UDFs User Defined Functions

Executable User Defined Functions

ClickHouse can call any external executable program or script to process data.

The configuration of executable user defined functions can be located in one or more xml-files. The path to the configuration is specified in the user_defined_executable_functions_config parameter.

A function configuration contains the following settings:

name - a function name.
command - script name to execute or command if execute_direct is false.
argument - argument description with the type, and optional name of an argument. Each argument is described in a separate setting. Specifying name is necessary if argument names are part of serialization for user defined function format like Native or JSONEachRow. Default argument name value is c + argument_number.
format - a format in which arguments are passed to the command.
return_type - the type of a returned value.
return_name - name of returned value. Specifying return name is necessary if return name is part of serialization for user defined function format like Native or JSONEachRow. Optional. Default value is result.
type - an executable type. If type is set to executable then single command is started. If it is set to executable_pool then a pool of commands is created.
max_command_execution_time - maximum execution time in seconds for processing block of data. This setting is valid for executable_pool commands only. Optional. Default value is 10.
command_termination_timeout - time in seconds during which a command should finish after its pipe is closed. After that time SIGTERM is sent to the process executing the command. Optional. Default value is 10.
command_read_timeout - timeout for reading data from command stdout in milliseconds. Default value 10000. Optional parameter.
command_write_timeout - timeout for writing data to command stdin in milliseconds. Default value 10000. Optional parameter.
pool_size - the size of a command pool. Optional. Default value is 16.
send_chunk_header - controls whether to send row count before sending a chunk of data to process. Optional. Default value is false.
execute_direct - If execute_direct = 1, then command will be searched inside user_scripts folder specified by user_scripts_path. Additional script arguments can be specified using whitespace separator. Example: script_name arg1 arg2. If execute_direct = 0, command is passed as argument for bin/sh -c. Default value is 1. Optional parameter.
lifetime - the reload interval of a function in seconds. If it is set to 0 then the function is not reloaded. Default value is 0. Optional parameter.

The command must read arguments from STDIN and must output the result to STDOUT. The command must process arguments iteratively. That is after processing a chunk of arguments it must wait for the next chunk.

Example

Creating test_function using XML configuration. File test_function.xml (/etc/clickhouse-server/test_function.xml with default path settings).

<functions>
    <function>
        <type>executable</type>
        <name>test_function_python</name>
        <return_type>String</return_type>
        <argument>
            <type>UInt64</type>
            <name>value</name>
        </argument>
        <format>TabSeparated</format>
        <command>test_function.py</command>
    </function>
</functions>

Script file inside user_scripts folder test_function.py (/var/lib/clickhouse/user_scripts/test_function.py with default path settings).

#!/usr/bin/python3

import sys

if __name__ == '__main__':
    for line in sys.stdin:
        print("Value " + line, end='')
        sys.stdout.flush()

Query:

SELECT test_function_python(toUInt64(2));

Result:

┌─test_function_python(2)─┐
│ Value 2                 │
└─────────────────────────┘

Creating test_function_sum manually specifying execute_direct to 0 using XML configuration. File test_function.xml (/etc/clickhouse-server/test_function.xml with default path settings).

<functions>
    <function>
        <type>executable</type>
        <name>test_function_sum</name>
        <return_type>UInt64</return_type>
        <argument>
            <type>UInt64</type>
            <name>lhs</name>
        </argument>
        <argument>
            <type>UInt64</type>
            <name>rhs</name>
        </argument>
        <format>TabSeparated</format>
        <command>cd /; clickhouse-local --input-format TabSeparated --output-format TabSeparated --structure 'x UInt64, y UInt64' --query "SELECT x + y FROM table"</command>
        <execute_direct>0</execute_direct>
    </function>
</functions>

Query:

SELECT test_function_sum(2, 2);

Result:

┌─test_function_sum(2, 2)─┐
│                       4 │
└─────────────────────────┘

Creating test_function_sum_json with named arguments and format JSONEachRow using XML configuration. File test_function.xml (/etc/clickhouse-server/test_function.xml with default path settings).

<functions>
    <function>
        <type>executable</type>
        <name>test_function_sum_json</name>
        <return_type>UInt64</return_type>
        <return_name>result_name</return_name>
        <argument>
            <type>UInt64</type>
            <name>argument_1</name>
        </argument>
        <argument>
            <type>UInt64</type>
            <name>argument_2</name>
        </argument>
        <format>JSONEachRow</format>
        <command>test_function_sum_json.py</command>
    </function>
</functions>

Script file inside user_scripts folder test_function_sum_json.py (/var/lib/clickhouse/user_scripts/test_function_sum_json.py with default path settings).

#!/usr/bin/python3

import sys
import json

if __name__ == '__main__':
    for line in sys.stdin:
        value = json.loads(line)
        first_arg = int(value['argument_1'])
        second_arg = int(value['argument_2'])
        result = {'result_name': first_arg + second_arg}
        print(json.dumps(result), end='\n')
        sys.stdout.flush()

Query:

SELECT test_function_sum_json(2, 2);

Result:

┌─test_function_sum_json(2, 2)─┐
│                            4 │
└──────────────────────────────┘

Executable user defined functions can take constant parameters configured in command setting (works only for user defined functions with executable type). It also requires the execute_direct option (to ensure no shell argument expansion vulnerability). File test_function_parameter_python.xml (/etc/clickhouse-server/test_function_parameter_python.xml with default path settings).

<functions>
    <function>
        <type>executable</type>
        <execute_direct>true</execute_direct>
        <name>test_function_parameter_python</name>
        <return_type>String</return_type>
        <argument>
            <type>UInt64</type>
        </argument>
        <format>TabSeparated</format>
        <command>test_function_parameter_python.py {test_parameter:UInt64}</command>
    </function>
</functions>

Script file inside user_scripts folder test_function_parameter_python.py (/var/lib/clickhouse/user_scripts/test_function_parameter_python.py with default path settings).

#!/usr/bin/python3

import sys

if __name__ == "__main__":
    for line in sys.stdin:
        print("Parameter " + str(sys.argv[1]) + " value " + str(line), end="")
        sys.stdout.flush()

Query:

SELECT test_function_parameter_python(1)(2);

Result:

┌─test_function_parameter_python(1)(2)─┐
│ Parameter 1 value 2                  │
└──────────────────────────────────────┘

Error Handling

Some functions might throw an exception if the data is invalid. In this case, the query is canceled and an error text is returned to the client. For distributed processing, when an exception occurs on one of the servers, the other servers also attempt to abort the query.

Evaluation of Argument Expressions

In almost all programming languages, one of the arguments might not be evaluated for certain operators. This is usually the operators &&, ||, and ?:. But in ClickHouse, arguments of functions (operators) are always evaluated. This is because entire parts of columns are evaluated at once, instead of calculating each row separately.

Performing Functions for Distributed Query Processing

For distributed query processing, as many stages of query processing as possible are performed on remote servers, and the rest of the stages (merging intermediate results and everything after that) are performed on the requestor server.

This means that functions can be performed on different servers. For example, in the query SELECT f(sum(g(x))) FROM distributed_table GROUP BY h(y),

if a distributed_table has at least two shards, the functions ‘g’ and ‘h’ are performed on remote servers, and the function ‘f’ is performed on the requestor server.
if a distributed_table has only one shard, all the ‘f’, ‘g’, and ‘h’ functions are performed on this shard’s server.

The result of a function usually does not depend on which server it is performed on. However, sometimes this is important. For example, functions that work with dictionaries use the dictionary that exists on the server they are running on. Another example is the hostName function, which returns the name of the server it is running on in order to make GROUP BY by servers in a SELECT query.

If a function in a query is performed on the requestor server, but you need to perform it on remote servers, you can wrap it in an ‘any’ aggregate function or add it to a key in GROUP BY.

SQL User Defined Functions

Custom functions from lambda expressions can be created using the CREATE FUNCTION statement. To delete these functions use the DROP FUNCTION statement.

UDFs User Defined Functions

Executable User Defined Functions​

Error Handling​

Evaluation of Argument Expressions​

Performing Functions for Distributed Query Processing​

SQL User Defined Functions​

Related Content​

User-defined functions in ClickHouse Cloud​

Executable User Defined Functions

Error Handling

Evaluation of Argument Expressions

Performing Functions for Distributed Query Processing

SQL User Defined Functions

Related Content

User-defined functions in ClickHouse Cloud