First, ensure both ClickHouse and Typesense are installed and running. Confirm that you have access to both systems and that your environment is correctly configured to connect to ClickHouse and Typesense. This might involve setting up network configurations and user permissions.

Use ClickHouse's SQL interface to query and extract the relevant data. You can use a command like the following to export data to a CSV format, which is a common intermediary format:
```sql
SELECT * FROM your_table INTO OUTFILE 'data.csv' FORMAT CSV;
```
Ensure that the data is exported with the correct formatting and encoding to avoid issues during the import process.

Once you have the CSV file, you need to convert it into a JSON format that Typesense can understand. Write a script in a language like Python to read the CSV file and transform each row into a JSON object. Each JSON object should match the schema of the Typesense collection you will import into.

Before importing data, define the schema for your Typesense collection. This involves specifying the structure of your data, including field names, types, and any faceting or indexing options. Use the Typesense API to create this collection:
```json
{
"name": "your_collection",
"fields": [
{"name": "field1", "type": "string"},
{"name": "field2", "type": "int32"}
// Add more fields as needed
]
}
```

With your data prepared and collection configured, use a script to load your JSON objects into Typesense. This can be done via HTTP POST requests to the Typesense API. Ensure you handle authentication and error checking:
```python
import requests
headers = {'X-TYPESENSE-API-KEY': 'your_api_key'}
for document in json_data:
response = requests.post('http://localhost:8108/collections/your_collection/documents', headers=headers, json=document)
response.raise_for_status() # Raise an error for bad responses
```

After the import, verify that the data in Typesense matches the data extracted from ClickHouse. Use the Typesense API to query the collection and ensure the data is correctly indexed and accessible:
```python
response = requests.get('http://localhost:8108/collections/your_collection/documents', headers=headers)
data = response.json()
print(data)
```

If you plan to regularly move data from ClickHouse to Typesense, automate the process using a script that sequentially performs the extraction, transformation, and loading steps. Schedule this script to run at regular intervals using cron jobs or a similar task scheduler.

By following this guide, you can efficiently transfer data from ClickHouse to Typesense without relying on third-party tools, ensuring full control over the data migration process.