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You have json file which is nested with multiple key value pair how you read it in databricks?

learning_1989
New Contributor II

You have json file which is nested with multiple key value pair how you read it in databricks?

4 REPLIES 4

Kaniz
Community Manager
Community Manager

Hi @learning_1989, To successfully read a nested JSON file within Databricks, utilizing PySpark is the key. 

 

Follow these steps to get started: 

 

1. Begin by reading the JSON file: Harness the power of the spark.read.json function to read your JSON file. In the case of a multiline file, setting the multiline option to true is crucial.

2. Transforming a nested JSON: In case your JSON file features nested structures, you can easily flatten them using the handy explode function and the $"column.*" method.

3. Selecting certain elements: To extract specific fields from the JSON, simply utilize the <column-name>:<extraction-path> syntax.

 

If you are working with larger JSON files, it's important to take performance-enhancing measures like caching or partitioning into account. Be sure to replace "file_path" with the correct path to your JSON file.

Ayushi_Suthar
Honored Contributor
Honored Contributor

Hello @learning_1989 Please have a look at the following document to see how to read the JSON file in Databricks:
Document: https://docs.databricks.com/en/query/formats/json.html#json-file

This allows you to read JSON files with key-value pairs in single-line or multi-line mode. In single-line mode, a file can be split into many parts and read in parallel. In multi-line mode, a file is loaded as a whole entity and cannot be split.

Lakshay
Esteemed Contributor
Esteemed Contributor

You should be able to read the json file with below code.

val df = spark.read.format("json").load("file.json")

After this you will need to use the explode function to add columns to the dataframe using the nested values.

Kaniz
Community Manager
Community Manager

Hey there! Thanks a bunch for being part of our awesome community! 🎉 

We love having you around and appreciate all your questions. Take a moment to check out the responses – you'll find some great info. Your input is valuable, so pick the best solution for you. And remember, if you ever need more help , we're here for you! 

Keep being awesome! 😊🚀

 

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