Read a JSON file using the Apache Spark DataFrame : Databricks Tutorials

In Databricks, you can read a JSON file using the Apache Spark DataFrame API. Here’s a step-by-step guide on how to read a JSON file in Databricks:

Upload Your JSON File: First, make sure you have your JSON file uploaded to Databricks. You can upload files to Databricks DBFS (Databricks File System) or specify a path to a file located in your data storage.
Create a Spark Session: If you don’t already have a Spark session running, create one. This is typically done at the beginning of your notebook or script:

from pyspark.sql import SparkSession

spark = SparkSession.builder.appName("JSONReadExample").getOrCreate()

3. Read the JSON File: You can use the `spark.read.json` method to read the JSON file into a DataFrame. Specify the path to your JSON file as the argument to this method:

json_df = spark.read.json("/path/to/your/jsonfile.json")

Replace `”/path/to/your/jsonfile.json”` with the actual path to your JSON file.

4. View the DataFrame: You can view the contents of the DataFrame by calling `.show()`:

json_df.show()

This will display the first few rows of your JSON data.

5. Perform Operations: Now that you have your JSON data in a DataFrame, you can perform various operations and transformations on it using Spark’s DataFrame API. For example:

# Select specific columns

json_df.select("column_name").show()

# Filter rows

json_df.filter(json_df["column_name"] == "some_value").show()

# Aggregations, joins, and more

6. Stop the Spark Session*: Once you’re done working with the DataFrame, it’s good practice to stop the Spark session:

spark.stop()

That’s it! You’ve successfully read a JSON file in Databricks using Apache Spark. You can use this DataFrame for data analysis and manipulation within your Databricks environment.