json data file load in databricks

Question

Hey,

could you please explain how we can load below curly bracket files in databricks when there are multiple unwanted curly brackets are there apart from main data?

in this case data is available in till Result only

{
    "Generic": {
        "id": "33",
        "Products": [
            {
                "Code": "111",
                "Amount": 1.0,
                "category": "33",
                "price": 11,
                "totalprice": 233
            }
        ],
        "Result": "test",
    },
    "Notification": {
        "Environment": "local",
        "Instance": "local",
        "Time": "00"}

   

Answer 1

@Vineet S - Thanks for the question and using MS Q&A platform.

To load the JSON data file in Databricks, you can use the spark.read.json() method. Here's an example code snippet that you can use:

df = spark.read.json("/path/to/json/file.json", multiLine=True)

In the above code, multiLine=True is used to indicate that the JSON file contains multiple lines. This is required because the JSON file you provided has multiple lines.

However, since your JSON file has some unwanted curly brackets, you will need to clean up the data before loading it into Databricks. One way to do this is to use a regular expression to remove the unwanted curly brackets. Here's an example code snippet that you can use:

import re

# Read the JSON file as a string
with open("/path/to/json/file.json", "r") as f:
    json_str = f.read()

# Remove unwanted curly brackets
json_str = re.sub(r"\{[^{}]*\}", "", json_str)

# Load the cleaned up JSON data into Databricks
df = spark.read.json(sc.parallelize([json_str]), multiLine=True)

In the above code, the regular expression r"\{[^{}]*\}" is used to match and remove the unwanted curly brackets. The cleaned up JSON data is then loaded into Databricks using the spark.read.json() method.

For more details, refer to Azure Databricks - JSON file.

Hope this helps. Do let us know if you any further queries.

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