Read JSON file as Spark DataFrame in Python / Spark

Spark has easy fluent APIs that can be used to read data from JSON file as DataFrame object.

In this code example, JSON file named 'example.json' has the following content:

[ { "Category": "Category A", "Count": 100, "Description": "This is category A" }, { "Category": "Category B", "Count": 120, "Description": "This is category B" }, { "Category": "Category C", "Count": 150, "Description": "This is category C" } ]

The file is loaded as a Spark DataFrame using SparkSession.read.json function.

multiLine=True argument is important as the JSON file content is across multiple lines.

Code snippet

from pyspark.sql import SparkSession
from pyspark.sql.types import ArrayType, StructField, StructType, StringType, IntegerType

appName = "PySpark Example - JSON file to Spark Data Frame"
master = "local"

# Create Spark session
spark = SparkSession.builder \
    .appName(appName) \
    .master(master) \
    .getOrCreate()

# Create a schema for the dataframe
schema = StructType([
    StructField('Category', StringType(), True),
    StructField('Count', IntegerType(), True),
    StructField('Description', StringType(), True)
])

# Create data frame
json_file_path = 'data/example.json'
df = spark.read.json(json_file_path, schema, multiLine=True)
print(df.schema)
df.show()

Code snippet

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