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Describe the storage layer in the technical report #2853

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12 changes: 6 additions & 6 deletions ouroboros-consensus/docs/report/chapters/consensus/protocol.tex
Original file line number Diff line number Diff line change
Expand Up @@ -284,12 +284,12 @@ \subsection{Protocol state management}

Re-applying previously-validated blocks happens when we are replaying blocks
from the immutable database when initialising the in-memory ledger state
(\cref{ledgerdb:initialisation}). It is also useful during chain selection
(\cref{chainsel}): depending on the consensus protocol, we may end up switching
relatively frequently between short-lived forks; when this happens, skipping
expensive checks can improve the performance of the node. \todo{How does this
relate to the best case == worst case thing? Or to the asymptotic
attacker/defender costs?}
(\cref{ledgerdb:on-disk:initialisation}). It is also useful during chain
selection (\cref{chainsel}): depending on the consensus protocol, we may end up
switching relatively frequently between short-lived forks; when this happens,
skipping expensive checks can improve the performance of the node. \todo{How
does this relate to the best case == worst case thing? Or to the asymptotic
attacker/defender costs?}

\subsection{Leader selection}
\label{consensus:class:leaderselection}
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Original file line number Diff line number Diff line change
Expand Up @@ -47,8 +47,8 @@ \section{Serialising for storage}

\begin{itemize}
\item Blocks
\item The extended ledger state (\cref{storage:extledgerstate}) which is the
combination of:
\item The extended ledger state (see \cref{storage:extledgerstate} and
\cref{ledgerdb:on-disk}) which is the combination of:
\begin{itemize}
\item The header state (\cref{storage:headerstate})
\item The ledger state\todo{link?}
Expand Down
191 changes: 191 additions & 0 deletions ouroboros-consensus/docs/report/chapters/storage/chaindb.tex
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,196 @@ \chapter{Chain Database}

TODO\todo{TODO}: This is currently a disjoint collection of snippets.

\section{Union of the Volatile DB and the Immutable DB}
\label{chaindb:union}

As discussed in \cref{storage:components}, the blocks in the Chain DB are
divided between the Volatile DB (\cref{volatile}) and the Immutable DB
(\cref{immutable}). Yet, it presents a unified view of the two databases.
Whereas the Immutable DB only contains the immutable chain and the Volatile DB
the volatile \emph{parts} of multiple forks, by combining the two, the Chain DB
contains multiple forks.

\subsection{Looking up blocks}
\label{chaindb:union:lookup}

Just like the two underlying databases the Chain DB allows looking up a
\lstinline!BlockComponent! of a block by its point. By comparing the slot number
of the point to the slot of the immutable tip, we could decide in which database
to look up the block. However, this would not be correct: the point might have a
slot older than the immutable tip, but refer to a block not in the Immutable DB,
i.e., a block on an older fork. More importantly, there is a potential race
condition: between the time at which the immutable tip was retrieved and the
time the block is retrieved from the Volatile DB, the block might have been
copied to the Immutable DB and garbage collected from the Volatile DB, resulting
in a false negative. Nevertheless, the overlap between the two makes this
scenario very unlikely.

For these reasons, we look up a block in the Chain DB as follows. We first look
up the given point in the Volatile DB. If the block is not in the Volatile DB,
we fall back to the Immutable DB. This means that if, at the same, a block is
copied from the Volatile DB to the Immutable DB and garbage collected from the
Volatile DB, we will still find it in the Immutable DB. Note that failed lookups
in the Volatile DB are cheap, as no disk access is required.

\subsection{Iterators}
\label{chaindb:union:iterators}

Similar to the Immutable DB (\cref{immutable:api:iterators}), the Chain DB
allows streaming blocks using iterators. We only support streaming blocks from
the current chain or from a recent fork. We \emph{do not} support streaming from
a fork that starts before the current immutable tip, as these blocks are likely
to be garbage collected soon. Moreover, it is of no use to us to serve another
node blocks from a fork we discarded.

We might have to stream blocks from the Immutable DB, the Volatile DB, or from
both. If the end bound is older or equal to the immutable tip, we simply try to
open an Immutable DB iterator with the given bounds. If the end bound is newer
than the immutable tip, we construct a path of points (see
\lstinline!filterByPredecessor! in \cref{volatile:api}) connecting the end bound
to the start bound. This path is either entirely in the Volatile DB or it is
partial because a block is missing from the Volatile DB. If the missing block is
the tip of the Immutable DB, we will have to stream from the Immutable DB in
addition to the Volatile DB. If the missing block is not the tip of the
Immutable DB, we consider the range to be invalid. In other words, we allow
streaming from both databases, but only if the immutable tip is the transition
point between the two, it cannot be a block before the tip, as that would mean
the fork is too old.

\todo{TODO} Image?

To stream blocks from the Volatile DB, we maintain the constructed path of
points as a list in memory and look up the corresponding block (component) in
the Volatile DB one by one.

Consider the following scenario: we open a Chain DB iterator to stream the
beginning of the current volatile chain, i.e., the blocks in the Volatile DB
right after the immutable tip. However, before streaming the iterator's first
block, we switch to a long fork that forks off all the way back at our immutable
tip. If that fork is longer than the previous chain, blocks from the start of
our chain will be copied from the Volatile DB to the Immutable DB,\todo{link}
advancing the immutable tip. This means the blocks the iterator will stream are
now part of a fork older than $k$. In this new situation, we would not allow
opening an iterator with the same range as the already-opened iterator. However,
we do allow streaming these blocks using the already opened iterator, as the
blocks to stream are unlikely to have already been garbage collected.
Nevertheless, it is still theoretically possible\footnote{This is unlikely, as
there is a delay between copying and garbage collection (see
\cref{chaindb:gc:delay}) and there are network time-outs on the block fetch
protocol, of which the server-side (see \cref{servers:blockfetch}) is the
primary user of Chain DB iterators.} that such a block has already been garbage
collected. For this reason, the Chain DB extends the Immutable DB's
\lstinline!IteratorResult! type (see \cref{immutable:api:iterators}) with the
\lstinline!IteratorBlockGCed! constructor:
%
\begin{lstlisting}
data IteratorResult blk b =
IteratorExhausted
| IteratorResult b
| IteratorBlockGCed (RealPoint blk)
\end{lstlisting}

There is another scenario to consider: we stream the blocks from the start of
the current volatile chain, just like in the previous scenario. However, in this
case, we do not switch to a fork, but our chain is extended with new blocks,
which means blocks from the start of our volatile chain are copied from the
Volatile DB to the Immutable DB. If these blocks have been copied and garbage
collected before the iterator is used to stream them from the Volatile DB (which
is unlikely, as explained in the previous scenario), the iterator will
incorrectly yield \lstinline!IteratorBlockGCed!. Instead, when a block that was
planned to be streamed from the Volatile DB is missing, we first look in the
Immutable DB for the block in case it has been copied there. After the block
copied to the Immutable has been streamed, we continue with the remaining blocks
to stream from the Volatile DB. It might be the case that the next block has
also been copied and garbage collected, requiring another switch to the
Immutable DB. In the theoretical worst case, we have to switch between the two
databases for each block, but this is nearly impossible to happen in practice.

\subsection{Followers}
\label{chaindb:union:followers}

In addition to iterators, the Chain DB also supports \emph{followers}. Unlike an
iterator, which is used to request a static segment of the current chain or a
recent fork, a follower is used to follow the \emph{current chain}. Either from
the start of from a suggested more recent point. Unlike iterators, followers are
dynamic, they will follow the chain when it grows or forks. A follower is
pull-based, just like its primary user, the chain sync server (see
\cref{servers:chainsync}). This avoids the need to have a growing queue of
changes to the chain on the server side in case the client side is slower.

The API of a follower is as follows:
%
\begin{lstlisting}
data Follower m blk a = Follower {
followerInstruction :: m (Maybe (ChainUpdate blk a))
, followerInstructionBlocking :: m (ChainUpdate blk a)
, followerForward :: [Point blk] -> m (Maybe (Point blk))
, followerClose :: m ()
}
\end{lstlisting}
%
The \lstinline!a! parameter is the same \lstinline!a! as the one in
\lstinline!BlockComponent! (see \cref{immutable:api:block-component}), as a
follower for any block component \lstinline!a! can be opened.

A follower always has an implicit position associated with it. The
\lstinline!followerInstruction! operation and its blocking variant allow
requesting the next instruction w.r.t.\ the follower's implicit position, i.e.,
a \lstinline!ChainUpdate!:
%
\begin{lstlisting}
data ChainUpdate block a =
AddBlock a
| RollBack (Point block)
\end{lstlisting}
%
The \lstinline!AddBlock! constructor indicates that to follow the current chain,
the follower should extend its chain with the given block (component). Switching
to a fork is represented by first rolling back to a certain point
(\lstinline!RollBack!), followed by at least as many new blocks
(\lstinline!AddBlock!) as blocks that have been rolled back. If we were to
represent switching to a fork using a constructor like:
%
\begin{lstlisting}
| SwitchToFork (Point block) [a]
\end{lstlisting}
%
we would need to have many blocks or block components in memory at the same
time.

These operations are implemented as follows. In case the follower is looking at
the immutable part of the chain, an Immutable DB iterator is used and no
rollbacks will be encountered. When the follower has advanced into the volatile
part of the chain, the in-memory fragment containing the last $k$ headers is
used (see \cref{storage:inmemory}). Depending on the block component, the
corresponding block might have to be read from the Volatile DB.

When a new chain has been adopted during chain selection (see
\cref{chainsel:addblock}), all open followers that are looking at the part of
the current chain that was rolled back are updated so that their next
instruction will be the correct \lstinline!RollBack!. By definition, followers
looking at the immutable part of the chain will be unaffected.

By default, a follower will start from the very start of the chain, i.e., at
genesis. Accordingly, the first instruction will be an \lstinline!AddBlock! with
the very first block of the chain. As mentioned, the primary user of a follower
is the chain sync server, of which the clients in most cases already have large
parts of the chain. The \lstinline!followerForward! operation can be used in
these cases to find a more recent intersection from which the follower can
start. The client will sent a few recent points from its chain and the follower
will try to find the most recent of them that is on our current chain. This is
implemented by looking up blocks by their point in the current chain fragment
and the Immutable DB.

Followers are affected by garbage collection similarly to how iterators are
(\cref{chaindb:union:iterators}): when the implicit position of the follower is
in the immutable part of the chain, an Immutable DB iterator with a static range
is used. Such an iterator is not aware of blocks appended to the Immutable DB
since the iterator was opened. This means that when the iterator reaches its
end, we first have to check whether more blocks have been appended to the
Immutable DB. If so, a new iterator is opened to stream these blocks. If not, we
switch over to the in-memory fragment.

\section{Block processing queue}
\label{chaindb:queue}

Expand Down Expand Up @@ -100,6 +290,7 @@ \section{Garbage collection}
refer here, though, not to the vol DB chapter.

\subsection{GC delay}
\label{chaindb:gc:delay}

For performance reasons neither the immutable DB nor the volatile DB ever makes
explicit \lstinline!fsync! calls to flush data to disk. This means that when the
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -344,8 +344,9 @@ \section{Initialisation}

\item
\label{chaindb:init:imm}
Initialise the immutable database, determine its tip $I$, and ask the
ledger DB for the corresponding ledger state $L$.
Initialise the immutable database, determine its tip $I$, and ask the ledger DB
for the corresponding ledger state $L$ (see
\cref{ledgerdb:on-disk:initialisation}).

\item Compute the set of candidates anchored at the immutable database's tip
\label{chaindb:init:compute}
Expand Down
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