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如何使用Spark在数据框中创建架构数组

[英]How to create schema Array in data frame with spark

I have code to create data frame and this works fine if there is no array in my input data. 我有创建数据框的代码,如果我的输入数据中没有数组,则可以正常工作。

I tried using Json data which doen't have array and it runs successfully. 我尝试使用没有数组的Json数据,它成功运行。 My code is 我的代码是

val vals = sc.parallelize(
  """{"id":"1","name":"alex"}""" ::
  Nil
)

val schema = (new StructType)
      .add("id", StringType)
      .add("name", StringType)


  sqlContext.read.schema(schema).json(vals).select($"*").printSchema()

My question is, if I have input data with array like below then how to create schema? 我的问题是,如果我有如下所示的数组输入数据,那么如何创建模式?

     val vals = sc.parallelize(
  """{"id":"1","name":"alex","score":[{"keyword":"read","point":10}]}""" ::
  Nil
)


val schema = (new StructType)
      .add("id", StringType)
      .add("name", StringType)

Thanks. 谢谢。

Oke, I could have solution in my code. 好的,我可以在代码中找到解决方案。

Create schema in array in data frame spark you can this code. 在数据帧中的数组中创建模式可以触发此代码。

val vals = sc.parallelize(
  """{"id":"1","name":"alex","score":[{"keyword":"read","point":10}]}""" ::
  Nil
)

val schema = StructType(
      Array(
        StructField("id", StringType),
        StructField("name", StringType),
        StructField("score", ArrayType(StructType(Array(
          StructField("keyword", StringType),
          StructField("point", IntegerType)
        ))))
      )
    )

and you print schema 然后您打印架构

sqlContext.read.schema(schema).json(vals).select($"*").printSchema()

Thanks is resolved 谢谢解决

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