MySQL to JSON Lines Converter

About MySQL to JSON Lines Converter

Convert MySQL database dumps (CREATE TABLE and INSERT statements) to JSON Lines (JSONL) format, also known as newline-delimited JSON. Each row becomes a separate JSON object or array on its own line, perfect for streaming and big data applications.

Key Features

• Line-Delimited Format: One JSON object/array per line
• Object Mode: Convert rows to objects using column names as keys
• Array Mode: Convert rows to simple arrays
• Streaming Ready: Process large datasets line-by-line
• Big Data Compatible: Works with Hadoop, Spark, and other tools
• File Download: Save as .jsonl file
• Instant Preview: Real-time conversion as you type

How to Use

1. Input MySQL Data: Paste your MySQL dump or upload a .sql file
2. Configure Options: Choose whether to use columns for object keys
3. Review Output: The JSON Lines updates automatically
4. Copy or Download: Use the JSONL in your application

What is JSON Lines?

JSON Lines is a text format where:

• Each line is a valid JSON value (object or array)
• Lines are separated by newline characters (\n)
• Files can be processed line-by-line without loading entire dataset
• Ideal for streaming, logging, and big data processing

Example Conversion

MySQL Input:

CREATE TABLE employees (
  id INT PRIMARY KEY,
  name VARCHAR(100),
  age INT,
  department VARCHAR(50)
);

INSERT INTO employees VALUES (1, 'John Doe', 28, 'Engineering');
INSERT INTO employees VALUES (2, 'Jane Smith', 34, 'Marketing');

JSON Lines Output (Object Mode):

{"id":"1","name":"John Doe","age":"28","department":"Engineering"}
{"id":"2","name":"Jane Smith","age":"34","department":"Marketing"}

JSON Lines Output (Array Mode):

["id","name","age","department"]
["1","John Doe","28","Engineering"]
["2","Jane Smith","34","Marketing"]

Common Use Cases

• Data Streaming: Process large MySQL exports without loading into memory
• Log Files: Structured logging of database changes in JSON Lines format
• Big Data: Import MySQL data into Hadoop, Spark, or other big data tools
• ETL Pipelines: Extract MySQL data and load efficiently into data warehouses
• Database Import: Bulk import MySQL data into MongoDB, Elasticsearch, etc.
• API Responses: Stream large MySQL result sets from APIs
• Data Migration: Migrate MySQL databases to NoSQL systems

Advantages of JSON Lines

• Streamable: Process one line at a time
• Appendable: Add new records without parsing entire file
• Simple: Easy to generate and parse
• Robust: Corrupted line doesn't affect others
• Universal: Supported by many data processing tools
• Memory Efficient: No need to load entire dataset

Processing JSON Lines

Python:

import json

with open('output.jsonl', 'r') as f:
    for line in f:
        data = json.loads(line)
        print(data['name'], data['age'])

JavaScript/Node.js:

const fs = require('fs');
const readline = require('readline');

const rl = readline.createInterface({
    input: fs.createReadStream('output.jsonl')
});

rl.on('line', (line) => {
    const data = JSON.parse(line);
    console.log(data.name, data.age);
});

Command Line (jq):

cat output.jsonl | jq '.name'

Tools Supporting JSON Lines

• Apache Spark
• Hadoop
• MongoDB (mongoimport)
• Elasticsearch (bulk API)
• BigQuery
• jq (command-line JSON processor)
• Pandas (Python data analysis)
• Apache Kafka

Supported MySQL Syntax

• CREATE TABLE: Extracts column names from table definitions
• INSERT INTO: Parses VALUES clauses with quoted strings
• Column Lists: Supports INSERT INTO table (col1, col2) VALUES format
• Quoted Values: Handles single and double quotes properly
• Escaped Quotes: Processes escaped quotes in string values

Tips for Best Results

• Include CREATE TABLE for automatic column name detection
• Use object mode for self-describing data
• Use array mode for minimal file size
• Process line-by-line for large MySQL exports
• Validate with JSON Lines validators if needed
• Use .jsonl or .ndjson file extension

Privacy & Security

All conversions happen locally in your browser. Your MySQL data is never uploaded to any server, ensuring complete privacy and security.

FAQ

What is the difference between JSON and JSON Lines?

Standard JSON represents a single JSON value (often an array of objects), while JSON Lines stores one JSON value per line. JSONL is easier to stream, append, and process incrementally.

Are trailing newlines required in JSONL files?

No, but they are common. This tool trims the final newline when displaying output; most JSONL consumers handle files with or without a trailing newline.

Can I safely split a large JSONL file?

Yes. Because each line is an independent JSON value, you can split or concatenate JSONL files along line boundaries without breaking structure.

Does this tool infer numeric types?

No. Values are emitted as strings. If you need numbers or booleans, convert them in your processing pipeline after reading each JSON object or array.

Is any of my data uploaded or logged?

No. All conversion logic runs in your browser only. The tool does not send your MySQL or JSONL data to external servers.