ClickHouse/docs/en/sql-reference/table-functions/executable.md

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/en/engines/table-functions/executable	55	executable	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:

executable(script_name, format, structure, [input_query...] [,SETTINGS ...])

• 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. :::

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:

#!/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:

SELECT * FROM executable('my_script.py', TabSeparated, 'id UInt32, random String', (SELECT 10))

The response looks like:

┌─id─┬─random─────┐
│  0 │ xheXXCiSkH │
│  1 │ AqxvHAoTrl │
│  2 │ JYvPCEbIkY │
│  3 │ sWgnqJwGRm │
│  4 │ fTZGrjcLon │
│  5 │ ZQINGktPnd │
│  6 │ YFSvGGoezb │
│  7 │ QyMJJZOOia │
│  8 │ NfiyDDhmcI │
│  9 │ REJRdJpWrg │
└────┴────────────┘

Settings

• send_chunk_header - controls whether to send row count before sending a chunk of data to process. Default value is false.
• pool_size — Size of pool. If 0 is specified as pool_size then there is no pool size restrictions. Default value is 16.
• max_command_execution_time — Maximum executable script command execution time for processing block of data. Specified in seconds. Default value is 10.
• command_termination_timeout — executable script should contain main read-write loop. After table function is destroyed, pipe is closed, and executable file will have command_termination_timeout seconds to shutdown, before ClickHouse will send SIGTERM signal to child process. Specified in seconds. Default value is 10.
• command_read_timeout - timeout for reading data from command stdout in milliseconds. Default value 10000.
• command_write_timeout - timeout for writing data to command stdin in milliseconds. Default value 10000.

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. Here is how you execute the same script in that example using the executable table function:

SELECT * FROM executable(
    'sentiment.py',
    TabSeparated,
    'id UInt64, sentiment Float32',
    (SELECT id, comment FROM hackernews WHERE id > 0 AND comment != '' LIMIT 20)
);