如何在DataFrame中保持键值顺序与JSON相同? [英] How to maintain order of key-value in DataFrame same as JSON?

问题描述

示例JSON数据:

{"name": "dev","salary": 100,"occupation": "engg","address": "noida"}
{"name": "karthik","salary": 200,"occupation": "engg","address": "blore"}

Spark Java代码:

Spark Java code:

DataFrame df = sqlContext.read().json(jsonPath);
df.printSchema();
df.show(false);

输出:

root
 |-- address: string (nullable = true)
 |-- name: string (nullable = true)
 |-- occupation: string (nullable = true)
 |-- salary: long (nullable = true)


+-------+-------+----------+------+
|address|name   |occupation|salary|
+-------+-------+----------+------+
|noida  |dev    |engg      |10000 |
|blore  |karthik|engg      |20000 |
+-------+-------+----------+------+

各列按字母顺序排列. 有什么方法可以维持自然秩序?

Columns are arranged in the alphabetical order. Is there any way to maintain natural order?

推荐答案

您可以在阅读json的同时提供schema，它会保持顺序.

You can provide schema while reading the json and it will maintain the order.

StructType schema = DataTypes.createStructType(new StructField[] { 
    DataTypes.createStructField("name", DataTypes.StringType, true),
    DataTypes.createStructField("salary", DataTypes.IntegerType, true),
    DataTypes.createStructField("occupation", DataTypes.StringType, true),
    DataTypes.createStructField("address", DataTypes.StringType, true)});

DataFrame df = sqlContext.read().schema(schema).json(jsonPath);
df.printSchema();
df.show(false);

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