I'm trying to look at the Freebase data dump which is stored on a server that I access through ssh. The trouble is I don't know how I can view it in a way that doesn't take forever, make things freeze or crash, I had been trying to view it with nano and it evokes the precisely the behaviour just described.
The operating system is Darwin.
How can I examine this data?
Basically you could use command more or less to scroll over the file. If you know which lines in the file you are interested in, like from line 3000 to 3999, you could show them with sed -n '3000,3999p' your_file_name.
New to this forum - looks great!
I have some Processing code that periodically reads data wirelessly from remote devices and writes that data as bytes to a file, e.g. data.dat. I want to write an Objective C program on my Mac Mini using Xcode to read this file, parse the data, and act on the data if data values indicate a problem. My question is: can my two different programs access the same file asynchronously without a problem? If this is a problem can you suggest a technique that will allow these operations?
Thanks,
Kevin H.
Multiple processes can read from the same file at a time without any problem. A process can also read from a file while another writes without problem, although you'll have to take care to ensure that you read in any new data that was written. Multiple processes should not write to the same file at at the same time, though. The OS will let you do it, but the ordering of data will be undefined, and you'll like overwrite data—in general, you're gonna have a bad time if you do that. So you should take care to ensure that only one process writes to a file at a time.
The simplest way to protect a file so that only one process can write to it at a time is with the C function flock(), although that function is admittedly a bit rudimentary and may or may not suit your use case.
Say I have app TestApp.exe
While TestApp.exe is running I want a separate program to be able to read the executable code that is resident in memory. I'd like to ignore stack and heap and anything else that is tangential.
Put another way, I guess I'm asking how to determine where the memory-side equivalent of the .exe binary data on disk resides. I realize it's not a 1:1 stuffing into memory.
Edit: I think what I'm asking for is shown as Image in the following screenshot of vmmap.exe
Edit: I am able to get from memory all memory that is tagged with any protect flag of Execute* (PAGE_EXECUTE, etc) using VirtualQueryEx and ReadProcessMemory. There are a couple issues with that. First, I'm grabbing about 2 megabytes of data for notepad.exe which is a 189 kilobyte file on disk. Everything I'm grabbing has a protect flag of PAGE_EXECUTE. Second, If I run it on a different Win7 64bit machine I get the same data, only split in half and in a different order. I could use some expert guidance. :)
Edit: Also, not sure why I'm at -1 for this question. If I need to clear anything up please let me know.
Inject a DLL to the target process and call GetModuleHandle with the name of the executable. That will point to its PE header that has been loaded in the memory. Once you have this information, you can parse the PE header manually and find where .text section is located relative to the base address of the image in the memory.
no need to inject a dll
use native api hooking apis
I learned a ton doing this project. I ended up parsing the PE header and using that information to route me all over. In the end I accomplished what I set out to and I am more knowledgeable as a result.
What happens, at low-level (stepwise) when a program is executed in windows. In other words the processes that take place from clicking a file to actually reaching execution.
Are you aware of any resources that might cover this topic in-depth?
I'd suggest reading this two part MSDN article on the Win32 Portable Executable file format. It describes all the different parts of the file which gives you a lot of information about what has to happen in order to load and run the executable file.
The Wikipedia page on the PE format also contains useful info.
Previously, I asked the question.
The problem is the demands of our file structure are very high.
For instance, we're trying to create a container with up to 4500 files and 500mb data.
The file structure of this container consists of
SQLite DB (under 1mb)
Text based xml-like file
Images inside a dynamic folder structure that make up the rest of the 4,500ish files
After the initial creation the images files are read only with the exception of deletion.
The small db is used regularly when the container is accessed.
Tar, Zip and the likes are all too slow (even with 0 compression). Slow is subjective I know, but to untar a container of this size is over 20 seconds.
Any thoughts?
As you seem to be doing arbitrary file system operations on your container (say, creation, deletion of new files in the container, overwriting existing files, appending), I think you should go for some kind of file system. Allocate a large file, then create a file system structure in it.
There are several options for the file system available: for both Berkeley UFS and Linux ext2/ext3, there are user-mode libraries available. It might also be possible that you find a FAT implementation somewhere. Make sure you understand the structure of the file system, and pick one that allows for extending - I know that ext2 is fairly easy to extend (by another block group), and FAT is difficult to extend (need to append to the FAT).
Alternatively, you can put a virtual disk format yet below the file system, allowing arbitrary remapping of blocks. Then "free" blocks of the file system don't need to appear on disk, and you can allocate the virtual disk much larger than the real container file will be.
Three things.
1) What Timothy Walters said is right on, I'll go in to more detail.
2) 4500 files and 500Mb of data is simply a lot of data and disk writes. If you're operating on the entire dataset, it's going to be slow. Just I/O truth.
3) As others have mentioned, there's no detail on the use case.
If we assume a read only, random access scenario, then what Timothy says is pretty much dead on, and implementation is straightforward.
In a nutshell, here is what you do.
You concatenate all of the files in to a single blob. While you are concatenating them, you track their filename, the file length, and the offset that the file starts within the blob. You write that information out in to a block of data, sorted by name. We'll call this the Table of Contents, or TOC block.
Next, then, you concatenate the two files together. In the simple case, you have the TOC block first, then the data block.
When you wish to get data from this format, search the TOC for the file name, grab the offset from the begining of the data block, add in the TOC block size, and read FILE_LENGTH bytes of data. Simple.
If you want to be clever, you can put the TOC at the END of the blob file. Then, append at the very end, the offset to the start of the TOC. Then you lseek to the end of the file, back up 4 or 8 bytes (depending on your number size), take THAT value and lseek even farther back to the start of your TOC. Then you're back to square one. You do this so you don't have to rebuild the archive twice at the beginning.
If you lay out your TOC in blocks (say 1K byte in size), then you can easily perform a binary search on the TOC. Simply fill each block with the File information entries, and when you run out of room, write a marker, pad with zeroes and advance to the next block. To do the binary search, you already know the size of the TOC, start in the middle, read the first file name, and go from there. Soon, you'll find the block, and then you read in the block and scan it for the file. This makes it efficient for reading without having the entire TOC in RAM. The other benefit is that the blocking requires less disk activity than a chained scheme like TAR (where you have to crawl the archive to find something).
I suggest you pad the files to block sizes as well, disks like work with regular sized blocks of data, this isn't difficult either.
Updating this without rebuilding the entire thing is difficult. If you want an updatable container system, then you may as well look in to some of the simpler file system designs, because that's what you're really looking for in that case.
As for portability, I suggest you store your binary numbers in network order, as most standard libraries have routines to handle those details for you.
Working on the assumption that you're only going to need read-only access to the files why not just merge them all together and have a second "index" file (or an index in the header) that tells you the file name, start position and length. All you need to do is seek to the start point and read the correct number of bytes. The method will vary depending on your language but it's pretty straight forward in most of them.
The hardest part then becomes creating your data file + index, and even that is pretty basic!
An ISO disk image might do the trick. It should be able to hold that many files easily, and is supported by many pieces of software on all the major operating systems.
First, thank-you for expanding your question, it helps a lot in providing better answers.
Given that you're going to need a SQLite database anyway, have you looked at the performance of putting it all into the database? My experience is based around SQL Server 2000/2005/2008 so I'm not positive of the capabilities of SQLite but I'm sure it's going to be a pretty fast option for looking up records and getting the data, while still allowing for delete and/or update options.
Usually I would not recommend to put files inside the database, but given that the total size of all images is around 500MB for 4500 images you're looking at a little over 100K per image right? If you're using a dynamic path to store the images then in a slightly more normalized database you could have a "ImagePaths" table that maps each path to an ID, then you can look for images with that PathID and load the data from the BLOB column as needed.
The XML file(s) could also be in the SQLite database, which gives you a single 'data file' for your app that can move between Windows and OSX without issue. You can simply rely on your SQLite engine to provide the performance and compatability you need.
How you optimize it depends on your usage, for example if you're frequently needing to get all images at a certain path then having a PathID (as an integer for performance) would be fast, but if you're showing all images that start with "A" and simply show the path as a property then an index on the ImageName column would be of more use.
I am a little concerned though that this sounds like premature optimization, as you really need to find a solution that works 'fast enough', abstract the mechanics of it so your application (or both apps if you have both Mac and PC versions) use a simple repository or similar and then you can change the storage/retrieval method at will without any implication to your application.
Check Solid File System - it seems to be what you need.