Begin by exporting the data from your MySQL database. You can do this using the `mysqldump` utility to create a SQL dump file. Run the following command in your terminal:
```sh
mysqldump -u [username] -p [database_name] > data_dump.sql
```
This command will prompt you for the password and create a `data_dump.sql` file containing all the data and schema from your specified database.

Since ClickHouse prefers data to be loaded in CSV format, convert your SQL dump to CSV. Use a script or tool to parse the SQL dump and generate CSV files. This can be done using Python or any scripting language that can read the SQL file and output CSV. Here's a simple Python snippet:
```python
import csv

def sql_to_csv(sql_file, csv_file):
with open(sql_file, 'r') as file:
lines = file.readlines()
with open(csv_file, 'w', newline='') as csvfile:
csvwriter = csv.writer(csvfile)
# Parse SQL and write to CSV (implementation depends on SQL structure)
# Example: csvwriter.writerow([column1, column2, ...])
sql_to_csv('data_dump.sql', 'data_dump.csv')
```

Before loading data into ClickHouse, ensure you have the corresponding table schema ready. You can create the table using the ClickHouse client with a command like:
```sql
CREATE TABLE my_table (
column1 DataType,
column2 DataType,
...
) ENGINE = MergeTree()
ORDER BY (primary_key_column);
```
Adjust the `DataType` and `ORDER BY` clause according to your specific data requirements.

If you haven't already, install the ClickHouse client on your machine. This is necessary for executing commands against your ClickHouse database. You can download it from the official ClickHouse repository or use a package manager:
```sh
sudo apt-get install clickhouse-client
```

Utilize the ClickHouse client to load your CSV file into the prepared table. Use the `INSERT INTO ... FORMAT CSV` command:
```sh
clickhouse-client --query="INSERT INTO my_table FORMAT CSV" < data_dump.csv
```
This command reads from the CSV file and inserts the data into the specified ClickHouse table.

After loading, verify that your data has been correctly inserted into ClickHouse. Run a few SELECT queries to ensure data integrity and consistency:
```sql
SELECT * FROM my_table LIMIT 10;
```

Finally, consider optimizing your ClickHouse database for better performance. This might include partitioning tables, optimizing queries, or adjusting settings specific to your workload. Evaluate your queries and storage to improve efficiency.

By following these steps, you can successfully move data from MySQL to ClickHouse without relying on third-party connectors or integrations.