When working with data, it is common to have multiple JSON files that need to be combined into a single file for further processing. In this article, we will explore three different ways to append multiple JSON files together and output a single Avro file using Python.

Option 1: Using the json and avro libraries

import json
import avro
from avro.datafile import DataFileWriter
from avro.io import DatumWriter

# List of JSON files to be combined
json_files = ['file1.json', 'file2.json', 'file3.json']

# Create an Avro schema
schema = avro.schema.Parse(open('schema.avsc', 'r').read())

# Create a DataFileWriter
writer = DataFileWriter(open('output.avro', 'wb'), DatumWriter(), schema)

# Iterate over each JSON file
for file in json_files:
    with open(file, 'r') as f:
        # Load JSON data
        data = json.load(f)
        
        # Write JSON data to Avro file
        writer.append(data)

# Close the DataFileWriter
writer.close()

This option uses the json and avro libraries to read the JSON files and write the combined data to an Avro file. It first creates an Avro schema by parsing a schema file. Then, it creates a DataFileWriter with the Avro schema and opens the output Avro file. Next, it iterates over each JSON file, loads the JSON data, and appends it to the Avro file. Finally, it closes the DataFileWriter.

Option 2: Using the pandas library

import pandas as pd
import avro
from avro.datafile import DataFileWriter
from avro.io import DatumWriter

# List of JSON files to be combined
json_files = ['file1.json', 'file2.json', 'file3.json']

# Create an Avro schema
schema = avro.schema.Parse(open('schema.avsc', 'r').read())

# Create an empty DataFrame
df = pd.DataFrame()

# Iterate over each JSON file
for file in json_files:
    # Read JSON data into a DataFrame
    data = pd.read_json(file)
    
    # Append DataFrame to the main DataFrame
    df = df.append(data)

# Create a DataFileWriter
writer = DataFileWriter(open('output.avro', 'wb'), DatumWriter(), schema)

# Iterate over each row in the DataFrame
for _, row in df.iterrows():
    # Write row data to Avro file
    writer.append(row.to_dict())

# Close the DataFileWriter
writer.close()

This option uses the pandas library to read the JSON files into DataFrames and combine them. It first creates an Avro schema by parsing a schema file. Then, it creates an empty DataFrame. Next, it iterates over each JSON file, reads the JSON data into a DataFrame, and appends it to the main DataFrame. After that, it creates a DataFileWriter with the Avro schema and opens the output Avro file. Finally, it iterates over each row in the DataFrame, converts it to a dictionary, and appends it to the Avro file.

Option 3: Using the json and fastavro libraries

import json
import fastavro

# List of JSON files to be combined
json_files = ['file1.json', 'file2.json', 'file3.json']

# Create an Avro schema
schema = json.loads(open('schema.avsc', 'r').read())

# Create an empty list to store the combined data
combined_data = []

# Iterate over each JSON file
for file in json_files:
    with open(file, 'r') as f:
        # Load JSON data
        data = json.load(f)
        
        # Append JSON data to the combined data list
        combined_data.extend(data)

# Write the combined data to an Avro file
with open('output.avro', 'wb') as f:
    fastavro.writer(f, schema, combined_data)

This option uses the json and fastavro libraries to read the JSON files and write the combined data to an Avro file. It first creates an Avro schema by parsing a schema file. Then, it creates an empty list to store the combined data. Next, it iterates over each JSON file, loads the JSON data, and appends it to the combined data list. Finally, it writes the combined data to an Avro file using the fastavro library.

After evaluating the three options, it is clear that Option 2, which utilizes the pandas library, is the better choice. The pandas library provides powerful data manipulation capabilities and allows for efficient handling of large datasets. Additionally, the option of using DataFrames simplifies the process of combining the JSON files and provides a more structured approach to data manipulation. Therefore, Option 2 is recommended for appending multiple JSON files together and outputting a single Avro file using Python.