I have a series of large text files (10s - 100s of thousands of lines) that I want to parse line-by-line. The idea is to check if the line has a specific word/character/phrase and to, for now, record to a secondary file if it does.
The code I've used so far is:
ifstream infile1("c:/test/test.txt");
while (getline(infile1, line)) {
if (line.empty()) continue;
if (line.find("mystring") != std::string::npos) {
outfile1 << line << '\n';
}
}
The end goal is to be writing those lines to a database. My thinking was to write them to the file first and then to import the file.
The problem I'm facing is the time taken to complete the task. I'm looking to minimize the time as far as possible, so any suggestions as to time savings on the read/write scenario above would be most welcome. Apologies if anything is obvious, I've only just started moving into C++.
Thanks
EDIT
I should say that I'm using VS2015
EDIT 2
So this was my own dumb fault, when switching to Release and changing the architecture type I had noticeable speed increases. Thanks to everyone for pointing me in that direction. I'm also looking at the mmap stuff and that's proving useful too. Thanks guys!
When you use ifstream to read and process to/from really big files, you have to increase the default buffer size that is used (normally 512 bytes).
The best buffer size depends on your needs, but as a hint you can use the partition block size of the file(s) your reading/writing. To know that information you can use a lot of tools or even code.
Example in Windows:
fsutil fsinfo ntfsinfo c:
Now, you have to create a new buffer to ifstream like this:
size_t newBufferSize = 4 * 1024; // 4K
char * newBuffer = new char[newBufferSize];
ifstream infile1;
infile1.rdbuf()->pubsetbuf(newBuffer, newBufferSize);
infile1.open("c:/test/test.txt");
while (getline(infile1, line)) {
/* ... */
}
delete newBuffer;
Do the same with the output stream and don't forget set new buffer before open file or it may not work.
You can play with values to find the very best size for you.
You'll note the difference.
C-style I/O functions are much faster than fstream.
You may use fgets/fputs to read/write each text line.
I'm working on some project and I'm wondering which way is the most efficient to read a huge amount of data off a file(I'm speaking of file of 100 lines up to 3 billions lines approx., can be more thought). Once read, data will be stored in a structured data set (vector<entry> where "entry" defines a structured line).
A structured line of this file may look like :
string int int int string string
which also ends with the appropriate platform EOL and is TAB delimited
What I wish to accomplish is :
Read file into memory (string) or vector<char>
Read raw data from my buffer and format it into my data set.
I need to consider memory footprint and have a fast parsing rate.
I'm already avoiding usage of stringstream as they seems too slow.
I'm also avoiding multiple I/O call to my file by using :
// open the stream
std::ifstream is(filename);
// determine the file length
is.seekg(0, ios_base::end);
std::size_t size = is.tellg();
is.seekg(0, std::ios_base::beg);
// "out" can be a std::string or vector<char>
out.reserve(size / sizeof (char));
out.resize(size / sizeof (char), 0);
// load the data
is.read((char *) &out[0], size);
// close the file
is.close();
I've thought of taking this huge std::string and then looping line by line, I would extract line information (string and integer parts) into my data set row. Is there a better way of doing this?
EDIT : This application may run on a 32bit, 64bit computer, or on a super computer for bigger files.
Any suggestions are very welcome.
Thank you
Some random thoughts:
Use vector::resize() at the beginning (you did that)
Read large blocks of file data at a time, at least 4k, better still 256k. Read them into a memory buffer, parse that buffer into your vector.
Don't read the whole file at once, this might needlessly lead to swapping.
sizeof(char) is always 1 :)
while i cannot speak for supercomputers with 3 gig lines you will go nowhere in memory on a desktop machine.
i think you should first try to figure out all operations on that data. you should try to design all algorithms to operate sequentially. if you need random access you will do swapping all the time. this algorithm design will have a big impact on your data model.
so do not start with reading all data, just because that is an easy part, but design the whole system with a clear view an what data is in memory during the whole processing.
update
when you do all processing in a single run on the stream and separate the data processing in stages (read - preprocess - ... - write) you can utilize multithreading effectivly.
finally
whatever you want to do in a loop over the data, try to keep the number of loops a minimum. averaging for sure you can do in the read loop.
immediately make up a test file the size you expect to be the worst case in size and time two different approaches
.
time
loop
read line from disk
time
loop
process line (counting words per line)
time
loop
write data (word count) from line to disk
time
versus.
time
loop
read line from disk
process line (counting words per line)
write data (word count) from line to disk
time
if you have the algorithms already use yours. otherwise make up one (like counting words per line). if the write stage does not apply to your problem skip it. this test does take you less than an hour to write but can save you a lot.
I have some .gz compressed files which is around 5-7gig uncompressed.
These are flatfiles.
I've written a program that takes a uncompressed file, and reads it line per line, which works perfectly.
Now I want to be able to open the compressed files inmemory and run my little program.
I've looked into zlib but I can't find a good solution.
Loading the entire file is impossible using gzread(gzFile,void *,unsigned), because of the 32bit unsigned int limitation.
I've tried gzgets, but this almost doubles the execution time, vs reading in using gzread.(I tested on a 2gig sample.)
I've also looked into "buffering", such as splitting the gzread process into multiple 2gig chunks, find the last newline using strcchr, and then setting the gzseek.
But gzseek will emulate a total file uncompression. which is very slow.
I fail to see any sane solution to this problem.
I could always do some checking, whether or not a current line actually has a newline (should only occure in the last partially read line), and then read more data from the point in the program where this occurs.
But this could get very ugly.
Does anyhow have any suggestions?
thanks
edit:
I dont need to have the entire file at once,just need one line a time, but I got a fairly huge machine, so if that was the easiest I would have no problems.
For all those that suggest piping the stdin, I've experienced extreme slowdowns compared to opening the file. Here is a small code snippet I made some months ago, that illustrates it.
time ./a.out 59846/59846.txt
# 59846/59846.txt
18255221
real 0m4.321s
user 0m2.884s
sys 0m1.424s
time ./a.out <59846/59846.txt
18255221
real 1m56.544s
user 1m55.043s
sys 0m1.512s
And the source code
#include <iostream>
#include <fstream>
#define LENS 10000
int main(int argc, char **argv){
std::istream *pFile;
if(argc==2)//ifargument supplied
pFile = new std::ifstream(argv[1],std::ios::in);
else //if we want to use stdin
pFile = &std::cin;
char line[LENS];
if(argc==2) //if we are using a filename, print it.
printf("#\t%s\n",argv[1]);
if(!pFile){
printf("Do you have permission to open file?\n");
return 0;
}
int numRow=0;
while(!pFile->eof()) {
numRow++;
pFile->getline(line,LENS);
}
if(argc==2)
delete pFile;
printf("%d\n",numRow);
return 0;
}
thanks for your replies, I'm still waiting the golden apple
edit2:
using the cstyle FILE pointers instead of c++ streams is much much faster. So I think this is the way to go.
Thank for all your input
gzip -cd compressed.gz | yourprogram
just go ahead and read it line by line from stdin as it is uncompressed.
EDIT: Response to your remarks about performance. You're saying reading STDIN line by line is slow compared to reading an uncompressed file directly. The difference lies within terms of buffering. Normally pipe will yield to STDIN as soon as the output becomes available (no, or very small buffering there). You can do "buffered block reads" from STDIN and parse the read blocks yourself to gain performance.
You can achieve the same result with possibly better performance by using gzread() as well. (Read a big chunk, parse the chunk, read the next chunk, repeat)
gzread only reads chunks of the file, you loop on it as you would using a normal read() call.
Do you need to read the entire file into memory ?
If what you need is to read lines, you'd gzread() a sizable chunk(say 8192 bytes) into a buffer, loop through that buffer and find all '\n' characters and process those as individual lines. You'd have to save the last piece incase there is just part of a line, and prepend that to the data you read next time.
You could also read from stdin and invoke your app like
zcat bigfile.gz | ./yourprogram
in which case you can use fgets and similar on stdin. This is also beneficial in that you'd run decompression on one processor and processing the data on another processor :-)
I don't know if this will be an answer to your question, but I believe it's more than a comment:
Some months ago I discovered that the contents of Wikipedia can be downloaded in much the same way as the StackOverflow data dump. Both decompress to XML.
I came across a description of how the multi-gigabyte compressed dump file could be parsed. It was done by Perl scripts, actually, but the relevant part for you was that Bzip2 compression was used.
Bzip2 is a block compression scheme, and the compressed file could be split into manageable pieces, and each part uncompressed individually.
Unfortunately, I don't have a link to share with you, and I can't suggest how you would search for it, except to say that it was described on a Wikipedia 'data dump' or 'blog' page.
EDIT: Actually, I do have a link
So i have a gui, designed using QT, c++. I have large amount of data in a text file that I would like to read in this fashion:
load first 50 lines, when the user scrolls down load next 50 lines and so one. When the user scrolls up load previous 50 lines.
Thank you.
The easiest solution would be to load the file into memory and manipulate it from there:
std::vector<std::string> lines;
std::string line;
while(std::getline(file,line)
{
lines.push_back(line);
}
If the file is way to large.
Then you need to build an index of the file that tells you exactly where each line starts.
std::vector<std::streampos> index;
index.push_back(file.tellg());
std::string line;
while(std::getline(file,line)
{
index.push_back(file.tellg());
}
file.setg(0);
file.clear(); // Resets the EOF flag.
Once you have your index. You can jump around the file and read any particular line.
int jumpTo = 50;
file.seekg(index[jumpTo]); // Jump to line 50.
//
// Read 50 lines. Do not read past the end
// This will set the EOF flag and future reads will fail.
for(int loop=0;loop < 50 && ((jumpTo + loop) < index.size());++loop)
{
std::string line;
std::getline(file,line);
}
Connect your app to the sliderMoved or sliderReleased signals of your QSlider and read the 50 lines you want to display. Or use the valueChange event.
I am guessing that this file may be huge (say in the Gigabyte range).
Assuming that portability is not an issue, you may want to use memory mapped io. On many unix systems you have the mmap command.
A nice tutorial can be found here.
If you need to do this for windows systems A windows equivalent example can be found here.
What mmap effectively does is maps the file into the current processes memory space. When one wants to read a bit of the file, the OS copies the bits of the file being looked at into RAM for the user to access. This is done using the same mechanism that allows the OS to move memory from idle processes onto disk until it is required again.
The only tricky bit will be dividing the file blocks into lines.
I need to read the number of lines in a file before doing some operations on that file. When I try to read the file and increment the line_count variable at each iteration until I reach EOF. It was not that fast in my case. I used both ifstream and fgets. They were both slow. Is there a hacky way to do this, which is also used by, for instance BSD, Linux kernel or berkeley db (may be by using bitwise operations).
The number of lines is in the millions in that file and it keeps getting larger, each line is about 40 or 50 characters. I'm using Linux.
Note:
I'm sure there will be people who might say use a DB idiot. But briefly in my case I can't use a db.
The only way to find the line count is to read the whole file and count the number of line-end characters. The fastest way to do this is probably to read the whole file into a large buffer with one read operation and then go through the buffer counting the '\n' characters.
As your current file size appears to be about 60Mb, this is not an attractive option. You can get some of the speed by not reading the whole file, but reading it in chunks, say of size 1Mb. You also say that a database is out of the question, but it really does look to be the best long-term solution.
Edit: I just ran a small benchmark on this and using the buffered approach (buffer size 1024K) seems to be a bit more than twice as fast as reading a line at a time with getline(). Here's the code - my tests were done with g++ using -O2 optimisation level:
#include <iostream>
#include <fstream>
#include <vector>
#include <ctime>
using namespace std;
unsigned int FileRead( istream & is, vector <char> & buff ) {
is.read( &buff[0], buff.size() );
return is.gcount();
}
unsigned int CountLines( const vector <char> & buff, int sz ) {
int newlines = 0;
const char * p = &buff[0];
for ( int i = 0; i < sz; i++ ) {
if ( p[i] == '\n' ) {
newlines++;
}
}
return newlines;
}
int main( int argc, char * argv[] ) {
time_t now = time(0);
if ( argc == 1 ) {
cout << "lines\n";
ifstream ifs( "lines.dat" );
int n = 0;
string s;
while( getline( ifs, s ) ) {
n++;
}
cout << n << endl;
}
else {
cout << "buffer\n";
const int SZ = 1024 * 1024;
std::vector <char> buff( SZ );
ifstream ifs( "lines.dat" );
int n = 0;
while( int cc = FileRead( ifs, buff ) ) {
n += CountLines( buff, cc );
}
cout << n << endl;
}
cout << time(0) - now << endl;
}
Don't use C++ stl strings and getline ( or C's fgets), just C style raw pointers and either block read in page-size chunks or mmap the file.
Then scan the block at the native word size of your system ( ie either uint32_t or uint64_t) using one of the magic algorithms 'SIMD Within A Register (SWAR) Operations' for testing the bytes within the word. An example is here; the loop with the 0x0a0a0a0a0a0a0a0aLL in it scans for line breaks. ( that code gets to around 5 cycles per input byte matching a regex on each line of a file )
If the file is only a few tens or a hundred or so megabytes, and it keeps growing (ie something keeps writing to it), then there's a good likelihood that linux has it cached in memory, so it won't be disk IO limited, but memory bandwidth limited.
If the file is only ever being appended to, you could also remember the number of lines
and previous length, and start from there.
It has been pointed out that you could use mmap with C++ stl algorithms, and create a functor to pass to std::foreach. I suggested that you shouldn't do it not because you can't do it that way, but there is no gain in writing the extra code to do so. Or you can use boost's mmapped iterator, which handles it all for you; but for the problem the code I linked to was written for this was much, much slower, and the question was about speed not style.
You wrote that it keeps getting larger.
This sounds like it is a log file or something similar where new lines are appended but existing lines are not changed. If this is the case you could try an incremental approach:
Parse to the end of file.
Remember the line count and the offset of EOF.
When the file grows fseek to the offset, parse to EOF and update the line count and the offset.
There's a difference between counting lines and counting line separators. Some common gotchas to watch out for if getting an exact line count is important:
What's the file encoding? The byte-by-byte solutions will work for ASCII and UTF-8, but watch out if you have UTF-16 or some multibyte encoding that doesn't guarantee that a byte with the value of a line feed necessarily encodes a line feed.
Many text files don't have a line separator at the end of the last line. So if your file says "Hello, World!", you could end up with a count of 0 instead of 1. Rather than just counting the line separators, you'll need a simple state machine to keep track.
Some very obscure files use Unicode U+2028 LINE SEPARATOR (or even U+2029 PARAGRAPH SEPARATOR) as line separators instead of the more common carriage return and/or line feed. You might also want to watch out for U+0085 NEXT LINE (NEL).
You'll have to consider whether you want to count some other control characters as line breakers. For example, should a U+000C FORM FEED or U+000B LINE TABULATION (a.k.a. vertical tab) be considered going to a new line?
Text files from older versions of Mac OS (before OS X) use carriage returns (U+000D) rather than line feeds (U+000A) to separate lines. If you're reading the raw bytes into a buffer (e.g., with your stream in binary mode) and scanning them, you'll come up with a count of 0 on these files. You can't count both carriage returns and line feeds, because PC files generally end a line with both. Again, you'll need a simple state machine. (Alternatively, you can read the file in text mode rather than binary mode. The text interfaces will normalize line separators to '\n' for files that conform to the convention used on your platform. If you're reading files from other platforms, you'll be back to binary mode with a state machine.)
If you ever have a super long line in the file, the getline() approach can throw an exception causing your simple line counter to fail on a small number of files. (This is particularly true if you're reading an old Mac file on a non-Mac platform, causing getline() to see the entire file as one gigantic line.) By reading chunks into a fixed-size buffer and using a state machine, you can make it bullet proof.
The code in the accepted answer suffers from most of these traps. Make it right before you make it fast.
Remember that all fstreams are buffered. So they in-effect do actually reads in chunks so you do not have to recreate this functionality. So all you need to do is scan the buffer. Don't use getline() though as this will force you to size a string. So I would just use the STL std::count and stream iterators.
#include <iostream>
#include <fstream>
#include <iterator>
#include <algorithm>
struct TestEOL
{
bool operator()(char c)
{
last = c;
return last == '\n';
}
char last;
};
int main()
{
std::fstream file("Plop.txt");
TestEOL test;
std::size_t count = std::count_if(std::istreambuf_iterator<char>(file),
std::istreambuf_iterator<char>(),
test);
if (test.last != '\n') // If the last character checked is not '\n'
{ // then the last line in the file has not been
++count; // counted. So increement the count so we count
} // the last line even if it is not '\n' terminated.
}
It isn't slow because of your algorithm , It is slow because IO operations are slow. I suppose you are using a simple O(n) algorithm that is simply going over the file sequentially. In that case , there is no faster algorithm that can optimize your program.
However , I said there is no faster algorithm , but there is a faster mechanism which called "Memory Mapped file " , There are some drawback for mapped files and it might not be appropiate for you case , So you'll have to read about it and figure out by yourself.
Memory mapped files won't let you implement an algorithm better then O(n) but it may will reduce IO access time.
You can only get a definitive answer by scanning the entire file looking for newline characters. There's no way around that.
However, there are a couple of possibilities which you may want to consider.
1/ If you're using a simplistic loop, reading one character at a time checking for newlines, don't. Even though the I/O may be buffered, function calls themselves are expensive, time-wise.
A better option is to read large chunks of the file (say 5M) into memory with a single I/O operation, then process that. You probably don't need to worry too much about special assembly instruction since the C runtime library will be optimized anyway - a simple strchr() should do it.
2/ If you're saying that the general line length is about 40-50 characters and you don't need an exact line count, just grab the file size and divide by 45 (or whatever average you deem to use).
3/ If this is something like a log file and you don't have to keep it in one file (may require rework on other parts of the system), consider splitting the file periodically.
For example, when it gets to 5M, move it (e.g., x.log) to a dated file name (e.g., x_20090101_1022.log) and work out how many lines there are at that point (storing it in x_20090101_1022.count, then start a new x.log log file. Characteristics of log files mean that this dated section that was created will never change so you will never have to recalculate the number of lines.
To process the log "file", you'd just cat x_*.log through some process pipe rather than cat x.log. To get the line count of the "file", do a wc -l on the current x.log (relatively fast) and add it to the sum of all the values in the x_*.count files.
The thing that takes time is loading 40+ MB into memory. The fastest way to do that is to either memorymap it, or load it in one go into a big buffer. Once you have it in memory, one way or another, a loop traversing the data looking for \n characters is almost instantaneous, no matter how it is implemented.
So really, the most important trick is to load the file into memory as fast as possible. And the fastest way to do that is to do it as a single operation.
Otherwise, plenty of tricks may exist to speed up the algorithm. If lines are only added, never modified or removed, and if you're reading the file repeatedly, you can cache the lines read previously, and the next time you have to read the file, only read the newly added lines.
Or perhaps you can maintain a separate index file showing the location of known '\n' characters, so those parts of the file can be skipped over.
Reading large amounts of data from the harddrive is slow. There's no way around that.
If your file only grows, then Ludwig Weinzierl is the best solution if you do not have control of the writers. Otherwise, you can make it even faster: increment the counter by one each time a line is written to the file. If multiple writers may try to write to the file simultaneously, then make sure to use a lock. Locking your existing file is enough. The counter can be 4 or 8 bytes written in binary in a file written under /run/<your-prog-name>/counter (which is RAM so dead fast).
Ludwig Algorithm
Initialize offset to 0
Read file from offset to EOF counting '\n' (as mentioned by others, make sure to use buffered I/O and count the '\n' inside that buffer)
Update offset with position at EOF
Save counter & offset to a file or in a variable if you only need it in your software
Repeat from "Read file ..." on a change
This is actually how various software processing log files function (i.e. fail2ban comes to mind).
The first time, it has to process a huge file. Afterward, it is very small and thus goes very fast.
Proactive Algorithm
When creating the files, reset counter to 0.
Then each time you receive a new line to add to the file:
Lock file
Write one line
Load counter
Add one to counter
Save counter
Unlock file
This is very close to what database systems do so a SELECT COUNT(*) FROM table on a table with millions of rows return instantly. Databases also do that per index. So if you add a WHERE clause which matches a specific index, you also get the total instantly. Same principle as above.
Personal note: I see a huge number of Internet software which are backward. A watchdog makes sense for various things in a software environment. However, in most cases, when something of importance happens, you should send a message at the time it happens. Not use a backward concept of checking logs to detect that something bad just happened.
For example, you detect that a user tried to access a website and entered the wrong password 5 times in a row. You want to send a instant message to the admin to make sure there wasn't a 6th time which was successful and the hacker can now see all your user's data... If you use logs, the "instant message" is going to be late by seconds if not minutes.
Don't do processing backward.