1. In redo() we save the old state.
2. If we do redo() for the same operation twice, the old state will be
overritten with the new one.
3. This in turn affects undo() and subsequent isAncestor() check.
Signed-off-by: Evgenii Stratonikov <e.stratonikov@yadro.com>
Memory forest is here to check the correctness of boltdb optimized
implementation. Let's keep it simple.
Signed-off-by: Evgenii Stratonikov <e.stratonikov@yadro.com>
Initially it was there to check whether an update is being initiated by
a proper node. It is now obsolete for 2 reasons:
1. Background synchronization fetches all operations from a single node.
2. There are a lot more problems with trust in the tree service, it is
only used in controlled environments.
Signed-off-by: Evgenii Stratonikov <e.stratonikov@yadro.com>
Because synchronization _most likely_ will have apply already existing
operations, it is much faster to check their presence in a read
transaction. However, always doing this will degrade the perfomance
for normal `Apply`. And, let's be honest, it is already not good.
Thus we add a separate parameter which specifies whether this logic is
enabled.
Signed-off-by: Evgenii Stratonikov <e.stratonikov@yadro.com>
Node children are not sorted and could occur in any order.
Signed-off-by: Evgenii Stratonikov <evgeniy@nspcc.ru>
Signed-off-by: Evgenii Stratonikov <evgeniy@morphbits.ru>
Currently there is a possibility for modifying operations to fail
because of I/O errors and a new tree to be created on another shard.
This commit adds existence check for modifying operations.
Read operations remain as they are, not to slow things.
`TreeDrop` is an exception, because this is a tree removal and trying
multiple shards is not an unwanted behaviour.
Signed-off-by: Evgenii Stratonikov <evgeniy@morphbits.ru>
Current implementation prevents invalid operations to become valid at
some later point (consider adding a child to the non-existent parent and
then adding the parent). This seems to diverge from the paper algorithm
and complicates implementation. Make it simpler.
Signed-off-by: Evgenii Stratonikov <evgeniy@nspcc.ru>
Currently to find a node by path we iterate over all the children on
each level. This is far from optimal and scales badly with the number of
nodes on a single level. Thus we introduce "indexed attributes" for
which an additional information is stored and which can be use in
`*ByPath` operations. Currently this set only includes `FileName`
attribute but this may change in future.
Signed-off-by: Evgenii Stratonikov <evgeniy@nspcc.ru>
Consider a node `{FileName: "dir", Attribute: "xxx"}`. In case we add
a new node by path `["dir", "file.txt"]`, create a new intermediate node
with a single attribute.
`GetByPath` now also considers only nodes with a single attribute while building a path.
Signed-off-by: Evgenii Stratonikov <evgeniy@nspcc.ru>
In this commit we implement algorithm for CRDT trees from
https://martin.klepmann.com/papers/move-op.pdf
Each tree is identified by the ID of a container it belongs to
and the tree name itself. Essentially, it is a sequence of operations
which should be applied in chronological order to get a usual tree
representation.
There are 2 backends for now: bbolt database and in-memory.
In-memory backend is here for debugging and will eventually act
as a memory-cache for the on-disk database.
Signed-off-by: Evgenii Stratonikov <evgeniy@nspcc.ru>
