mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-12-04 21:42:39 +00:00
97 lines
3.5 KiB
Markdown
97 lines
3.5 KiB
Markdown
---
|
|
slug: /en/engines/table-functions/executable
|
|
sidebar_position: 55
|
|
sidebar_label: executable
|
|
keywords: [udf, user defined function, clickhouse, executable, table, function]
|
|
---
|
|
|
|
# executable Table Function for UDFs
|
|
|
|
The `executable` table function creates a table based on the output of a user-defined function (UDF) that you define in a script that outputs rows to **stdout**. The executable script is stored in the `users_scripts` directory and can read data from any source.
|
|
|
|
You can optionally include one or more input queries that stream their results to **stdin** for the script to read.
|
|
|
|
:::note
|
|
A key advantage between ordinary UDF functions and the `executable` table function and `Executable` table engine is that ordinary UDF functions cannot change the row count. For example, if the input is 100 rows, then the result must return 100 rows. When using the `executable` table function or `Executable` table engine, your script can make any data transformations you want, including complex aggregations.
|
|
:::
|
|
|
|
## Syntax
|
|
|
|
The `executable` table function requires three parameters and accepts an optional list of input queries:
|
|
|
|
```sql
|
|
executable(script_name, format, structure, [input_query...])
|
|
```
|
|
|
|
- `script_name`: the file name of the script. saved in the `user_scripts` folder (the default folder of the `user_scripts_path` setting)
|
|
- `format`: the format of the generated table
|
|
- `structure`: the table schema of the generated table
|
|
- `input_query`: an optional query (or collection or queries) whose results are passed to the script via **stdin**
|
|
|
|
:::note
|
|
If you are going to invoke the same script repeatedly with the same input queries, consider using the [`Executable` table engine](../../engines/table-engines/special/executable.md).
|
|
:::
|
|
|
|
The following Python script is named `generate_random.py` and is saved in the `user_scripts` folder. It reads in a number `i` and prints `i` random strings, with each string preceded by a number that is separated by a tab:
|
|
|
|
```python
|
|
#!/usr/local/bin/python3.9
|
|
|
|
import sys
|
|
import string
|
|
import random
|
|
|
|
def main():
|
|
|
|
# Read input value
|
|
for number in sys.stdin:
|
|
i = int(number)
|
|
|
|
# Generate some random rows
|
|
for id in range(0, i):
|
|
letters = string.ascii_letters
|
|
random_string = ''.join(random.choices(letters ,k=10))
|
|
print(str(id) + '\t' + random_string + '\n', end='')
|
|
|
|
# Flush results to stdout
|
|
sys.stdout.flush()
|
|
|
|
if __name__ == "__main__":
|
|
main()
|
|
```
|
|
|
|
Let's invoke the script and have it generate 10 random strings:
|
|
|
|
```sql
|
|
SELECT * FROM executable('my_script.py', TabSeparated, 'id UInt32, random String', (SELECT 10))
|
|
```
|
|
|
|
The response looks like:
|
|
|
|
```response
|
|
┌─id─┬─random─────┐
|
|
│ 0 │ xheXXCiSkH │
|
|
│ 1 │ AqxvHAoTrl │
|
|
│ 2 │ JYvPCEbIkY │
|
|
│ 3 │ sWgnqJwGRm │
|
|
│ 4 │ fTZGrjcLon │
|
|
│ 5 │ ZQINGktPnd │
|
|
│ 6 │ YFSvGGoezb │
|
|
│ 7 │ QyMJJZOOia │
|
|
│ 8 │ NfiyDDhmcI │
|
|
│ 9 │ REJRdJpWrg │
|
|
└────┴────────────┘
|
|
```
|
|
|
|
## Passing Query Results to a Script
|
|
|
|
Be sure to check out the example in the `Executable` table engine on [how to pass query results to a script](../../engines/table-engines/special/executable.md#passing-query-results-to-a-script). Here is how you execute the same script in that example using the `executable` table function:
|
|
|
|
```sql
|
|
SELECT * FROM executable(
|
|
'sentiment.py',
|
|
TabSeparated,
|
|
'id UInt64, sentiment Float32',
|
|
(SELECT id, comment FROM hackernews WHERE id > 0 AND comment != '' LIMIT 20)
|
|
);
|
|
``` |