Availability Store

This is a utility subsystem responsible for keeping available certain data and pruning that data.

The two data types:

  • Full PoV blocks of candidates we have validated
  • Availability chunks of candidates that were backed and noted available on-chain.

For each of these data we have pruning rules that determine how long we need to keep that data available.

PoV hypothetically only need to be kept around until the block where the data was made fully available is finalized. However, disputes can revert finality, so we need to be a bit more conservative and we add a delay. We should keep the PoV until a block that finalized availability of it has been finalized for 1 day + 1 hour.

Availability chunks need to be kept available until the dispute period for the corresponding candidate has ended. We can accomplish this by using the same criterion as the above. This gives us a pruning condition of the block finalizing availability of the chunk being final for 1 day + 1 hour.

There is also the case where a validator commits to make a PoV available, but the corresponding candidate is never backed. In this case, we keep the PoV available for 1 hour.

There may be multiple competing blocks all ending the availability phase for a particular candidate. Until finality, it will be unclear which of those is actually the canonical chain, so the pruning records for PoVs and Availability chunks should keep track of all such blocks.

Lifetime of the block data and chunks in storage

%3Block data FSMstStoredincIncludedst->incBlockincludedprnPrunedst->prnStored blocktimed outinc->stCompeting blocksfinalizedfinFinalizedinc->finBlockfinalizedfin->prnBlock keep time(1 day + 1 hour) elapsed

Database Schema

We use an underlying Key-Value database where we assume we have the following operations available:

  • write(key, value)
  • read(key) -> Option<value>
  • iter_with_prefix(prefix) -> Iterator<(key, value)> - gives all keys and values in lexicographical order where the key starts with prefix.

We use this database to encode the following schema:

fn main() {
("available", CandidateHash) -> Option<AvailableData>
("chunk", CandidateHash, u32) -> Option<ErasureChunk>
("meta", CandidateHash) -> Option<CandidateMeta>

("unfinalized", BlockNumber, BlockHash, CandidateHash) -> Option<()>
("prune_by_time", Timestamp, CandidateHash) -> Option<()>

Timestamps are the wall-clock seconds since Unix epoch. Timestamps and block numbers are both encoded as big-endian so lexicographic order is ascending.

The meta information that we track per-candidate is defined as the CandidateMeta struct

fn main() {
struct CandidateMeta {
  state: State,
  data_available: bool,
  chunks_stored: Bitfield,

enum State {
  /// Candidate data was first observed at the given time but is not available in any block.
  /// The candidate was first observed at the given time and was included in the given list of unfinalized blocks, which may be
  /// empty. The timestamp here is not used for pruning. Either one of these blocks will be finalized or the state will regress to
  /// `State::Unavailable`, in which case the same timestamp will be reused.
  Unfinalized(Timestamp, Vec<(BlockNumber, BlockHash)>),
  /// Candidate data has appeared in a finalized block and did so at the given time.

We maintain the invariant that if a candidate has a meta entry, its available data exists on disk if data_available is true. All chunks mentioned in the meta entry are available.

Additionally, there is exactly one prune_by_time entry which holds the candidate hash unless the state is Unfinalized. There may be zero, one, or many "unfinalized" keys with the given candidate, and this will correspond to the state of the meta entry.


Input: AvailabilityStoreMessage



For each head in the activated list:

  • Load all ancestors of the head back to the finalized block so we don't miss anything if import notifications are missed. If a StoreChunk message is received for a candidate which has no entry, then we will prematurely lose the data.
  • Note any new candidates backed in the head. Update the CandidateMeta for each. If the CandidateMeta does not exist, create it as Unavailable with the current timestamp. Register a "prune_by_time" entry based on the current timestamp + 1 hour.
  • Note any new candidate included in the head. Update the CandidateMeta for each, performing a transition from Unavailable to Unfinalized if necessary. That includes removing the "prune_by_time" entry. Add the head hash and number to the state, if unfinalized. Add an "unfinalized" entry for the block and candidate.
  • The CandidateEvent runtime API can be used for this purpose.

On OverseerSignal::BlockFinalized(finalized) events:

  • for each key in iter_with_prefix("unfinalized")

    • Stop if the key is beyond ("unfinalized, finalized)
    • For each block number f that we encounter, load the finalized hash for that block.
      • The state of each CandidateMeta we encounter here must be Unfinalized, since we loaded the candidate from an "unfinalized" key.
      • For each candidate that we encounter under f and the finalized block hash,
        • Update the CandidateMeta to have State::Finalized. Remove all "unfinalized" entries from the old Unfinalized state.
        • Register a "prune_by_time" entry for the candidate based on the current time + 1 day + 1 hour.
      • For each candidate that we encounter under f which is not under the finalized block hash,
        • Remove all entries under f in the Unfinalized state.
        • If the CandidateMeta has state Unfinalized with an empty list of blocks, downgrade to Unavailable and re-schedule pruning under the timestamp + 1 hour. We do not prune here as the candidate still may be included in a descendant of the finalized chain.
      • Remove all "unfinalized" keys under f.
  • Update last_finalized = finalized.

    This is roughly O(n * m) where n is the number of blocks finalized since the last update, and m is the number of parachains.

On QueryAvailableData message:

  • Query ("available", candidate_hash)

    This is O(n) in the size of the data, which may be large.

On QueryDataAvailability message:

  • Query whether ("meta", candidate_hash) exists and data_available == true.

    This is O(n) in the size of the metadata which is small.

On QueryChunk message:

  • Query ("chunk", candidate_hash, index)

    This is O(n) in the size of the data, which may be large.

On QueryAllChunks message:

  • Query ("meta", candidate_hash). If None, send an empty response and return.
  • For all 1 bits in the chunks_stored, query ("chunk", candidate_hash, index). Ignore but warn on errors, and return a vector of all loaded chunks.

On QueryChunkAvailability message:

  • Query whether ("meta", candidate_hash) exists and the bit at index is set.

    This is O(n) in the size of the metadata which is small.

On StoreChunk message:

  • If there is a CandidateMeta under the candidate hash, set the bit of the erasure-chunk in the chunks_stored bitfield to 1. If it was not 1 already, write the chunk under ("chunk", candidate_hash, chunk_index).

    This is O(n) in the size of the chunk.

On StoreAvailableData message:

  • If there is no CandidateMeta under the candidate hash, create it with State::Unavailable(now). Load the CandidateMeta otherwise.

  • Store data under ("available", candidate_hash) and set data_available to true.

  • Store each chunk under ("chunk", candidate_hash, index) and set every bit in chunks_stored to 1.

    This is O(n) in the size of the data as the aggregate size of the chunks is proportional to the data.

Every 5 minutes, run a pruning routine:

  • for each key in iter_with_prefix("prune_by_time"):

    • If the key is beyond ("prune_by_time", now), return.
    • Remove the key.
    • Extract candidate_hash from the key.
    • Load and remove the ("meta", candidate_hash)
    • For each erasure chunk bit set, remove ("chunk", candidate_hash, bit_index).
    • If data_available, remove ("available", candidate_hash) This is O(n * m) in the amount of candidates and average size of the data stored. This is probably the most expensive operation but does not need to be run very often.

Basic scenarios to test

Basically we need to test the correctness of data flow through state FSMs described earlier. These tests obviously assume that some mocking of time is happening.

  • Stored data that is never included pruned in necessary timeout

    • A block (and/or a chunk) is added to the store.
    • We never note that the respective candidate is included.
    • Until a defined timeout the data in question is available.
    • After this timeout the data is no longer available.
  • Stored data is kept until we are certain it is finalized.

    • A block (and/or a chunk) is added to the store.
    • It is available.
    • Before the inclusion timeout expires notify storage that the candidate was included.
    • The data is still available.
    • Wait for an absurd amount of time (longer than 1 day).
    • Check that the data is still available.
    • Send finality notification about the block in question.
    • Wait for some time below finalized data timeout.
    • The data is still available.
    • Wait until the data should have been pruned.
    • The data is no longer available.
  • Fork-awareness of the relay chain is taken into account

    • Block B1 is added to the store.
    • Block B2 is added to the store.
    • Notify the subsystem that both B1 and B2 were included in different leafs of relay chain.
    • Notify the subsystem that the leaf with B1 was finalized.
    • Leaf with B2 is never finalized.
    • Leaf with B2 is pruned and its data is no longer available.
    • Wait until the finalized data of B1 should have been pruned.
    • B1 is no longer available.