如何将json字符串转换为spark上的数据帧 [英] how to convert json string to dataframe on spark

问题描述

我想将下面的字符串变量转换为 spark 上的数据帧.

val jsonStr = "{ "metadata": { "key": 84896, "value": 54 }}"

我知道如何从 json 文件创建数据框.

sqlContext.read.json("file.json")

但我不知道如何从字符串变量创建数据框.

如何将 json 字符串变量转换为数据框.

解决方案

对于 Spark 2.2+:

import spark.implicits._val jsonStr = """{ "metadata": { "key": 84896, "value": 54 }}"""val df = spark.read.json(Seq(jsonStr).toDS)

对于 Spark 2.1.x:

val events = sc.parallelize("""{"action":"create","timestamp":"2016-01-07T00:01:17Z"}""" :: Nil)val df = sqlContext.read.json(events)

<块引用>

提示:这是使用 sqlContext.read.json(jsonRDD: RDD[Stirng]) 重载.还有 sqlContext.read.json(path: String) 直接读取 Json 文件.

对于旧版本:

val jsonStr = """{ "metadata": { "key": 84896, "value": 54 }}"""val rdd = sc.parallelize(Seq(jsonStr))val df = sqlContext.read.json(rdd)

I want to convert string variable below to dataframe on spark.

val jsonStr = "{ "metadata": { "key": 84896, "value": 54 }}"

I know how to create dataframe from json file.

sqlContext.read.json("file.json")

but I don't know how to create dataframe from string variable.

How can I convert json String variable to dataframe.

解决方案

For Spark 2.2+:

import spark.implicits._
val jsonStr = """{ "metadata": { "key": 84896, "value": 54 }}"""
val df = spark.read.json(Seq(jsonStr).toDS)

For Spark 2.1.x:

val events = sc.parallelize("""{"action":"create","timestamp":"2016-01-07T00:01:17Z"}""" :: Nil)    
val df = sqlContext.read.json(events)

Hint: this is using sqlContext.read.json(jsonRDD: RDD[Stirng]) overload. There is also sqlContext.read.json(path: String) where it reads a Json file directly.

For older versions:

val jsonStr = """{ "metadata": { "key": 84896, "value": 54 }}"""
val rdd = sc.parallelize(Seq(jsonStr))
val df = sqlContext.read.json(rdd)

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