从JSON模式表示形式创建Spark数据帧模式 [英] Create spark dataframe schema from json schema representation

问题描述

是否有一种方法可以将数据帧架构序列化为json并在以后进行反序列化?

Is there a way to serialize a dataframe schema to json and deserialize it later on?

用例很简单: 我有一个json配置文件，其中包含我需要读取的数据帧的架构. 我希望能够从现有模式(在数据帧中)创建默认配置，并且希望能够通过从json字符串中读取它来生成相关模式，以供以后使用.

The use case is simple: I have a json configuration file which contains the schema for dataframes I need to read. I want to be able to create the default configuration from an existing schema (in a dataframe) and I want to be able to generate the relevant schema to be used later on by reading it from the json string.

推荐答案

有两个步骤:从现有数据帧创建json，并从先前保存的json字符串创建模式.

There are two steps for this: Creating the json from an existing dataframe and creating the schema from the previously saved json string.

从现有数据框中创建字符串

    val schema = df.schema
    val jsonString = schema.json

从json创建模式

    import org.apache.spark.sql.types.{DataType, StructType}
    val newSchema = DataType.fromJson(jsonString).asInstanceOf[StructType]

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