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Asynchronous Low Latency C++ Logging Library

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Quill

Asynchronous Low Latency C++ Logging Library


homebrew vcpkg conan
brew install quill vcpkg install quill quill/[>=1.2.3]

Introduction

Quill is a cross-platform low latency logging library based on C++14/C++17.

There are two versions on the library:

v1.7 : C++14 - Bug fix only

v2 : C++17 - New features and actively maintained

Documentation

ReadtheDocs

The examples folder is also a good source of documentation.

Features

  • Low latency logging See Benchmarks.
  • Format outside the hot-path in a backend logging thread. For non-built-in types ostream::operator<<() is called on a copy of the object by the backend logging thread. Unsafe to copy non-trivial user defined are detected in compile time. Those types can be tagged as safe-to-copy to avoid formatting them on the hot path. See User Defined Types.
  • Custom formatters. Logs can be formatted based on a user specified pattern. See Formatters.
  • Support for rdtsc, chrono or custom clock (usefull for simulations) for timestamp generation.
  • Support for log stack traces. Store log messages in a ring buffer and display later on a higher severity log statement or on demand. See Backtrace Logging.
  • Various logging targets. See Handlers.
    • Console logging with colours support.
    • File Logging
    • Rotating log files
    • Time rotating log files
    • JSON logging
    • Custom Handlers
  • Filters for filtering log messages. See Filters.
  • Ability to produce JSON structured log. See Structured-Log
  • guaranteed non-blocking or non-guaranteed logging. In non-guaranteed mode there is no heap allocation of a new queue but log messages can be dropped. See FAQ.
  • Support for wide character logging and wide character filenames (Windows and v1.7.x only).
  • Log statements in timestamp order even when produced by different threads. This makes debugging multithreading applications easier.
  • Log levels can be completely stripped out at compile time reducing if branches.
  • Clean warning-free codebase even on high warning levels.
  • Crash safe behaviour with a built-in signal handler.
  • Type safe python style API with compile type checks and built-in support for logging STL types/containers by using the excellent {fmt} library.

Performance

Latency

Log Numbers

The following message is logged 100'000 times per thread LOG_INFO(logger, "Logging int: {}, int: {}, double: {}", i, j, d).

The results in the tables below are in nanoseconds (ns).

1 Thread
Library 50th 75th 90th 95th 99th 99.9th
Quill v2.8.0 Unbounded Queue 20 21 24 25 27 34
Quill v2.8.0 Bounded Queue 17 19 21 22 26 36
fmtlog 16 19 21 22 27 40
MS BinLog 41 43 44 46 66 118
PlatformLab NanoLog 53 66 75 80 92 106
Reckless 62 75 79 84 94 103
Iyengar NanoLog 164 186 213 232 305 389
spdlog 694 761 838 887 996 1143
g3log 5398 5639 5875 6025 6327 6691
4 Threads
Library 50th 75th 90th 95th 99th 99.9th
Quill v2.8.0 Unbounded Queue 20 22 24 26 28 35
Quill v2.8.0 Bounded Queue 17 19 21 22 26 36
fmtlog 16 19 21 23 26 35
MS BinLog 42 44 46 48 76 118
PlatformLab NanoLog 56 67 77 82 95 159
Reckless 46 62 78 92 113 155
Iyengar NanoLog 150 168 247 289 355 456
spdlog 728 828 907 959 1140 1424
g3log 5103 5318 5525 5657 5927 6279

Log Numbers and Large Strings

The following message is logged 100'000 times per thread LOG_INFO(logger, "Logging int: {}, int: {}, string: {}", i, j, large_string). The large string is over 35 characters to avoid short string optimisation of std::string

1 Thread
Library 50th 75th 90th 95th 99th 99.9th
Quill v2.8.0 Unbounded Queue 31 33 35 36 39 48
Quill v2.8.0 Bounded Queue 30 32 33 35 43 51
fmtlog 29 31 34 37 44 53
MS BinLog 50 51 53 56 77 127
PlatformLab NanoLog 71 86 105 117 136 158
Reckless 215 242 268 284 314 517
Iyengar NanoLog 172 191 218 238 312 401
spdlog 653 708 770 831 950 1083
g3log 4802 4998 5182 5299 5535 5825
4 Threads
Library 50th 75th 90th 95th 99th 99.9th
Quill v2.8.0 Unbounded Queue 31 33 35 37 40 48
Quill v2.8.0 Bounded Queue 29 31 33 35 41 49
fmtlog 29 31 35 37 44 54
MS BinLog 50 52 54 58 86 130
PlatformLab NanoLog 69 82 99 111 134 194
Reckless 187 209 232 247 291 562
Iyengar NanoLog 159 173 242 282 351 472
spdlog 679 751 839 906 1132 1478
g3log 4739 4955 5157 5284 5545 5898

The benchmarks are done on Ubuntu - Intel(R) Xeon(R) Gold 6254 CPU @ 3.10GHz with GCC 12.2

Each thread is pinned on a different cpu. Unfortunately the cores are not isolated on this system. If the backend logging thread is run in the same CPU as the caller hot-path threads, that slows down the log message processing on the backend logging thread and will cause the SPSC queue to fill faster and re-allocate.

Continuously logging messages in a loop makes the consumer (backend logging thread) unable to follow up and the queue will have to re-allocate or block for most logging libraries expect very high throughput binary loggers like PlatformLab Nanolog.

Therefore, a different approach was followed that suits more to a real time application:

  1. 20 messages are logged in a loop.
  2. calculate/store the average latency for those messages.
  3. wait between 1-2 ms.
  4. repeat for n iterations.

I run each logger benchmark 4 times and the above latencies are the second-best result.

The benchmark code and results can be found here.

Throughput

The main focus of the library is not throughput. The backend logging thread is a single thread responsible for formatting, ordering the log messages from multiple hot threads and finally outputting everything as human-readable text. The logging thread always empties all the queues of the hot threads on the highest priority (to avoid allocating a new queue or dropping messages on the hot path). To achieve that, it internally buffers the log messages and then writes them later when the hot thread queues are empty or when a limit is reached backend_thread_transit_events_soft_limit.

I haven't found an easy way to compare the throughput against other logging libraries while doing asynchronous logging. For example some libraries will drop the log messages ending in producing much smaller log files than the expected, other libraries only offer an async flush meaning that you never really know when the logging thread has finished processing everything.

Quill has a blocking flush() guaranteeing every single log message from the hot threads up to that point is flushed to the file. The maximum throughput is measured as the max log messages number the backend logging thread can write to the file per second.

Benchmark code can be found here

Measured on the same system as the latency benchmarks above for 4 million messages produces a log file of 476 mb

1.76 million msgs/sec average, total time elapsed 2266 ms, total log messages 4 million

Basic usage

#include "quill/Quill.h"

int main()
{
  quill::Config cfg;
  cfg.enable_console_colours = true;
  quill::configure(cfg);
  quill::start();

  quill::Logger* logger = quill::get_logger();
  logger->set_log_level(quill::LogLevel::TraceL3);

  // enable a backtrace that will get flushed when we log CRITICAL
  logger->init_backtrace(2, quill::LogLevel::Critical);

  LOG_BACKTRACE(logger, "Backtrace log {}", 1);
  LOG_BACKTRACE(logger, "Backtrace log {}", 2);

  LOG_INFO(logger, "Welcome to Quill!");
  LOG_ERROR(logger, "An error message. error code {}", 123);
  LOG_WARNING(logger, "A warning message.");
  LOG_CRITICAL(logger, "A critical error.");
  LOG_DEBUG(logger, "Debugging foo {}", 1234);
  LOG_TRACE_L1(logger, "{:>30}", "right aligned");
  LOG_TRACE_L2(logger, "Positional arguments are {1} {0} ", "too", "supported");
  LOG_TRACE_L3(logger, "Support for floats {:03.2f}", 1.23456);
}

Output

Screenshot-2020-08-14-at-01-09-43.png

CMake-Integration

External

Building and Installing Quill as Static Library
git clone http://github.com/odygrd/quill.git
mkdir cmake_build
cd cmake_build
make install

Note: To install in custom directory invoke cmake with -DCMAKE_INSTALL_PREFIX=/quill/install-dir/

Building and Installing Quill as Static Library With External libfmt
cmake -DCMAKE_PREFIX_PATH=/my/fmt/fmt-config.cmake-directory/ -DQUILL_FMT_EXTERNAL=ON -DCMAKE_INSTALL_PREFIX=/quill/install-dir/'

Then use the library from a CMake project, you can locate it directly with find_package()

Directory Structure
my_project/
├── CMakeLists.txt
├── main.cpp
CMakeLists.txt
# Set only if needed - quill was installed under a custom non-standard directory
set(CMAKE_PREFIX_PATH /test_quill/usr/local/)

find_package(quill REQUIRED)

# Linking your project against quill
add_executable(example main.cpp)
target_link_libraries(example PRIVATE quill::quill)
main.cpp

See basic usage

Embedded

To embed the library directly, copy the source folder to your project and call add_subdirectory() in your CMakeLists.txt file

Directory Structure
my_project/
├── quill/            (source folder)
├── CMakeLists.txt
├── main.cpp
CMakeLists.txt
cmake_minimum_required(VERSION 3.1.0)
project(my_project)

set(CMAKE_CXX_STANDARD 14)

add_subdirectory(quill)

add_executable(my_project main.cpp)
target_link_libraries(my_project PRIVATE quill::quill)
main.cpp

See basic usage

Design

design.jpg

License

Quill is licensed under the MIT License

Quill depends on third party libraries with separate copyright notices and license terms. Your use of the source code for these subcomponents is subject to the terms and conditions of the following licenses.

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