Enhancing Real-Time Analytics with ClickHouse: A Deep Dive into User Defined Functions

Empower, Elevate, Automate – With ChistaDATA, transcend the limits of performance and automation in your data infrastructure.

User Defined Functions (UDF) in ClickHouse allow users to extend the native capabilities of the database by creating custom functions for specific use cases. UDFs in ClickHouse are usually written in C++ for performance reasons.

Steps to Build UDF in ClickHouse

1. Set Up the Development Environment

  • Clone the ClickHouse repository. 

git clone https://github.com/ClickHouse/ClickHouse.git

Install the necessary build tools and libraries.

2. Write the UDF

UDFs in ClickHouse are typically written in C++. For this example, let’s create a simple UDF that calculates the factorial of a number.

#include <Core/Types.h>
#include <Functions/IFunction.h>
#include <Functions/FunctionFactory.h>
namespace DB
class FunctionFactorial : public IFunction
static constexpr auto name = “factorial”;
static FunctionPtr create(const Context &)
return std::make_shared<FunctionFactorial>();
String getName() const override
return name;
size_t getNumberOfArguments() const override
return 1;
DataTypePtr getReturnTypeImpl(const DataTypes & arguments) const override
return std::make_shared<DataTypeUInt64>();
void executeImpl(Block & block, const ColumnNumbers & arguments, size_t result, size_t input_rows_count) override
auto * result_column = block.getByPosition(result).column.get();
const ColumnWithTypeAndName & argument_column = block.getByPosition(arguments[0]);
for (size_t row = 0; row < input_rows_count; ++row)
UInt64 value = argument_column.column->getUInt(row);
UInt64 factorial = 1;
for (UInt64 i = 1; i <= value; ++i)
factorial *= i;
void registerFunctionFactorial(FunctionFactory & factory)

3. Register the UDF

  • Add the registration code at the end of the UDF file.

class FunctionFactory;
void registerFunctionFactorial(FunctionFactory &);

Add the registration function to the build system.

4. Compile and Install ClickHouse with the UDF

  1. Build ClickHouse with the custom function. 
  2. Install and restart ClickHouse. 

5. Use the UDF

SELECT factorial(5); — Expected output: 120

Benefits of UDFs in ClickHouse:

  1. Customization: Tailor ClickHouse to your specific needs.
  2. Performance: Being written in C++, UDFs are compiled into native code, ensuring high performance.
  3. Flexibility: Integrate third-party libraries or proprietary algorithms directly into ClickHouse.


ClickHouse, with its capabilities to support User Defined Functions, is not just a database, but a powerful platform for high-performance real-time analytics. For businesses operating at webscale, the ability to customize and enhance their analytics infrastructure is invaluable. By developing advanced real-time analytics using ClickHouse, companies can derive actionable insights from vast amounts of data in real-time, allowing them to make informed decisions rapidly and stay ahead in the competitive global marketplace.

Unlock Next-Level Performance with ChistaDATA! 🚀 Dive into unparalleled efficiency with our custom server extensions and top-tier production engineering tools. Achieve extreme automation and elevate your Data SRE operations. Ready to transform your infrastructure? Reach out to us at info@chistadata.com or visit chistadata.com/chistadata-contact/. Let ChistaDATA be your catalyst for superior performance and automation!

About Shiv Iyer 199 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.