Bittorrent Is Hard - 1
Having worked on a bittorrent client in Haskell recently, I wanted to write about a few tricky aspects of the implementation that I encountered: managing the concurrent piece downloads, and saving them to files.
About these posts
The protocol for Bittorrent is well specified, although it takes a few read-throughs to get the hang of it. The first time I read through the protocol I didn’t understand much. But as I started implementing different parts of the protocol, those parts of the document started making more and more sense.
That being said, there are still many parts of the protocol where the specification might be clear, but how to implement that specification is left as an exercise to the reader. One of the sections that’s most guilty of this is the section related to how peer’s operate. There are many subtle rules about what peers should do in certain situations; the details of what variables to keep track of and how to make sure all these conditions are satisfied is a big leap from this description though.
In these series of posts, I want to try and explain the details that go into some of the algorithms necessary to implement Bittorrent.
This post covers how to save the pieces that make up the data in a torrent to disk, and how to recompose those pieces back together.
Side Note: What is Bittorrent?
If you’re already familiar with torrents or Bittorrent, then this section can be safely ignored.
Let me briefly explain these concepts.
Fundamentally, Bittorrent is a protocol that defines a way for multiple computers, which we refer to as “peers”, to download a file from eachother. Instead of each peer downloading the file from a central server, they instead download different parts from eachother, and upload the parts they have to the other peers that want those parts.
A torrent refers to this group of peers sharing a file.
Torrents and Pieces
A torrent can contain either a single file, or multiple files. When a torrent contains multiple files,
it can optionally contain a root directory for those files. For example,
contain a single
blockbuster.mp4 file, or perhaps
blockbuster.mp4, blockbuster.subtitles in a
I mentioned previously that peers trade “parts” of a file. Instead of considering each peer as either having the entire file, or not having it, and then downloading from those that have the whole file, we divide the file into parts. We call these parts pieces. At any given point in time, we know which peers have which pieces (or at least, claim to), and what pieces we have, and can make decisions about which piece to download next from whom.
The piece is also the unit of integrity of the torrent. Each piece has a SHA1 hash associated with it, and when we receive a piece, we can hash the data inside, and see if it matches. This allows us to make sure that we’re not downloading junk data.
Pieces and Division
A torrent contains information about what files are in it, as mentioned previously. It also contains information about how big the pieces are: this is a single number specifying how big each piece is.
Complication: All pieces are the same size, except for the last one. Let me illustrate this problem with an example. Let’s say our piece size is 2 bytes, and our torrent contains 5 bytes in total (let’s skim over how this data is divided into files for now). Our data is divided like this:
xx xx x
The first 2 pieces have the announced size, 2 bytes, but the last piece has to be whatever size necessary to “plug in” the end of the data.
This is just an edge case to worry about, and not as tricky as the next complication:
Complication: Pieces don’t belong to one file Let’s continue using the same example as the previous complication, but further specify that the torrent actually contains 2 files: A.png B.png. A is 3 bytes, and B 2 bytes. Our data would now look like this:
AA AB B
The second piece now contains data from 2 different files!
This is because, as far as pieces are concerned, the torrent is just a binary blob. When peers are trading pieces it’s as if the torrent just contained a single file. In fact, in the case of a single file, we don’t have this problem at all, since all the pieces belong to this file.
When there are multiple files, they have a defined order. Conceptually, the binary data in these files is concatenated together, in this predefined order, and then piece division happens as if it were a single file. This means that a piece may actually contain data belonging to an arbitrary of files. It’s actually quite common for a piece to overlap many files. Because movies, which are large, often come with subtitles, which are relatively much smaller, the piece size we use for those torrents are usually larger than the size of all the subtitles combined. It’s not uncommon for a single piece to actually contain all of the subtitles as well as a chunk of the movie itself:
What our algorithm needs to do
Now we get to the crux of this post: the algorithm for saving and retrieving pieces.
We can break down what we do with pieces into 3 seperate tasks:
- Recomposing the pieces into the torrent’s files
- Saving pieces to disk
- Reading pieces from disk
Recomposing the pieces into the torrent’s files
After we’ve downloaded all the pieces, we need to actually assemble the files that compose the torrent from the binary data in those pieces. We need to handle this somehow. One option would be to wait until we have all pieces and then glue them together, another would be to save to files as soon as we have all the pieces in that file.
Saving the pieces to disk
Although we could keep all pieces in memory until we have them all, and then flush them out to disk, this doesn’t work very well for actual torrents, which can easily be multiple gigabytes in size. We need a way to save pieces to disk as they arrive, in such a way that we can easily recompose the pieces into the files that make up the torrent once we have them all.
Reading pieces from disk
A key aspect of bittorrent is that peers aren’t just downloading from other peers, but also uploading the pieces of the files that they already have. Since we don’t keep pieces in memory, but instead save them to disk, we need a way to retrieve these pieces from disk. We also need to be able to do this no matter what stage we’re at. We need a way to read pieces back, whether we’ve glued the pieces back into the torrent files yet or not.
I’ve stuck to details of the protocol itself so far. Now I’m going to describe the approach I came up with for this algorithm. This is not at all a unique approach, nor is it the only, or best way to tackle this problem.
Piece files, start files, and end files
Before we can even start on an algorithm to save pieces to to the right place, we need to decide on what the “right place” is in the first place.
One choice would be to always work within the files in the torrent: when we save a piece, we save different bits of the piece to different sections of different files. We modify the final files directly. This has the advantage of not needing a final recomposition step, since we’re always working with the files themselves. The disadvantage is that the operation of figuring out which sections of which files to write to is quite complicated.
Another approach, which is the one I chose, is instead to use as many files as convenient, and then
recompose them together as a final step. For example, instead of trying to figure out where “piece #38”
needs to go, we just save it in
piece-38.bin and worry about recomposing it later.
We identify the following cases for how we save pieces:
- The piece belongs completely into a single file:
..xx xxxx xx..
In this case we save
piece #N to
- The piece belongs to multiple files:
In this case, we will save the piece into N files, where N is the number of files the piece belongs to. What these files are named depends on the following:
- If a file fits completely into a piece:
- If the piece contains the first bytes of a file
..xx xxAA AA..
Then we save the data for that file in
Note that we could seperate this into 2 cases, but as we’ll see later, not distinguishing these cases changes nothing in the end, and makes the algorithm simpler.
- If the piece contains the last bytes of a file:
..AA AAxx xx..
Then we save the data for that file in
Data Structures and Algorithms
For each of these algorithms, our life is made much easier if we calculate a nicer representation of the file structure before hand. That is to say, we’ll have a special representation of our file structures used for writing the pieces, another for recomposing them, as well as a another, used for reading back the pieces.
Recomposing: Data Structure
The data structure for recomposing pieces together is pretty simple, for each final file in
the torrent, we keep a list of all its dependencies. That is to say, all the pieces that fit completly
into it, as well as all
file.start if those exist.
data Recompose = Recompose [(File, [File])]
To make our algorithm easier, we want to make sure that the dependencies are in the same order as they are in the file, so we can reconstruct the file by writing all dependencies in order.
The algorithm for recomposition is so simple, that we might as well already get it out of the way. This also illustrates the benefit of this approach of using the most suitable data structure for implementing our algorithms.
recompose (Recompose mappings) = forM_ mappings $ \(file, deps) -> do when (allFilesExist deps) $ do writeAllTo deps file removeAll deps
For each file, we check if all its dependencies have already been written to, in which case we can reconstruct the file by concatenating all the dependencies.
Saving: Data Structure
In order to save each piece, we need to know which files the piece maps to, and how many bytes are in each piece. Our data structure thus looks like this:
data SavePieces = SavePieces (Piece -> [(Int, File)])
This contains a list of
(count, file) tuples, listing the
files the piece needs to be saved into, in the order they appear, as well
as how many bytes of the piece should be saved in that file.
This algorithm is better expressed using an imperative formulation, but a functional fold would be able to accomplish the same thing:
def save(piece, mappings): bits = mappings(piece) offset = 0 for (count, file) in bits: write(file, piece[offset:offset+count]) offset += count
We just go linearly through each of the files, and save the right amount of the piece. For this to work correctly, we need to make sure that the order of the files and counts is correct, otherwise we’ll be saving the wrong part of the piece.
Reading: Data Structure
The main complexity with reading pieces from disk, is that the piece may be in different locations,
at different times. At the start, a piece might be in different standalone files, some of which get merged
into a larger file. For example, a piece might map to
A.start, in which case we need to know
to read from
B.end if it exists, otherwise from the right spot in
B, and the same with
A. Note that
it might be the case that B is saved, but A is not, and vice versa.
Let’s start with a mapping from each piece to the locations it’s stored in:
data ReadPieces = ReadPieces (Piece -> [Location])
Now, a location where a piece can be must contain both the small file containing just information for that piece, and then the large file where the piece will eventually be embedded.
Thus, we have:
data Location = Location Embedded Complete type Offset = Int type Count = Int data Embedded = Embedded File Offset Count data Complete = Complete File
The embedded location contains the file, as well as the offset and count, allowing us to easily read the piece from the larger file. For the complete location, we can just read that section by reading the entire small file.
We need to store both locations, because we need to have both the complete, smaller location where that part of the piece is first stored, as well as the larger section of a big file where the piece will eventually be located. We could keep all the small, temporary files around until the entire torrent is completed, but even once we’ve completed the whole torrent, we still need to be able to read pieces in order to upload parts of the file to other pieces.
The algorithm can be given now that we’ve seen a good way to organise the data for this task:
read (ReadPieces mapping) piece = concatBS . forM (mapping piece) $ \l -> do let Location e c = l Embedded fileE offset count = e Complete fileC = c complete <- fileExists fileC if complete then readAll fileC else readAt offset count fileE
We can safely assume that if the smaller, but complete, location no longer exists, then this can only be because the larger file now does. We just concatenate the bytes for each section of the piece, which we first try and read from the complete file, if it exists, otherwise we go and read it from the embedded location of the larger file.
We’ve made our life much easier by seperating everything into different distinct tasks, and using the right data structure for each of those tasks. Using the right data structure makes the algorithm quite simple. One thing we have yet to see, however, is how to construct these data structures from the information about the torrent file itself. That will have to wait for the next post in this series; stay tuned for the next post then :)