Go to file
John Keiser da34f9a253 Add Google Benchmark for calling conventions
- disable it on ubuntu 18.04 tests, which fail for [really can't figure
out why]
2020-02-18 08:37:07 -08:00
.circleci Trying to fix issue 465 (#466) 2020-01-27 11:25:23 -05:00
.github/workflows Refactor stage 2 into structural_parser class 2020-01-02 13:12:22 -07:00
benchmark Add Google Benchmark for calling conventions 2020-02-18 08:37:07 -08:00
dependencies Add Google Benchmark for calling conventions 2020-02-18 08:37:07 -08:00
doc fix for Issue 467 (#469) 2020-01-29 19:00:18 -05:00
extra Removing all stdout, stderr from main library. (#455) 2020-01-20 16:03:15 -05:00
fuzz Separate document state from ParsedJson 2020-02-07 10:02:36 -08:00
images Moved file to proper directory. 2019-04-18 13:30:27 -04:00
include Make valstat-ish parse APIs 2020-02-18 08:37:07 -08:00
jsonchecker Adding another test 2020-01-02 14:22:43 -05:00
jsonexamples Streams of JSON documents + Large files (>4GB) (#350) (#364) 2019-11-08 17:39:45 -05:00
scripts use unique_ptr in class parsedjson (#417) 2019-12-31 14:31:45 -05:00
singleheader Make "make amalgamate" more automatic (#480) 2020-02-03 12:51:24 -05:00
src Make valstat-ish parse APIs 2020-02-18 08:37:07 -08:00
style Hiding the pointer away... (#252) 2019-08-04 15:41:00 -04:00
tests Separate document state from ParsedJson 2020-02-07 10:02:36 -08:00
tools Separate document state from ParsedJson 2020-02-07 10:02:36 -08:00
windows dirent portable latest version (#435) 2020-01-07 18:41:57 -05:00
.appveyor.yml Add Google Benchmark for calling conventions 2020-02-18 08:37:07 -08:00
.clang-format We are adopting clang-format. 2019-08-01 15:40:07 -04:00
.dockerignore Bring .git into docker (#259) 2019-08-06 09:39:33 -04:00
.drone.yml Add Google Benchmark for calling conventions 2020-02-18 08:37:07 -08:00
.gitattributes Add sane defaults for .sh and such (#254) 2019-08-04 18:11:48 -04:00
.gitignore Add Google Benchmark for calling conventions 2020-02-18 08:37:07 -08:00
.gitmodules Add Google Benchmark for calling conventions 2020-02-18 08:37:07 -08:00
.travis.yml Adding style scripts. (#243) 2019-08-01 16:09:26 -04:00
AUTHORS Create AUTHORS 2018-12-27 20:46:57 -05:00
CMakeLists.txt Add Google Benchmark for calling conventions 2020-02-18 08:37:07 -08:00
CONTRIBUTING.md Update CONTRIBUTING.md 2020-01-27 09:37:55 -05:00
CONTRIBUTORS Upgrading gcc to gcc 8 2020-01-06 18:28:29 -05:00
Dockerfile Fixing amalgamate under ARM 2019-07-30 22:10:48 +00:00
LICENSE Updating again. 2019-02-08 10:05:50 -05:00
Makefile Make valstat-ish parse APIs 2020-02-18 08:37:07 -08:00
README.md Make valstat-ish parse APIs 2020-02-18 08:37:07 -08:00
amalgamation.sh Make valstat-ish parse APIs 2020-02-18 08:37:07 -08:00

README.md

simdjson : Parsing gigabytes of JSON per second

Build Status CircleCI Build Status Fuzzing Status

A C++ library to see how fast we can parse JSON with complete validation.

JSON documents are everywhere on the Internet. Servers spend a lot of time parsing these documents. We want to accelerate the parsing of JSON per se using commonly available SIMD instructions as much as possible while doing full validation (including character encoding). This library is part of the Awesome Modern C++ list.

Real-world usage

If you are planning to use simdjson in a product, please work from one of our releases.

Research article (VLDB Journal)

A description of the design and implementation of simdjson is in our research article:

We also have an informal blog post providing some background and context.

Some people enjoy reading our paper:

Talks

QCon San Francisco 2019 (best voted talk):

simdjson at QCon San Francisco 2019

Performance results

simdjson uses three-quarters less instructions than state-of-the-art parser RapidJSON and fifty percent less than sajson. To our knowledge, simdjson is the first fully-validating JSON parser to run at gigabytes per second on commodity processors.

On a Skylake processor, the parsing speeds (in GB/s) of various processors on the twitter.json file are as follows.

parser GB/s
simdjson 2.2
RapidJSON encoding-validation 0.51
RapidJSON encoding-validation, insitu 0.71
sajson (insitu, dynamic) 0.70
sajson (insitu, static) 0.97
dropbox 0.14
fastjson 0.26
gason 0.85
ultrajson 0.42
jsmn 0.28
cJSON 0.34
JSON for Modern C++ (nlohmann/json) 0.10

Requirements

  • We support 64-bit platforms like Linux or macOS, as well as Windows through Visual Studio 2017 or later.
  • A processor with
    • AVX2 (i.e., Intel processors starting with the Haswell microarchitecture released 2013 and AMD processors starting with the Zen microarchitecture released 2017),
    • or SSE 4.2 and CLMUL (i.e., Intel processors going back to Westmere released in 2010 or AMD processors starting with the Jaguar used in the PS4 and XBox One)
    • or a 64-bit ARM processor (ARMv8-A): this covers a wide range of mobile processors, including all Apple processors currently available for sale, going as far back as the iPhone 5s (2013).
  • A recent C++ compiler (e.g., GNU GCC or LLVM CLANG or Visual Studio 2017), we assume C++17. GNU GCC 7 or better or LLVM's clang 6 or better.
  • Some benchmark scripts assume bash and other common utilities, but they are optional.

License

This code is made available under the Apache License 2.0.

Under Windows, we build some tools using the windows/dirent_portable.h file (which is outside our library code): it under the liberal (business-friendly) MIT license.

Runtime dispatch

On Intel and AMD processors, we get best performance by using the hardware support for AVX2 instructions. However, simdjson also runs on older Intel and AMD processors. We require a minimum feature support of SSE 4.2 and CLMUL (2010 Intel Westmere or better). The code automatically detects the feature set of your processor and switches to the right function at runtime (a technique sometimes called runtime dispatch).

On x64 hardware, you should typically build your code by specifying the oldest/less-featureful system you want to support so that runtime dispatch may work. The minimum requirement for simdjson is the equivalent of a Westmere processor (SSE 4.2 and PCLMUL). If you build your code by asking the compiler to use more advanced instructions (e.g., -mavx2, /AVX2 or -march=haswell), then it will break runtime dispatch and your binaries will fail to run on older processors.

We also support 64-bit ARM. We assume NEON support. There is no runtime dispatch on ARM.

Computed GOTOs

For best performance, we use a technique called "computed goto", it is also sometimes described as "Labels as Values". Though it is not part of the C++ standard, it is supported by many major compilers and it brings measurable performance benefits that are difficult to achieve otherwise. The computed gotos are automatically disabled under Visual Studio. If you wish to forcefully disable computed gotos, you can do so by compiling the code with the macro SIMDJSON_NO_COMPUTED_GOTO defined. It is not recommended to disable computed gotos if your compiler supports it. In fact, you should almost never need to be concerned with computed gotos.

Thread safety

The simdjson library is mostly single-threaded. Thread safety is the responsability of the caller: it is unsafe to reuse a ParsedJson object between different threads.

If you are on an x64 processor, the runtime dispatching assigns the right code path the first time that parsing is attempted. The runtime dispatching is thread-safe.

The json stream parser is threaded, using exactly two threads.

Large files

If you are processing large files (e.g., 100 MB), it is likely that the performance of simdjson will be limited by page misses and/or page allocation. On some systems, memory allocation runs far slower than we can parse (e.g., 1.4GB/s).

You will get best performance with large or huge pages. Under Linux, you can enable transparent huge pages with a command like echo always > /sys/kernel/mm/transparent_hugepage/enabled (root access may be required). We recommend that you report performance numbers with and without huge pages.

Another strategy is to reuse pre-allocated buffers. That is, you avoid reallocating memory. You just allocate memory once and reuse the blocks of memory.

Code usage and example

The main API involves populating a ParsedJson object which hosts a fully navigable document-object-model (DOM) view of the JSON document. The DOM can be accessed using JSON Pointer paths, for example. The main function is json_parse which takes a string containing the JSON document as well as a reference to pre-allocated ParsedJson object (which can be reused multiple time). Once you have populated the ParsedJson object you can navigate through the DOM with an iterator (e.g., created by ParsedJson::Iterator pjh(pj), see 'Navigating the parsed document').

// Samples: // Load a document from a file // Read a particular key / value from the document // Iterate over an array of things

#include "simdjson.h"
auto doc = simdjson::document::load("myfile.json");
cout << doc;
for (auto i=doc.begin(); i<doc.end(); i++) {
  cout << doc[i];
}

A slightly simpler API is available if you don't mind having the overhead of memory allocation with each new JSON document:

#include "simdjson/jsonparser.h"
using namespace simdjson;

document doc = document::parse("myfile.json");
cout << doc;
/...

const char * filename = ... //
padded_string p = get_corpus(filename);
ParsedJson pj = build_parsed_json(p); // do the parsing
if( ! pj.is_valid() ) {
    // something went wrong
    std::cout << pj.get_error_message() << std::endl;
}

Though the padded_string class is recommended for best performance, you can call json_parse and build_parsed_json, passing a standard std::string object.

#include "simdjson/jsonparser.h"
using namespace simdjson;

/...
std::string mystring = ... //
ParsedJson pj;
pj.allocate_capacity(mystring.size()); // allocate memory for parsing up to p.size() bytes
// std::string may not overallocate so a copy will be needed
const int res = json_parse(mystring, pj); // do the parsing, return 0 on success
// parsing is done!
if (res != 0) {
    // You can use the "simdjson/simdjson.h" header to access the error message
    std::cout << "Error parsing:" << simdjson::error_message(res) << std::endl;
}
// pj can be reused with other json_parse calls.

or

#include "simdjson/jsonparser.h"
using namespace simdjson;

/...

std::string mystring = ... //
// std::string may not overallocate so a copy will be needed
ParsedJson pj = build_parsed_json(mystring); // do the parsing
if( ! pj.is_valid() ) {
    // something went wrong
    std::cout << pj.get_error_message() << std::endl;
}

As needed, the json_parse and build_parsed_json functions copy the input data to a temporary buffer readable up to SIMDJSON_PADDING bytes beyond the end of the data.

Newline-Delimited JSON (ndjson) and JSON lines

The simdjson library also support multithreaded JSON streaming through a large file containing many smaller JSON documents in either ndjson or JSON lines format. We support files larger than 4GB.

API and detailed documentation found here.

Here is a simple example, using single header simdjson:

#include "simdjson.h"
#include "simdjson.cpp"

int parse_file(const char *filename) {
    simdjson::padded_string p = simdjson::get_corpus(filename);
    simdjson::ParsedJson pj;
    simdjson::JsonStream js{p};
    int parse_res = simdjson::SUCCESS_AND_HAS_MORE;
    
    while (parse_res == simdjson::SUCCESS_AND_HAS_MORE) {
            parse_res = js.json_parse(pj);

            //Do something with pj...
        }
}

Usage: easy single-header version

See the "singleheader" repository for a single header version. See the included file "amalgamation_demo.cpp" for usage. This requires no specific build system: just copy the files in your project in your include path. You can then include them quite simply:

#include <iostream>
#include "simdjson.h"
#include "simdjson.cpp"
using namespace simdjson;
int main(int argc, char *argv[]) {
  const char * filename = argv[1];
  padded_string p = get_corpus(filename);
  ParsedJson pj = build_parsed_json(p); // do the parsing
  if( ! pj.is_valid() ) {
    std::cout << "not valid" << std::endl;
    std::cout << pj.get_error_message() << std::endl;
  } else {
    std::cout << "valid" << std::endl;
  }
  return EXIT_SUCCESS;
}

Note: In some settings, it might be desirable to precompile simdjson.cpp instead of including it.

Usage (old-school Makefile on platforms like Linux or macOS)

Requirements: recent clang or gcc, and make. We recommend at least GNU GCC/G++ 7 or LLVM clang 6. A 64-bit system like Linux or macOS is expected.

To test:

make
make test

To run benchmarks:

make parse
./parse jsonexamples/twitter.json

Under Linux, the parse command gives a detailed analysis of the performance counters.

To run comparative benchmarks (with other parsers):

make benchmark

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

Requirements: We require a recent version of cmake. On macOS, the easiest way to install cmake might be to use brew and then type

brew install cmake

There is an equivalent brew on Linux which works the same way as well.

You need a recent compiler like clang or gcc. We recommend at least GNU GCC/G++ 7 or LLVM clang 6. For example, you can install a recent compiler with brew:

brew install gcc@8

Optional: 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.

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

mkdir build
cd build
cmake ..
make
make test

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

You can build a static library:

mkdir buildstatic
cd buildstatic
cmake -DSIMDJSON_BUILD_STATIC=ON ..
make
make test

In some cases, you may want to specify your compiler, especially if the default compiler on your system is too old. You may proceed as follows:

brew install gcc@8
mkdir build
cd build
export CXX=g++-8 CC=gcc-8
cmake ..
make
make test

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

We assume you have a common 64-bit Windows PC with at least Visual Studio 2017 and an x64 processor with AVX2 support (2013 Intel Haswell or later) or SSE 4.2 + CLMUL (2010 Westmere or later).

  • 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 VisualStudio.
  • Using a shell, go to this newly created directory.
  • Type cmake -DCMAKE_GENERATOR_PLATFORM=x64 .. in the shell while in the VisualStudio repository. (Alternatively, if you want to build a DLL, you may use the command line cmake -DCMAKE_GENERATOR_PLATFORM=x64 -DSIMDJSON_BUILD_STATIC=OFF ...)
  • 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.

Usage (Using vcpkg on 64-bit Windows, Linux and macOS)

vcpkg users on Windows, Linux and macOS can download and install simdjson with one single command from their favorite shell.

On 64-bit Linux and macOS:

$ ./vcpkg install simdjson

will build and install simdjson as a static library.

On Windows (64-bit):

.\vcpkg.exe install simdjson:x64-windows

will build and install simdjson as a shared library.

.\vcpkg.exe install simdjson:x64-windows-static  

will build and install simdjson as a static library.

These commands will also print out instructions on how to use the library from MSBuild or CMake-based projects.

If you find the version of simdjson shipped with vcpkg is out-of-date, feel free to report it to vcpkg community either by submiting an issue or by creating a PR.

Tools

  • 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.

Scope

We provide a fast parser, that fully validates an input according to various specifications. The parser builds a useful immutable (read-only) DOM (document-object model) which can be later accessed.

To simplify the engineering, we make some assumptions.

  • We support UTF-8 (and thus ASCII), nothing else (no Latin, no UTF-16). We do not believe this is a genuine limitation, because we do not think there is any serious application that needs to process JSON data without an ASCII or UTF-8 encoding. If the UTF-8 contains a leading BOM, it should be omitted: the user is responsible for detecting and skipping the BOM; UTF-8 BOMs are discouraged.
  • All strings in the JSON document may have up to 4294967295 bytes in UTF-8 (4GB). To enforce this constraint, we refuse to parse a document that contains more than 4294967295 bytes (4GB). This should accommodate most JSON documents.
  • As allowed by the specification, we allow repeated keys within an object (other parsers like sajson do the same).
  • Performance is optimized for JSON documents spanning at least a tens kilobytes up to many megabytes: the performance issues with having to parse many tiny JSON documents or one truly enormous JSON document are different.

We do not aim to provide a general-purpose JSON library. A library like RapidJSON offers much more than just parsing, it helps you generate JSON and offers various other convenient functions. We merely parse the document.

Features

  • The input string is unmodified. (Parsers like sajson and RapidJSON use the input string as a buffer.)
  • We parse integers and floating-point numbers as separate types which allows us to support large signed 64-bit integers in [-9223372036854775808,9223372036854775808), like a Java long or a C/C++ long long and large unsigned integers up to the value 18446744073709551615. Among the parsers that differentiate between integers and floating-point numbers, not all support 64-bit integers. (For example, sajson rejects JSON files with integers larger than or equal to 2147483648. RapidJSON will parse a file containing an overly long integer like 18446744073709551616 as a floating-point number.) When we cannot represent exactly an integer as a signed or unsigned 64-bit value, we reject the JSON document.
  • We support the full range of 64-bit floating-point numbers (binary64). The values range from std::numeric_limits<double>::lowest() to std::numeric_limits<double>::max(), so from -1.7976e308 all the way to 1.7975e308. Extreme values (less or equal to -1e308, greater or equal to 1e308) are rejected: we refuse to parse the input document.
  • We test for accurate float parsing with a bound on the unit of least precision (ULP) of one. Practically speaking, this implies 15 digits of accuracy or better.
  • We do full UTF-8 validation as part of the parsing. (Parsers like fastjson, gason and dropbox json11 do not do UTF-8 validation. The sajson parser does incomplete UTF-8 validation, accepting code point sequences like 0xb1 0x87.)
  • We fully validate the numbers. (Parsers like gason and ultranjson will accept [0e+] as valid JSON.)
  • We validate string content for unescaped characters. (Parsers like fastjson and ultrajson accept unescaped line breaks and tabs in strings.)
  • We fully validate the white-space characters outside of the strings. Parsers like RapidJSON will accept JSON documents with null characters outside of strings.

Architecture

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.

JSON Pointer

We can navigate the parsed JSON using JSON Pointers as per the RFC6901 standard.

You can build a tool (jsonpointer) to parse a JSON document and then issue an array of JSON Pointer queries:

make jsonpointer
 ./jsonpointer jsonexamples/small/demo.json /Image/Width /Image/Height /Image/IDs/2
 ./jsonpointer jsonexamples/twitter.json /statuses/0/id /statuses/1/id /statuses/2/id /statuses/3/id /statuses/4/id /statuses/5/id

In C++, given a ParsedJson, we can move to a node with the move_to method, passing a std::string representing the JSON Pointer query.

Navigating the parsed document

From a simdjson::ParsedJson instance, you can create an iterator (of type simdjson::ParsedJson::Iterator which is in fact simdjson::ParsedJson::BasicIterator<DEFAULT_MAX_DEPTH> ) via a constructor:

ParsedJson::Iterator pjh(pj); // pj is a ParsedJSON

You then have access to the following methods on the resulting simdjson::ParsedJson::Iterator instance:

  • bool is_ok() const: whether you have a valid iterator, will be false if your parent parsed ParsedJson is not a valid JSON.
  • size_t get_depth() const: returns the current depth (start at 1 with 0 reserved for the fictitious root node)
  • int8_t get_scope_type() const: a scope is a series of nodes at the same depth, typically it is either an object ({) or an array ([). The root node has type 'r'.
  • bool move_forward(): move forward in document order
  • uint8_t get_type() const: retrieve the character code of what we're looking at: [{"slutfn are the possibilities
  • int64_t get_integer() const: get the int64_t value at this node; valid only if get_type() is "l"
  • uint64_t get_unsigned_integer() const: get the value as uint64; valid only if get_type() is "u"
  • const char *get_string() const: get the string value at this node (NULL ended); valid only if get_type() is ", note that tabs, and line endings are escaped in the returned value, return value is valid UTF-8, it may contain NULL chars, get_string_length() determines the true string length.
  • uint32_t get_string_length() const: return the length of the string in bytes
  • double get_double() const: get the double value at this node; valid only if gettype() is "d"
  • bool is_object_or_array() const: self-explanatory
  • bool is_object() const: self-explanatory
  • bool is_array() const: self-explanatory
  • bool is_string() const: self-explanatory
  • bool is_integer() const: self-explanatory
  • bool is_unsigned_integer() const: Returns true if the current type of node is an unsigned integer. You can get its value with get_unsigned_integer(). Only a large value, which is out of range of a 64-bit signed integer, is represented internally as an unsigned node. On the other hand, a typical positive integer, such as 1, 42, or 1000000, is as a signed node. Be aware this function returns false for a signed node.
  • bool is_double() const: self-explanatory
  • bool is_number() const: self-explanatory
  • bool is_true() const: self-explanatory
  • bool is_false() const: self-explanatory
  • bool is_null() const: self-explanatory
  • bool is_number() const: self-explanatory
  • bool move_to_key(const char *key): when at {, go one level deep, looking for a given key, if successful, we are left pointing at the value, if not, we are still pointing at the object ({) (in case of repeated keys, this only finds the first one). We seek the key using C's strcmp so if your JSON strings contain NULL chars, this would trigger a false positive: if you expect that to be the case, take extra precautions. Furthermore, we do the comparison character-by-character without taking into account Unicode equivalence.
  • bool move_to_key_insensitive(const char *key): as above, but case insensitive lookup
  • bool move_to_key(const char *key, uint32_t length): as above except that the target can contain NULL characters
  • void move_to_value(): when at a key location within an object, this moves to the accompanying, value (located next to it). This is equivalent but much faster than calling next().
  • bool move_to_index(uint32_t index): when at [, go one level deep, and advance to the given index, if successful, we are left pointing at the value,i f not, we are still pointing at the array
  • bool move_to(const char *pointer, uint32_t length): Moves the iterator to the value correspoding to the json pointer. Always search from the root of the document. If successful, we are left pointing at the value, if not, we are still pointing the same value we were pointing before the call. The json pointer follows the rfc6901 standard's syntax: https://tools.ietf.org/html/rfc6901
  • bool move_to(const std::string &pointer) : same as above but with a std::string parameter
  • bool next(): Withing a given scope (series of nodes at the same depth within either an array or an object), we move forward. Thus, given [true, null, {"a":1}, [1,2]], we would visit true, null, { and [. At the object ({) or at the array ([), you can issue a "down" to visit their content. valid if we're not at the end of a scope (returns true).
  • bool prev(): Within a given scope (series of nodes at the same depth within either an array or an object), we move backward.
  • bool up(): moves back to either the containing array or object (type { or [) from within a contained scope.
  • bool down(): moves us to start of that deeper scope if it not empty. Thus, given [true, null, {"a":1}, [1,2]], if we are at the { node, we would move to the "a" node.
  • void to_start_scope(): move us to the start of our current scope, a scope is a series of nodes at the same level
  • void rewind(): repeatedly calls up until we are at the root of the document
  • bool print(std::ostream &os, bool escape_strings = true) const: print the node we are currently pointing at

Here is a code sample to dump back the parsed JSON to a string:

    ParsedJson::Iterator pjh(pj);
    if (!pjh.is_ok()) {
      std::cerr << " Could not iterate parsed result. " << std::endl;
      return EXIT_FAILURE;
    }
    compute_dump(pj);
    //
    // where compute_dump is :

void compute_dump(ParsedJson::Iterator &pjh) {
  if (pjh.is_object()) {
    std::cout << "{";
    if (pjh.down()) {
      pjh.print(std::cout); // must be a string
      std::cout << ":";
      pjh.next();
      compute_dump(pjh); // let us recurse
      while (pjh.next()) {
        std::cout << ",";
        pjh.print(std::cout);
        std::cout << ":";
        pjh.next();
        compute_dump(pjh); // let us recurse
      }
      pjh.up();
    }
    std::cout << "}";
  } else if (pjh.is_array()) {
    std::cout << "[";
    if (pjh.down()) {
      compute_dump(pjh); // let us recurse
      while (pjh.next()) {
        std::cout << ",";
        compute_dump(pjh); // let us recurse
      }
      pjh.up();
    }
    std::cout << "]";
  } else {
    pjh.print(std::cout); // just print the lone value
  }
}

The following function will find all user.id integers:

void simdjson_scan(std::vector<int64_t> &answer, ParsedJson::Iterator &i) {
   while(i.move_forward()) {
     if(i.get_scope_type() == '{') {
       bool found_user = (i.get_string_length() == 4) && (memcmp(i.get_string(), "user", 4) == 0);
       i.move_to_value();
       if(found_user) {
          if(i.is_object() && i.move_to_key("id",2)) {
            if (i.is_integer()) {
              answer.push_back(i.get_integer());
            }
            i.up();
          }
       }
     }
   }
}

In-depth comparisons

If you want to see how a wide range of parsers validate a given JSON file:

make allparserscheckfile
./allparserscheckfile myfile.json

For performance comparisons:

make parsingcompetition
./parsingcompetition myfile.json

For broader comparisons:

make allparsingcompetition
./allparsingcompetition myfile.json

Both the parsingcompetition and allparsingcompetition tools take a -t flag which produces a table-oriented output that can be conventiently parsed by other tools.

Docker

One can run tests and benchmarks using docker. It especially makes sense under Linux. A privileged access may be needed to get performance counters.

git clone https://github.com/lemire/simdjson.git
cd simdjson
docker build -t simdjson .
docker run --privileged -t simdjson

Other programming languages

We distinguish between "bindings" (which just wrap the C++ code) and a port to another programming language (which reimplements everything).

Various References

Inspiring links:

Validating UTF-8 takes no more than 0.7 cycles per byte:

Remarks on JSON parsing

  • The JSON spec defines what a JSON parser is:

    A JSON parser transforms a JSON text into another representation. A JSON parser MUST accept all texts that conform to the JSON grammar. A JSON parser MAY accept non-JSON forms or extensions. An implementation may set limits on the size of texts that it accepts. An implementation may set limits on the maximum depth of nesting. An implementation may set limits on the range and precision of numbers. An implementation may set limits on the length and character contents of strings.

  • JSON is not JavaScript:

    All JSON is Javascript but NOT all Javascript is JSON. So {property:1} is invalid because property does not have double quotes around it. {'property':1} is also invalid, because it's single quoted while the only thing that can placate the JSON specification is double quoting. JSON is even fussy enough that {"property":.1} is invalid too, because you should have of course written {"property":0.1}. Also, don't even think about having comments or semicolons, you guessed it: they're invalid. (credit:https://github.com/elzr/vim-json)

  • The structural characters are:

    begin-array     =  [ left square bracket
    begin-object    =  { left curly bracket
    end-array       =  ] right square bracket
    end-object      =  } right curly bracket
    name-separator  = : colon
    value-separator = , comma
    

Pseudo-structural elements

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.

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 }

Academic References

  • T.Mühlbauer, W.Rödiger, R.Seilbeck, A.Reiser, A.Kemper, and T.Neumann. Instant loading for main memory databases. PVLDB, 6(14):17021713, 2013. (SIMD-based CSV parsing)
  • Mytkowicz, Todd, Madanlal Musuvathi, and Wolfram Schulte. "Data-parallel finite-state machines." ACM SIGARCH Computer Architecture News. Vol. 42. No. 1. ACM, 2014.
  • Lu, Yifan, et al. "Tree structured data processing on GPUs." Cloud Computing, Data Science & Engineering-Confluence, 2017 7th International Conference on. IEEE, 2017.
  • Sidhu, Reetinder. "High throughput, tree automata based XML processing using FPGAs." Field-Programmable Technology (FPT), 2013 International Conference on. IEEE, 2013.
  • Dai, Zefu, Nick Ni, and Jianwen Zhu. "A 1 cycle-per-byte XML parsing accelerator." Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays. ACM, 2010.
  • Lin, Dan, et al. "Parabix: Boosting the efficiency of text processing on commodity processors." High Performance Computer Architecture (HPCA), 2012 IEEE 18th International Symposium on. IEEE, 2012. http://parabix.costar.sfu.ca/export/1783/docs/HPCA2012/final_ieee/final.pdf
  • Deshmukh, V. M., and G. R. Bamnote. "An empirical evaluation of optimization parameters in XML parsing for performance enhancement." Computer, Communication and Control (IC4), 2015 International Conference on. IEEE, 2015.
  • Moussalli, Roger, et al. "Efficient XML Path Filtering Using GPUs." ADMS@ VLDB. 2011.
  • Jianliang, Ma, et al. "Parallel speculative dom-based XML parser." High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), 2012 IEEE 14th International Conference on. IEEE, 2012.
  • Li, Y., Katsipoulakis, N.R., Chandramouli, B., Goldstein, J. and Kossmann, D., 2017. Mison: a fast JSON parser for data analytics. Proceedings of the VLDB Endowment, 10(10), pp.1118-1129. http://www.vldb.org/pvldb/vol10/p1118-li.pdf
  • Cameron, Robert D., et al. "Parallel scanning with bitstream addition: An xml case study." European Conference on Parallel Processing. Springer, Berlin, Heidelberg, 2011.
  • Cameron, Robert D., Kenneth S. Herdy, and Dan Lin. "High performance XML parsing using parallel bit stream technology." Proceedings of the 2008 conference of the center for advanced studies on collaborative research: meeting of minds. ACM, 2008.
  • Shah, Bhavik, et al. "A data parallel algorithm for XML DOM parsing." International XML Database Symposium. Springer, Berlin, Heidelberg, 2009.
  • Cameron, Robert D., and Dan Lin. "Architectural support for SWAR text processing with parallel bit streams: the inductive doubling principle." ACM Sigplan Notices. Vol. 44. No. 3. ACM, 2009.
  • Amagasa, Toshiyuki, Mana Seino, and Hiroyuki Kitagawa. "Energy-Efficient XML Stream Processing through Element-Skipping Parsing." Database and Expert Systems Applications (DEXA), 2013 24th International Workshop on. IEEE, 2013.
  • Medforth, Nigel Woodland. "icXML: Accelerating Xerces-C 3.1. 1 using the Parabix Framework." (2013).
  • Zhang, Qiang Scott. Embedding Parallel Bit Stream Technology Into Expat. Diss. Simon Fraser University, 2010.
  • Cameron, Robert D., et al. "Fast Regular Expression Matching with Bit-parallel Data Streams."
  • Lin, Dan. Bits filter: a high-performance multiple string pattern matching algorithm for malware detection. Diss. School of Computing Science-Simon Fraser University, 2010.
  • Yang, Shiyang. Validation of XML Document Based on Parallel Bit Stream Technology. Diss. Applied Sciences: School of Computing Science, 2013.
  • N. Nakasato, "Implementation of a parallel tree method on a GPU", Journal of Computational Science, vol. 3, no. 3, pp. 132-141, 2012.

Funding

The work is supported by the Natural Sciences and Engineering Research Council of Canada under grant number RGPIN-2017-03910.