一些兴趣点：

1)您不需要数据帧来加载您的json架构 . 模式在驱动程序上加载和执行，因为不需要分发那些不必要的开销

2)我构造了一个JColumn对象的List，并将它传递给StructType以动态构造模式

3)inferSchema应该是false，因为我们明确定义了schema

4)我假设您的数据库表使用“null”表示空值

5)调整映射修改typeMapping

import org.json4s._

import org.json4s.native.JsonMethods

case class JColumn(trim: Boolean, name: String, nullable: Boolean, id: Option[String], position: BigInt, table: String, _type: String, primaryKey: Boolean)

val path = """your_path\schema.json"""

val input = scala.io.Source.fromFile(path)

val json = JsonMethods.parse(input.reader())

val typeMapping = Map(

"double" -> DoubleType,

"integer" -> IntegerType,

"string" -> StringType,

"date" -> DateType,

"bool" -> BooleanType)

var rddSchema = ListBuffer[StructField]()

implicit val formats = DefaultFormats

val schema = json.extract[Array[JColumn]]

//schema.foreach(c => println(s"name:${c.name} type:${c._type} isnullable:${c.nullable}"))

schema.foreach { c =>

rddSchema += StructField(c.name, typeMapping(c._type), c.nullable, Metadata.empty)

}

val in_emp = spark.read

.format("com.databricks.spark.csv")

.schema(StructType(rddSchema.toList))

.option("inferSchema", "false")

.option("dateFormat", "yyyy.MM.dd")

.option("header", "false")

.option("delimiter", ",")

.option("nullValue", "null")

.option("treatEmptyValuesAsNulls", "true")

.csv("""your_path\employee.csv""")

in_emp.printSchema()

in_emp.collect()

in_emp.show()

我使用以下模式进行测试：

[

{

"trim": true,

"name": "id",

"nullable": true,

"id": null,

"position": 0,

"table": "employee",

"_type": "integer",

"primaryKey": true

},

{

"trim": true,

"name": "salary",

"nullable": true,

"id": null,

"position": 1,

"table": "employee",

"_type": "double",

"primaryKey": false

},

{

"trim": true,

"name": "dob",

"nullable": true,

"id": null,

"position": 2,

"table": "employee",

"_type": "date",

"primaryKey": false

},

{

"trim": true,

"name": "department",

"nullable": true,

"id": null,

"position": 3,

"table": "employee",

"_type": "string",

"primaryKey": false

}

]

以及下一个数据(employee.csv)：

1211,3500.0,null,marketing

1212,3000.0,2016.12.08,IT

1213,4000.0,2017.10.20,HR

1214,3000.0,2017.10.20,finance