#ipfs #embed #mdns

ipfs-embed

small embeddable ipfs implementation

11 releases (breaking)

new 0.10.0 Jan 9, 2021
0.9.0 Nov 19, 2020
0.8.0 Oct 5, 2020
0.3.0 Jul 27, 2020
Download history 50/week @ 2020-09-25 29/week @ 2020-10-02 14/week @ 2020-10-09 16/week @ 2020-10-16 22/week @ 2020-10-23 21/week @ 2020-10-30 25/week @ 2020-11-06 18/week @ 2020-11-13 18/week @ 2020-11-20 22/week @ 2020-11-27 28/week @ 2020-12-04 5/week @ 2020-12-11 4/week @ 2020-12-18 1/week @ 2020-12-25 14/week @ 2021-01-01 50/week @ 2021-01-08

68 downloads per month
Used in 3 crates

MIT/Apache

50KB
825 lines

ipfs-embed

A small embeddable ipfs implementation compatible with libipld and with a concurrent garbage collector. It supports

  • node discovery via mdns
  • provider discovery via kademlia
  • exchange blocks via bitswap
  • lru eviction policy
  • aliases, an abstraction of recursively named pins with customizable syncing of dags

Getting started

use ipfs_embed::Ipfs;
use ipfs_embed::core::BitswapStorage;
use ipfs_embed::db::StorageService;
use ipfs_embed::net::{NetworkConfig, NetworkService};
use libipld::DagCbor;
use libipld::store::{DefaultParams, Store};
use std::sync::Arc;
use std::time::Duration;

#[derive(Clone, DagCbor, Debug, Eq, PartialEq)]
struct Identity {
    id: u64,
    name: String,
    age: u8,
}

#[async_std::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let sled_config = sled::Config::new().temporary(true);
    let cache_size = 10;
    let sweep_interval = Duration::from_millis(10000);
    let net_config = NetworkConfig::new();
    let storage = Arc::new(StorageService::open(&sled_config, cache_size, sweep_interval).unwrap());
    let bitswap_storage = BitswapStorage::new(storage.clone());
    let network = Arc::new(NetworkService::new(net_config, bitswap_storage).unwrap());
    let ipfs = Ipfs::<DefaultParams, _, _>::new(storage, network);

    let identity = Identity {
        id: 0,
        name: "David Craven".into(),
        age: 26,
    };
    let cid = ipfs.insert(&identity).await?;
    let identity2 = ipfs.get(&cid).await?;
    assert_eq!(identity, identity2);
    println!("identity cid is {}", cid);

    Ok(())
}

What is ipfs?

Ipfs is a p2p network for locating and providing chunks of content addressed data called blocks.

Content addressing means that the data is located via it's hash as opposed to location addressing.

Unsurprisingly this is done using a distributed hash table. To avoid storing large amounts of data in the dht, the dht stores which peers have a block. After determining the peers that are providing a block, the block is requested from those peers.

To verify that the peer is sending the requested block and not an infinite stream of garbage, blocks need to have a finite size. In practice we'll assume a maximum block size of 1MB.

To encode arbitrary data in to 1MB blocks imposes two requirements on the codec. It needs to have a canonical representation to ensure that the same data results in the same hash and it needs to support linking to other content addressed blocks. Codecs having these two properties are called ipld codecs.

A property that follows from content addressing (representing edges as hashes of the node) is that arbitrary graphs of blocks are not possible. A graph of blocks is guaranteed to be directed and acyclic.

{"a":3}
{
  "a": 3,
}
{"/":"QmWATWQ7fVPP2EFGu71UkfnqhYXDYH566qy47CnJDgvs8u"}

Block storage

Let's start with a naive model of a persistent block store.

trait BlockStorage {
    fn get(&self, cid: &Cid) -> Result<Option<Vec<u8>>>;
    fn insert(&mut self, cid: &Cid, data: &[u8]) -> Result<()>;
    fn remove(&mut self, cid: &Cid) -> Result<()>;
}

Since content addressed blocks form a directed acyclic graph, blocks can't simply be deleted. A block may be referenced by multiple nodes, so some form of reference counting and garbage collection is required to determine when a block can safely be deleted. In the interest of being a good peer on the p2p network, we may want to keep old blocks around that other peers may want. So thinking of it as a reference counted cache may be a more appropriate model. We end up with something like this:

trait BlockStorage {
    fn get(&self, cid: &Cid) -> Result<Option<Vec<u8>>>;
    fn insert(&mut self, cid: &Cid, data: &[u8], references: &[Cid]) -> Result<()>;
    fn evict(&mut self) -> Result<()>;
    fn pin(&mut self, cid: &Cid) -> Result<()>;
    fn unpin(&mut self, cid: &Cid) -> Result<()>;
}

To mutate a block we need to perform three steps. Get the block, modify and insert the modified block and finally remove the old one. We also need a map from keys to cids, so even more steps are required. Any of these steps can fail leaving the block store in an inconsistent state, leading to data leakage. To prevent data leakage every api consumer would have to implement a write-ahead-log. To resolve these issues we extend the store with named pins called aliases.

trait BlockStorage {
    fn get(&self, cid: &Cid) -> Result<Option<Vec<u8>>>;
    fn insert(&mut self, cid: &Cid, data: &[u8], references: &[Cid]) -> Result<()>;
    fn evict(&mut self) -> Result<()>;
    fn alias(&mut self, alias: &[u8], cid: Option<&Cid>) -> Result<()>;
    fn resolve(&self, alias: &[u8]) -> Result<Option<Cid>>;
}

Assuming that each operation is atomic and durable, we have the minimal set of operations required to store dags of content addressed blocks.

Networked block storage - the ipfs-embed api

impl Ipfs {
    pub fn new(storage: Arc<S>, network: Arc<N>) -> Self { .. }
    pub fn local_peer_id(&self) -> &PeerId { .. }
    pub async fn listeners(&self) -> Vec<Multiaddr> { .. }
    pub async fn external_addresses(&self) -> Vec<Multiaddr> { .. }
    pub async fn pinned(&self, cid: &Cid) -> Result<Option<bool>> { .. }
    pub async fn get(&self, cid: &Cid) -> Result<Block> {
        if let Some(block) = self.storage.get(cid)? {
            return Ok(block);
        }
        self.network.get(cid).await?;
        if let Some(block) = self.storage.get(cid)? {
            return Ok(block);
        }
        log::error!("block evicted too soon");
        Err(BlockNotFound(*cid))
    }
    pub async fn insert(&self, cid: &Cid) -> Result<()> {
        self.storage.insert(cid)?;
        self.network.provide(cid)?;
        Ok(())
    }
    pub async fn alias(&self, alias: &[u8], cid: Option<&Cid>) -> Result<()> {
        if let Some(cid) = cid {
            self.network.sync(cid).await?;
        }
        self.storage.alias(alias, cid).await?;
        Ok(())
    }
    pub async fn resolve(&self, alias: &[u8]) -> Result<Option<Cid>> {
        self.storage.resolve(alias)?;
        Ok(())
    }
}

Design patterns - ipfs-embed in action

We'll be looking at some patterns used in the chain example. The chain example uses ipfs-embed to store a chain of blocks. A block is defined as:

#[derive(Debug, Default, DagCbor)]
pub struct Block {
    prev: Option<Cid>,
    id: u32,
    loopback: Option<Cid>,
    payload: Vec<u8>,
}

Atomicity

We have to different db's in this example. The one managed by ipfs-embed that stores blocks and aliases and one specific to the example that maps the block index to the block cid, so that we can lookup blocks quickly without having to traverse the entire chain. To guarantee atomicity we define two aliases and perform the syncing in two steps. This ensures that the synced chain always has it's blocks indexed.

const TMP_ROOT: &str = alias!(tmp_root);
const ROOT: &str = alias!(root);

ipfs.alias(TMP_ROOT, Some(new_root)).await?;
for _ in prev_root_id..new_root_id {
    // index block may error for various reasons
}
ipfs.alias(ROOT, Some(new_root)).await?;

Dagification

The recursive syncing algorithm will perform worst when it is syncing a chain, as every block needs to be synced one after the other, without being able to take advantage of any parallelism. To resolve this issue we increase the linking of the chain by including loopbacks, to increase the branching of the dag.

An algorithm was proposed by @rklaehn for this purpose:

fn loopback(block: usize) -> Option<usize> {
    let x = block.trailing_zeros();
    if x > 1 && block > 0 {
        Some(block - (1 << (x - 1)))
    } else {
        None
    }
}

Selectors

Syncing can take a long time and doesn't allow selecting the subset of data that is needed. For this purpose there is an experimental alias_with_syncer api that allows customizing the syncing behaviour. In the chain example it is used to provide block validation, to ensure that the blocks are valid. Altough this api is likely to change in the future.

pub struct ChainSyncer<S: StoreParams, T: Storage<S>> {
    index: sled::Db,
    storage: BitswapStorage<S, T>,
}

impl<S: StoreParams, T: Storage<S>> BitswapSync for ChainSyncer<S, T>
where
    S::Codecs: Into<DagCborCodec>,
{
    fn references(&self, cid: &Cid) -> Box<dyn Iterator<Item = Cid>> {
        if let Some(data) = self.storage.get(cid) {
            let ipld_block = libipld::Block::<S>::new_unchecked(*cid, data);
            if let Ok(block) = ipld_block.decode::<DagCborCodec, Block>() {
                return Box::new(block.prev.into_iter().chain(block.loopback.into_iter()));
            }
        }
        Box::new(std::iter::empty())
    }

    fn contains(&self, cid: &Cid) -> bool {
        self.storage.contains(cid)
    }
}

Efficient block storage implementation - ipfs-embed internals

Ipfs embed uses sled to implement the block store. Sled is a rust embedded key value store, exposing an api that implements persistent lock free BTreeMap with support for transactions involving multiple trees.

type Id = u64;
type Atime = u64;

#[derive(Clone)]
struct BlockCache {
    // Cid -> Id
    lookup: Tree,
    // Id -> Cid
    cid: Tree,
    // Id -> Vec<u8>
    data: Tree,
    // Id -> Vec<Id>
    refs: Tree,
    // Id -> Atime
    atime: Tree,
    // Atime -> Id
    lru: Tree,
}

impl BlockCache {
    // Updates the atime and lru trees and returns the data from the data tree.
    fn get(&self, cid: &Cid) -> Result<Option<Vec<u8>>> { .. }
    // Returns an iterator of blocks sorted by least recently used.
    fn lru(&self) -> impl Iterator<Item = Result<Id>> { self.lru.iter().values() }
    // Inserts into all trees.
    fn insert(&self, cid: &Cid, data: &[u8]) -> Result<()> { ... }
    // Removes from all trees.
    fn remove(&self, id: &Id) -> Result<()> { ... }
    // Returns the recursive set of references.
    fn closure(&self, cid: &Cid) -> Result<Vec<Id>> { ... }
    // A stream of insert/remove events, useful for plugging in a network layer.
    fn subscribe(&self) -> impl Stream<Item = StorageEvent> { ... }
}

Given the description of operations and how it's structured in terms of trees, these operations are straight forward to implement.

#[derive(Clone)]
struct BlockStorage {
    cache: BlockCache,
    // Vec<u8> -> Id
    alias: Tree,
    // Bag of live ids
    filter: Arc<Mutex<CuockooFilter>>,
    // Id -> Vec<Id>
    closure: Tree,
}

impl BlockStorage {
    // get from cache
    fn get(&self, cid: &Cid) -> Result<Option<Vec<u8>>> { self.cache.get(cid) }
    // insert to cache
    fn insert(&self, cid: &Cid, data: &[u8]) -> Result<()> { self.cache.insert(cid, data) }
    // returns the value of the alias tree
    fn resolve(&self, alias: &[u8]) -> Result<Option<Cid>> { ... }
    // remove the lru block that is not in the bag of live ids and remove it's closure from
    // the closure tree
    fn evict(&self) -> Result<()> { ... }
    // aliasing is an expensive operation, the implementation is sketched in pseudo code
    fn alias(&self, alias: &[u8], cid: Option<&Cid>) -> Result<()> {
        // precompute the closure
        let prev_id = self.alias.get(alias)?;
        let prev_closure = self.closure.get(&prev_id)?;
        let new_id = self.cache.lookup(&cid);
        let new_closure = self.cache.closure(&cid);

        // lock the filter preventing evictions
        let mut filter = self.filter.lock().unwrap();
        // make sure that new closure wasn't evicted in the mean time
        for id in &new_closure {
            if !self.cache.contains_id(&id) {
                return Err("cannot alias, missing references");
            }
        }
        // update the live set
        for id in &new_closure {
            filter.add(id);
        }
        for id in &prev_closure {
            filter.delete(id);
        }
        // perform transaction
        let res = (&self.alias, &self.closure).transaction(|(talias, tclosure)| {
            if let Some(id) = prev_id.as_ref() {
                talias.remove(alias)?;
            }
            if let Some(id) = id.as_ref() {
                talias.insert(alias, id)?;
                tclosure.insert(id, &closure)?;
            }
            Ok(())
        });
        // if transaction failed revert live set to previous state
        if res.is_err() {
            for id in &prev_closure {
                filter.add(id);
            }
            for id in &closure {
                filter.delete(id)
            }
        }
        res
    }
}

Efficiently syncing dags of blocks - libp2p-bitswap internals

Bitswap is a very simple protocol. It was adapted and simplified for ipfs-embed. The message format can be represented by the following enums.

pub enum BitswapRequest {
    Have(Cid),
    Block(Cid),
}

pub enum BitswapResponse {
    Have(bool),
    Block(Vec<u8>),
}

The mechanism for locating providers can be abstracted. A dht can be plugged in or a centralized db query. The bitswap api looks as follows:

pub enum Query {
    Get(Cid),
    Sync(Cid),
}

pub enum BitswapEvent {
    GetProviders(Cid),
    QueryComplete(Query, Result<()>),
}

impl Bitswap {
    pub fn add_address(&mut self, peer_id: &PeerId, addr: Multiaddr) { .. }
    pub fn get(&mut self, cid: Cid) { .. }
    pub fn cancel_get(&mut self, cid: Cid) { .. }
    pub fn add_provider(&mut self, cid: Cid, peer_id: PeerId) { .. }
    pub fn complete_get_providers(&mut self, cid: Cid) { .. }
    pub fn poll(&mut self, cx: &mut Context) -> BitswapEvent { .. }
}

So what happens when you create a get request? First all the providers in the initial set are queried with the have request. As an optimization, in every batch of queries a block request is sent instead. If the get query finds a block it returns a query complete. If the block wasn't found in the initial set, a GetProviders(Cid) event is emitted. This is where the bitswap consumer tries to locate providers by for example performing a dht lookup. These providers are registered by calling the add_provider method. After the locating of providers completes, it is signaled by calling complete_get_providers. The query manager then performs bitswap requests using the new provider set which results in the block being found or a block not found error.

Often we want to sync an entire dag of blocks. We can efficiently sync dags of blocks by adding a sync query that runs get queries in parallel for all the references of a block. The set of providers that had a block is used as the initial set in a reference query. For this we extend our api with the following calls.

/// Bitswap sync trait for customizing the syncing behaviour.
pub trait BitswapSync {
    /// Returns the list of blocks that need to be synced.
    fn references(&self, cid: &Cid) -> Box<dyn Iterator<Item = Cid>>;
    /// Returns if a cid needs to be synced.
    fn contains(&self, cid: &Cid) -> bool;
}

impl Bitswap {
    pub fn sync(&mut self, cid: Cid, syncer: Arc<dyn BitswapSync>) { .. }
    pub fn cancel_sync(&mut self, cid: Cid) { .. }
}

Note that we can customize the syncing behaviour arbitrarily by selecting a subset of blocks we want to sync. See design patterns for more information.

License

MIT OR Apache-2.0

Dependencies

~9–15MB
~292K SLoC