Efficiently reading a very large text file in C++

I’d redesign this to act streaming, instead of on a block.

A simpler approach would be:

std::ifstream ifs("input.txt");
std::vector<uint64_t> parsed(std::istream_iterator<uint64_t>(ifs), {});

If you know roughly how many values are expected, using std::vector::reserve up front could speed it up further.

Alternatively you can use a memory mapped file and iterate over the character sequence.

Update I modified the above program to parse uint32_ts into a vector.

When using a sample input file of 4.5GiB[1] the program runs in 9 seconds[2]:

sehe@desktop:/tmp$ make -B && sudo chrt -f 99 /usr/bin/time -f "%E elapsed, %c context switches" ./test smaller.txt
g++ -std=c++0x -Wall -pedantic -g -O2 -march=native test.cpp -o test -lboost_system -lboost_iostreams -ltcmalloc
parse success
trailing unparsed: '
data.size():   402653184
0:08.96 elapsed, 6 context switches

Of course it allocates at least 402653184 * 4 * byte = 1.5 gibibytes. So when
you read a 45 GB file, you will need an estimated 15GiB of RAM to just store
the vector (assuming no fragmentation on reallocation): The 45GiB parse
completes in 10min 45s

make && sudo chrt -f 99 /usr/bin/time -f "%E elapsed, %c context switches" ./test 45gib_uint32s.txt 
make: Nothing to be done for `all'.
tcmalloc: large alloc 17570324480 bytes == 0x2cb6000 @  0x7ffe6b81dd9c 0x7ffe6b83dae9 0x401320 0x7ffe6af4cec5 0x40176f (nil)
Parse success
Trailing unparsed: 1 characters
Data.size():   4026531840
Time taken by parsing: 644.64s
10:45.96 elapsed, 42 context switches

By comparison, just running wc -l 45gib_uint32s.txt took ~12 minutes (without realtime priority scheduling though). wc is blazingly fast

Full Code Used For Benchmark

#include <boost/spirit/include/qi.hpp>
#include <boost/iostreams/device/mapped_file.hpp>
#include <chrono>

namespace qi = boost::spirit::qi;

typedef std::vector<uint32_t> data_t;

using hrclock = std::chrono::high_resolution_clock;

int main(int argc, char** argv) {
    if (argc<2) return 255;
    data_t data;
    data.reserve(4392580288);   // for the  45 GiB file benchmark
    // data.reserve(402653284); // for the 4.5 GiB file benchmark

    boost::iostreams::mapped_file mmap(argv[1], boost::iostreams::mapped_file::readonly);
    auto f = mmap.const_data();
    auto l = f + mmap.size();

    using namespace qi;

    auto start_parse = hrclock::now();
    bool ok = phrase_parse(f,l,int_parser<uint32_t, 10>() % eol, blank, data);
    auto stop_time = hrclock::now();

    if (ok)   
        std::cout << "Parse success\n";
        std::cerr << "Parse failed at #" << std::distance(mmap.const_data(), f) << " around '" << std::string(f,f+50) << "'\n";

    if (f!=l) 
        std::cerr << "Trailing unparsed: " << std::distance(f,l) << " characters\n";

    std::cout << "Data.size():   " << data.size() << "\n";
    std::cout << "Time taken by parsing: " << std::chrono::duration_cast<std::chrono::milliseconds>(stop_time-start_parse).count() / 1000.0 << "s\n";

[1] generated with od -t u4 /dev/urandom -A none -v -w4 | pv | dd bs=1M count=$((9*1024/2)) iflag=fullblock > smaller.txt

[2] obviously, this was with the file cached in the buffer cache on linux – the large file doesn’t have this benefit

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