使用PySpark将JSON文件读取为Pyspark Dataframe吗? [英] Read JSON file as Pyspark Dataframe using PySpark?

问题描述

如何读取以下JSON结构以使用PySpark触发数据帧?

How can I read the following JSON structure to spark dataframe using PySpark?

我的JSON结构

{"results":[{"a":1,"b":2,"c":"name"},{"a":2,"b":5,"c":"foo"}]}

我尝试过:

df = spark.read.json('simple.json');

我希望将输出a，b，c作为列，并将值作为相应的行.

I want the output a,b,c as columns and values as respective rows.

谢谢.

推荐答案

Json字符串变量

如果您将 json字符串作为变量，则可以

simple_json = '{"results":[{"a":1,"b":2,"c":"name"},{"a":2,"b":5,"c":"foo"}]}'
rddjson = sc.parallelize([simple_json])
df = sqlContext.read.json(rddjson)

from pyspark.sql import functions as F
df.select(F.explode(df.results).alias('results')).select('results.*').show(truncate=False)

这将为您提供

+---+---+----+
|a  |b  |c   |
+---+---+----+
|1  |2  |name|
|2  |5  |foo |
+---+---+----+

Json字符串作为文件(sparkContext和sqlContext)中的单独行

如果文件中有 json字符串作为单独的行 ，则可以如上所述使用sparkContext将其读取到rdd [string] 中，其余过程相同如上

If you have json strings as separate lines in a file then you can read it using sparkContext into rdd[string] as above and the rest of the process is same as above

rddjson = sc.textFile('/home/anahcolus/IdeaProjects/pythonSpark/test.csv')
df = sqlContext.read.json(rddjson)
df.select(F.explode(df['results']).alias('results')).select('results.*').show(truncate=False)

Json字符串作为文件中的单独行(仅适用于sqlContext)

如果文件中有 json字符串作为单独的行 ，则只能使用sqlContext.但是该过程很复杂，因为您必须为其创建架构

If you have json strings as separate lines in a file then you can just use sqlContext only. But the process is complex as you have to create schema for it

df = sqlContext.read.text('path to the file')

from pyspark.sql import functions as F
from pyspark.sql import types as T
df = df.select(F.from_json(df.value, T.StructType([T.StructField('results', T.ArrayType(T.StructType([T.StructField('a', T.IntegerType()), T.StructField('b', T.IntegerType()), T.StructField('c', T.StringType())])))])).alias('results'))
df.select(F.explode(df['results.results']).alias('results')).select('results.*').show(truncate=False)

应该与上述结果相同

我希望答案会有所帮助

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