user/usrname/.sparkStaging/application_123456789_76
Exception in thread "main" org.apache.spark.SparkException: Application application_123456789_76 finished with failed status
    at org.apache.spark.deploy.yarn.Client.run(Client.scala:1187)
    at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1233)
    at org.apache.spark.deploy.yarn.Client.main(Client.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:782)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
18/09/21 15:59:38 INFO ShutdownHookManager: Shutdown hook called
18/09/21 15:59:38 INFO ShutdownHookManager: Deleting directory /tmp/spark-59934097-dfe9-4ad2-a66a-ff93d42cf838

我在build.sbt文件中的依赖项：

name := "Splinter"
version := "0.1"
scalaVersion := "2.11.8"

libraryDependencies ++= Seq(
  "org.apache.spark" %% "spark-core" % "2.0.0" % "provided",
  "org.apache.spark" %% "spark-sql" % "2.0.0" % "provided",
  "org.json4s" %% "json4s-jackson" % "3.2.11" % "provided",
  "org.apache.httpcomponents" % "httpclient" % "4.5.3"
)

// https://mvnrepository.com/artifact/org.postgresql/postgresql
libraryDependencies += "org.postgresql" % "postgresql" % "42.1.4"

用于读取postgres表的代码：

def prepareFinalDF(splitColumns:List[String], textList: ListBuffer[String], allColumns:String, dataMapper:Map[String, String], partition_columns:Array[String], spark:SparkSession): DataFrame = {
  val execQuery = s"select ${allColumns}, 0 as ${flagCol} from schema.tablename where period_year='2017'"
  val yearDF    = spark.read.format("jdbc").option("url", connectionUrl).option("dbtable", s"(${execQuery}) as year2017").option("user", devUserName).option("password", devPassword).option("numPartitions",20).load()
  val totalCols:List[String] = splitColumns ++ textList
  val cdt                    = new ChangeDataTypes(totalCols, dataMapper)
  hiveDataTypes              = cdt.gpDetails()
  prepareHiveTableSchema(hiveDataTypes, partition_columns)
  val allColsOrdered         = yearDF.columns.diff(partition_columns) ++ partition_columns
  val allCols                = allColsOrdered.map(colname => org.apache.spark.sql.functions.col(colname))
  val resultDF               = yearDF.select(allCols:_*)
  val stringColumns          = resultDF.schema.fields.filter(x => x.dataType == StringType).map(s => s.name)
  val finalDF                = stringColumns.foldLeft(resultDF) {
    (tempDF, colName) => tempDF.withColumn(colName, regexp_replace(regexp_replace(col(colName), "[\r\n]+", " "), "[\t]+"," "))
  }
  finalDF
}

execQuery包含： select * from schema.tablename where period_year=2017

val dataDF = prepareFinalDF(splitColumns, textList, allColumns, dataMapper, partition_columns, spark)
dataDF.createOrReplaceTempView("preparedDF")
spark.sql("set hive.exec.dynamic.partition.mode=nonstrict")
spark.sql("set hive.exec.dynamic.partition=true")
spark.sql(s"INSERT OVERWRITE TABLE default.xx_gl_forecast PARTITION(${prtn_String_columns}) select * from preparedDF")

我检查了spark-submit中提到的jar，它存在于给定的目录中，但提交时仍然失败。谁能告诉我我在这里做错了什么？在spark-submit中提供参数时，是否要遵循任何特定的顺序？