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Here's an example code using multiprocessing module in Python to divide a large JSON file into smaller ones. The basic idea is to read the large JSON file in chunks and process each chunk in a separate process, saving the result to a smaller JSON file.

import json
import os
from multiprocessing import Pool

# Function to process a chunk
def process_chunk(chunk):
    # Process the chunk and return the result
    result = ...

    # Save the result to a smaller JSON file
    with open(f"result_{os.getpid()}.json", "w") as f:
        f.write(json.dumps(result))

# Main function
def main():
    # Open the large JSON file
    with open("large_file.json", "r") as f:
        # Read the file in chunks
        chunk_size = 1000   # adjust to suit your needs
        while True:
            chunk = f.readlines(chunk_size)
            if not chunk:
                break

            # Create a process pool and process the chunk in parallel
            with Pool() as pool:
                pool.apply_async(process_chunk, args=(chunk, ))

    # Wait for all processes to finish
    pool.close()
    pool.join()

# Run the main function
if __name__ == "__main__":
    main()

Note that the process_chunk function is just a placeholder and you'll need to adjust it to suit your specific use case. Also note that the chunk size and the number of processes you can run in parallel will depend on your specific hardware setup and available resources.