Create dataframe with schema provided as JSON file

Question

How can I create a pyspark data frame with 2 JSON files?

• file1: this file has complete data
• file2: this file has only the schema of file1 data.

file1

{"RESIDENCY":"AUS","EFFDT":"01-01-1900","EFF_STATUS":"A","DESCR":"Australian Resident","DESCRSHORT":"Australian"}

file2

[{"fields":[{"metadata":{},"name":"RESIDENCY","nullable":true,"type":"string"},{"metadata":{},"name":"EFFDT","nullable":true,"type":"string"},{"metadata":{},"name":"EFF_STATUS","nullable":true,"type":"string"},{"metadata":{},"name":"DESCR","nullable":true,"type":"string"},{"metadata":{},"name":"DESCRSHORT","nullable":true,"type":"string"}],"type":"struct"}]

Answer 1

You have to read, first, the schema file using Python json.load, then convert it to DataType using StructType.fromJson.

import json
from pyspark.sql.types import StructType

with open("/path/to/file2.json") as f:
    json_schema = json.load(f)

schema = StructType.fromJson(json_schema[0])

Now just pass that schema to DataFrame Reader:

df = spark.read.schema(schema).json("/path/to/file1.json")

df.show()

#+---------+----------+----------+-------------------+----------+
#|RESIDENCY|     EFFDT|EFF_STATUS|              DESCR|DESCRSHORT|
#+---------+----------+----------+-------------------+----------+
#|      AUS|01-01-1900|         A|Australian Resident|Australian|
#+---------+----------+----------+-------------------+----------+

EDIT:

If the file containing the schema is located in GCS, you can use Spark or Hadoop API to get the file content. Here is an example using Spark:

file_content = spark.read.text("/path/to/file2.json").rdd.map(
    lambda r: " ".join([str(elt) for elt in r])
).reduce(
    lambda x, y: "\n".join([x, y])
)

json_schema = json.loads(file_content)

Answer 2

I have found GCSFS packages to access files in GCP Buckets:

pip install gcsfs

import gcsfs

fs = gcsfs.GCSFileSystem(project='your GCP project name')

with fs.open('path/toread/sample.json', 'rb') as f:
     json_schema=json.load(f)