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To interact with ClickHouse, ensure that the ClickHouse client is installed on your local machine. This tool allows you to execute SQL queries and export data. You can download and install it from the official ClickHouse website or use a package manager like `apt` or `yum`.
Open your terminal and connect to your ClickHouse server using the ClickHouse client. Use the following command, replacing `host`, `user`, and `password` with your ClickHouse server details:
```bash
clickhouse-client --host= --user= --password=
```
Determine the specific data you want to export from ClickHouse. Write a SQL SELECT query that retrieves the desired dataset. For example:
```sql
SELECT * FROM database_name.table_name;
```
Use the `FORMAT JSONEachRow` option in your SQL query to export the data in JSON format. This will output each row as a separate JSON object, suitable for appending to a JSON file. Execute the following command:
```bash
clickhouse-client --host= --user= --password= --query="SELECT * FROM database_name.table_name FORMAT JSONEachRow" > data.json
```
This command will write the output directly to a file named `data.json` in your local directory.
Open the `data.json` file with a text editor or JSON viewer to verify that the data has been exported correctly. Each line should represent a JSON object corresponding to a row from your query.
If necessary, format or prettify the JSON data for better readability or to meet specific formatting requirements. This can be done using tools like `jq`:
```bash
cat data.json | jq '.' > formatted_data.json
```
This command reads `data.json` and outputs a formatted version to `formatted_data.json`.
Once you have verified and formatted the JSON data, ensure it is stored securely. Consider creating a backup of the file in a safe location, especially if it contains sensitive information. Use standard file security practices such as setting appropriate permissions and encrypting the file if needed.
By following these steps, you can effectively move data from ClickHouse to a local JSON file without using any third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
An open-source database management system for online analytical processing (OLAP), ClickHouse takes the innovative approach of using a column-based database. It is easy to use right out of the box and is touted as being hardware efficient, extremely reliable, linearly scalable, and “blazing fast”—between 100-1,000x faster than traditional databases that write rows of data to the disk—allowing analytical data reports to be generated in real-time.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: