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Hacking simdjson

Here is wisdom about how to build, test and run simdjson from within the repository. This is mostly useful for people who plan to contribute simdjson, or maybe study the design.

If you plan to contribute to simdjson, please read our CONTRIBUTING guide.

Design notes

The parser works in two stages:

  • Stage 1. (Find marks) Identifies quickly structure elements, strings, and so forth. We validate UTF-8 encoding at that stage.
  • Stage 2. (Structure building) Involves constructing a "tree" of sort (materialized as a tape) to navigate through the data. Strings and numbers are parsed at this stage.

The role of stage 1 is to identify pseudo-structural characters as quickly as possible. A character is pseudo-structural if and only if:

  1. Not enclosed in quotes, AND
  2. Is a non-whitespace character, AND
  3. Its preceding character is either: (a) a structural character, OR (b) whitespace OR (c) the final quote in a string.

This helps as we redefine some new characters as pseudo-structural such as the characters 1, G, n in the following:

{ "foo" : 1.5, "bar" : 1.5 GEOFF_IS_A_DUMMY bla bla , "baz", null }

Stage 1 also does unicode validation.

Stage 2 handles all of the rest: number parsings, recognizing atoms like true, false, null, and so forth.

Developer mode

Build system targets that are only useful for developers of the simdjson library are behind the SIMDJSON_DEVELOPER_MODE option. Enabling this option makes tests, examples, benchmarks and other developer targets available. Not enabling this option means that you are a consumer of simdjson and thus you only get the library targets and options.

Developer mode is forced to be on when the CI environment variable is set to a value that CMake recognizes as "on", which is set to true in all of the CI workflows used by simdjson.

Directory Structure and Source

simdjson's source structure, from the top level, looks like this:

  • CMakeLists.txt: The main build system.
  • include: User-facing declarations and inline definitions (most user-facing functions are inlined).
    • simdjson.h: A "main include" that includes files from include/simdjson/. This is equivalent to the distributed simdjson.h.
    • simdjson/*.h: Declarations for public simdjson classes and functions.
    • simdjson/*-inl.h: Definitions for public simdjson classes and functions.
  • src: The source files for non-inlined functionality (e.g. the architecture-specific parser implementations).
    • simdjson.cpp: A "main source" that includes all implementation files from src/. This is equivalent to the distributed simdjson.cpp.
    • arm64/|fallback/|haswell/|ppc64/|westmere/: Architecture-specific implementations. All functions are Each architecture defines its own namespace, e.g. simdjson::haswell.
    • generic/: Generic implementations of the simdjson parser. These files may be included and compiled multiple times, from whichever architectures use them. They assume they are already enclosed in a namespace, e.g.: 
      namespace simdjson {
  namespace haswell {
    #include "generic/stage1/json_structural_indexer.h"
  }
}

Other important files and directories:

  • .drone.yml: Definitions for Drone CI.
  • .appveyor.yml: Definitions for Appveyor CI (Windows).
  • .circleci: Definitions for Circle CI.
  • .github/workflows: Definitions for GitHub Actions (CI).
  • singleheader: Contains generated simdjson.h and simdjson.cpp that we release. The files singleheader/simdjson.h and singleheader/simdjson.cpp should never be edited by hand.
  • singleheader/amalgamate.py: Generates singleheader/simdjson.h and singleheader/simdjson.cpp for release (python script).
  • benchmark: This is where we do benchmarking. Benchmarking is core to every change we make; the cardinal rule is don't regress performance without knowing exactly why, and what you're trading for it. Many of our benchmarks are microbenchmarks. We are effectively doing controlled scientific experiments for the purpose of understanding what affects our performance. So we simplify as much as possible. We try to avoid irrelevant factors such as page faults, interrupts, unnecessary system calls. We recommend checking the performance as follows: 
    mkdir build
cd build
cmake -D SIMDJSON_DEVELOPER_MODE=ON ..
cmake --build . --config Release
benchmark/dom/parse ../jsonexamples/twitter.json
    The last line becomes ./benchmark/Release/parse.exe ../jsonexample/twitter.json under Windows. You may also use Google Benchmark: 
    mkdir build
cd build
cmake -D SIMDJSON_DEVELOPER_MODE=ON ..
cmake --build . --target bench_parse_call --config Release
./benchmark/bench_parse_call
    The last line becomes ./benchmark/Release/bench_parse_call.exe under Windows. Under Windows, you can also build with the clang compiler by adding -T ClangCL to the call to cmake ..: cmake -T ClangCL ...
  • fuzz: The source for fuzz testing. This lets us explore important edge and middle cases
  • fuzz: The source for fuzz testing. This lets us explore important edge and middle cases automatically, and is run in CI.
  • jsonchecker: A set of JSON files used to check different functionality of the parser.
    • pass.json:* Files that should pass validation.
    • fail.json:* Files that should fail validation.
    • jsonchecker/minefield/y_*.json: Files that should pass validation.
    • jsonchecker/minefield/n_*.json: Files that should fail validation.
  • jsonexamples: A wide spread of useful, real-world JSON files with different characteristics and sizes.
  • test: The tests are here. basictests.cpp and errortests.cpp are the primary ones.
  • tools: Source for executables that can be distributed with simdjson. Some examples:
    • json2json mydoc.json parses the document, constructs a model and then dumps back the result to standard output.
    • json2json -d mydoc.json parses the document, constructs a model and then dumps model (as a tape) to standard output. The tape format is described in the accompanying file tape.md.
    • minify mydoc.json minifies the JSON document, outputting the result to standard output. Minifying means to remove the unneeded white space characters.
    • jsonpointer mydoc.json <jsonpath> <jsonpath> ... <jsonpath> parses the document, constructs a model and then processes a series of JSON Pointer paths. The result is itself a JSON document.

Don't modify the files in singleheader/ directly; these are automatically generated.

While simdjson distributes just two files from the singleheader/ directory, we maintain the code in multiple files under include/ and src/. The files include/simdjson.h and src/simdjson.cpp are the "spine" for these, and you can include them as if they were the corresponding singleheader/ files.

Runtime Dispatching

A key feature of simdjson is the ability to compile different processing kernels, optimized for specific instruction sets, and to select the most appropriate kernel at runtime. This ensures that users get the very best performance while still enabling simdjson to run everywhere. This technique is frequently called runtime dispatching. The simdjson achieves runtime dispatching entirely in C++: we do not assume that the user is building the code using CMake, for example.

To make runtime dispatching work, it is critical that the code be compiled for the lowest supported processor. In particular, you should not use flags such as -mavx2, /arch:AVX2 and so forth while compiling simdjson. When you do so, you allow the compiler to use advanced instructions. In turn, these advanced instructions present in the code may cause a runtime failure if the runtime processor does not support them. Even a simple loop, compiled with these flags, might generate binary code that only run on advanced processors.

So we compile simdjson for a generic processor. Our users should do the same if they want simdjson's runtime dispatch to work. It is important to understand that if runtime dispatching does not work, then simdjson will cause crashes on older processors. Of course, if a user chooses to compile their code for a specific instruction set (e.g., AVX2), they are responsible for the failures if they later run their code on a processor that does not support AVX2. Yet, if we were to entice these users to do so, we would share the blame: thus we carefully instruct users to compile their code in a generic way without doing anything to enable advanced instructions.

We only use runtime dispatching on x64 (AMD/Intel) platforms, at the moment. On ARM processors, we would need a standard way to query, at runtime, the processor for its supported features. We do not know how to do so on ARM systems in general. Thankfully it is not yet a concern: 64-bit ARM processors are fairly uniform as far as the instruction sets they support.

In all cases, simdjson uses advanced instructions by relying on "intrinsic functions": we do not write assembly code. The intrinsic functions are special functions that the compiler might recognize and translate into fast code. To make runtime dispatching work, we rely on the fact that the header providing these instructions (intrin.h under Visual Studio, x86intrin.h elsewhere) defines all of the intrinsic functions, including those that are not supported processor.

At this point, we are require to use one of two main strategies.

  1. On POSIX systems, the main compilers (LLVM clang, GNU gcc) allow us to use any intrinsic function after including the header, but they fail to inline the resulting instruction if the target processor does not support them. Because we compile for a generic processor, we would not be able to use most intrinsic functions. Thankfully, more recent versions of these compilers allow us to flag a region of code with a specific target, so that we can compile only some of the code with support for advanced instructions. Thus in our C++, one might notice macros like TARGET_HASWELL. It is then our responsibility, at runtime, to only run the regions of code (that we call kernels) matching the properties of the runtime processor. The benefit of this approach is that the compiler not only let us use intrinsic functions, but it can also optimize the rest of the code in the kernel with advanced instructions we enabled.

  2. Under Visual Studio, the problem is somewhat simpler. Visual Studio will not only provide the intrinsic functions, but it will also allow us to use them. They will compile just fine. It is at runtime that they may cause a crash. So we do not need to mark regions of code for compilation toward advanced processors (e.g., with TARGET_HASWELL macros). The downside of the Visual Studio approach is that the compiler is not allowed to use advanced instructions others than those we specify. In principle, this means that Visual Studio has weaker optimization opportunities.

We also handle the special case where a user is compiling using LLVM clang under Windows, using the Visual Studio toolchain. If you compile with LLVM clang under Visual Studio, then the header files (intrin.h or x86intrin.h) no longer provides the intrinsic functions that are unsupported by the processor. This appears to be deliberate on the part of the LLVM engineers. With a few lines of code, we handle this scenario just like LLVM clang under a POSIX system, but forcing the inclusion of the specific headers, and rolling our own intrinsic function as needed.

Regenerating Single-Header Files

The simdjson.h and simdjson.cpp files in the singleheader directory are not always up-to-date with the rest of the code; they are only ever systematically regenerated on releases. To ensure you have the latest code, you can regenerate them by running this at the top level:

mkdir build
cd build
cmake -D SIMDJSON_DEVELOPER_MODE=ON ..
cmake --build . # needed, because currently dependencies do not work fully for the amalgamate target
cmake --build . --target amalgamate

You need to have python3 installed on your system.

The amalgamator script amalgamate.py generates singleheader/simdjson.h by reading through include/simdjson.h, copy/pasting each header file into the amalgamated file at the point it gets included (but only once per header). singleheader/simdjson.cpp is generated from src/simdjson.cpp the same way, except files under generic/ may be included and copy/pasted multiple times.

Usage (CMake on 64-bit platforms like Linux, FreeBSD or macOS)

Requirements: In addition to git, we require a recent version of CMake as well as bash.

  1. On macOS, the easiest way to install cmake might be to use brew and then type
brew install cmake
  1. Under Linux, you might be able to install CMake as follows:
apt-get update -qq
apt-get install -y cmake
  1. On FreeBSD, you might be able to install bash and CMake as follows:
pkg update -f
pkg install bash
pkg install cmake

You need a recent compiler like clang or gcc. We recommend at least GNU GCC/G++ 7 or LLVM clang 6.

Building: While in the project repository, do the following:

mkdir build
cd build
cmake -D SIMDJSON_DEVELOPER_MODE=ON ..
cmake --build .
ctest

CMake will build a library. By default, it builds a static library (e.g., libsimdjson.a on Linux).

You can build a shared library:

mkdir buildshared
cd buildshared
cmake -D BUILD_SHARED_LIBS=ON -D SIMDJSON_DEVELOPER_MODE=ON ..
cmake --build .
ctest

In some cases, you may want to specify your compiler, especially if the default compiler on your system is too old. You need to tell cmake which compiler you wish to use by setting the CC and CXX variables. Under bash, you can do so with commands such as export CC=gcc-7 and export CXX=g++-7. You can also do it as part of the cmake command: cmake -DCMAKE_CXX_COMPILER=g++ ... You may proceed as follows:

brew install gcc@8
mkdir build
cd build
export CXX=g++-8 CC=gcc-8
cmake -D SIMDJSON_DEVELOPER_MODE=ON ..
cmake --build .
ctest

If your compiler does not default on C++11 support or better you may get failing tests. If so, you may be able to exclude the failing tests by replacing ctest with ctest -E "^quickstart$".

Note that the name of directory (build) is arbitrary, you can name it as you want (e.g., buildgcc) and you can have as many different such directories as you would like (one per configuration).

Usage (CMake on 64-bit Windows using Visual Studio 2019)

We assume you have a common 64-bit Windows PC with at least Visual Studio 2019.

  • Grab the simdjson code from GitHub, e.g., by cloning it using GitHub Desktop.
  • Install CMake. When you install it, make sure to ask that cmake be made available from the command line. Please choose a recent version of cmake.
  • Create a subdirectory within simdjson, such as build.
  • Using a shell, go to this newly created directory. You can start a shell directly from GitHub Desktop (Repository > Open in Command Prompt).
  • Type cmake .. in the shell while in the build repository.
  • This last command (cmake ...) created a Visual Studio solution file in the newly created directory (e.g., simdjson.sln). Open this file in Visual Studio. You should now be able to build the project and run the tests. For example, in the Solution Explorer window (available from the View menu), right-click ALL_BUILD and select Build. To test the code, still in the Solution Explorer window, select RUN_TESTS and select Build.

Though having Visual Studio installed is necessary, one can build simdjson using only cmake commands:

  • mkdir build
  • cd build
  • cmake ..
  • cmake --build . -config Release

Furthermore, if you have installed LLVM clang on Windows, for example as a component of Visual Studio 2019, you can configure and build simdjson using LLVM clang on Windows using cmake:

  • mkdir build
  • cd build
  • cmake -T ClangCL ..
  • cmake --build . -config Release

Various References

Inspiring links: