11 KiB
slug | sidebar_position | sidebar_label |
---|---|---|
/en/sql-reference/functions/udf | 15 | UDF |
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 ifexecute_direct
is false.argument
- argument description with thetype
, and optionalname
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 isc
+ 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 isresult
.type
- an executable type. Iftype
is set toexecutable
then single command is started. If it is set toexecutable_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 forexecutable_pool
commands only. Optional. Default value is10
.command_termination_timeout
- time in seconds during which a command should finish after its pipe is closed. After that timeSIGTERM
is sent to the process executing the command. Optional. Default value is10
.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 is16
.send_chunk_header
- controls whether to send row count before sending a chunk of data to process. Optional. Default value isfalse
.execute_direct
- Ifexecute_direct
=1
, thencommand
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
. Ifexecute_direct
=0
,command
is passed as argument forbin/sh -c
. Default value is1
. Optional parameter.lifetime
- the reload interval of a function in seconds. If it is set to0
then the function is not reloaded. Default value is0
. 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.