Prerequisites

• Ensure you have administrative access to the MySQL database.
• Install ClickHouse server and client on the destination machine.
• Familiarity with SQL and command-line tools.

1. Connect to MySQL:
   Open a terminal and connect to your MySQL database using the following command:
   mysql -u [username] -p[password] [database_name]
   Replace `[username]`, `[password]`, and `[database_name]` with your MySQL credentials and database name.
2. Choose Data to Export:
   Decide which tables or data you want to export. You can export entire tables or a subset of data based on your requirements.
3. Export Data to CSV:
   Use the SELECT ... INTO OUTFILE statement to export the data to a CSV file. For example:
   ‍SELECT * INTO OUTFILE '/path/to/your/output.csv'
FIELDS TERMINATED BY ','
OPTIONALLY ENCLOSED BY '"'
LINES TERMINATED BY '\n'
FROM your_table;

Replace `/path/to/your/output.csv` with the desired output file path and `your_table` with the table name you want to export.

1. Review Data Types:
   Ensure that the MySQL data types are compatible with ClickHouse data types. You may need to convert certain data types to match ClickHouse’s requirements.
2. Modify CSV (if necessary):
   If any modifications are needed (e.g., changing date formats or handling NULL values), process the CSV file using a scripting language like Python or a tool like awk.
3. Split Large Files (optional):
   If the CSV file is very large, consider splitting it into smaller chunks to make the import process more manageable.

1. Connect to ClickHouse:
   Open a terminal and connect to ClickHouse using the ClickHouse client:
   clickhouse-client -u [username] --password [password] --database [database_name]
Replace [username], [password], and [database_name] with your ClickHouse credentials and database name.
2. Create Table:
   Define the table schema in ClickHouse to match the structure of the MySQL data you are importing. Use the CREATE TABLE statement to create the table. For example:
   CREATE TABLE my_table (    
   id UInt32,    
    name String,    
    created_at DateTime
) ENGINE = MergeTree()
ORDER BY id;

Adjust the table definition according to your data.

1. Import Data:
   Use the clickhouse-client command to import the CSV file into ClickHouse. For example:
   ‍clickhouse-client --query="INSERT INTO my_table FORMAT CSV" --database=[database_name] < /path/to/your/output.csv
‍
Replace [database_name] with your ClickHouse database name and /path/to/your/output.csv with the path to your CSV file.

1. Check Data Count:
   Run a simple SELECT COUNT(*) FROM my_table; query in both MySQL and ClickHouse to ensure that the row counts match.
2. Compare Sample Data:
   Compare a sample set of data from both databases to verify that the data has been transferred correctly.
3. Validate Data Types:
   Ensure that all data types have been correctly interpreted and stored in ClickHouse.

1. Optimize Table (if necessary):
   In ClickHouse, you can run OPTIMIZE TABLE my_table FINAL; to merge data parts and improve query performance.
2. Remove Temporary Files:
   Delete the CSV files if they are no longer needed to free up space.

Tips:

• Always back up your data before performing migration operations.
• Test the migration process with a small subset of data before moving the entire dataset.
• Consider the impact of timezone differences and character encoding between MySQL and ClickHouse.
• If you encounter performance issues, you can tweak ClickHouse settings or adjust the import process (e.g., using parallel imports).