Update Snapshot & Root approach to get the root always from the db,
except in the cases that the tree is a snapshot, in which the root will
be in memory.
In this way, when a snapshot is performed and the original tree gets
modifyed, the snapshot will still point to the old root. Also, the root
obtained from the db, uses also the db.ReadTx, so if the root is being
modifyied in the current tx (db.WriteTx), when getting the root it will
be return the lastest version that is in the tx but not yet in the db.
- Update upFromNodes function for unbalanced tree case
- Add AddBatchTestVector2 & 3 with some edge cases
- Add checkRoots test method, which stores the Dump of the tree to file for after-debug
Case tree empty, AddBatch was 10.95x times faster than without AddBatch
nCPU: 4, nLeafs: 1024, hash: Poseidon, db: memory
dbgStats(hash: 2.047k, dbGet: 1, dbPut: 2.049k)
Case tree not empty w/ few leafs, AddBatch was 7.28x times faster than without AddBatch
nCPU: 4, nLeafs: 1024, hash: Poseidon, db: memory
dbgStats(hash: 2.047k, dbGet: 198, dbPut: 2.049k)
Case tree not empty w/ enough leafs, AddBatch was 5.94x times faster than without AddBatch
nCPU: 4, nLeafs: 1024, hash: Poseidon, db: memory
dbgStats(hash: 2.047k, dbGet: 1.000k, dbPut: 2.049k)
Case tree not empty, AddBatch was 9.27x times faster than without AddBatch
nCPU: 4, nLeafs: 4096, hash: Poseidon, db: memory
dbgStats(hash: 8.191k, dbGet: 1.800k, dbPut: 8.193k)
Case tree not empty & unbalanced, AddBatch was 10.67x times faster than without AddBatch
nCPU: 4, nLeafs: 4096, hash: Poseidon, db: memory
dbgStats(hash: 10.409k, dbGet: 2.668k, dbPut: 10.861k)
TestAddBatchBench: nCPU: 4, nLeafs: 50000, hash: Blake2b, db: badgerdb
Add loop: 10.10829114s
AddBatch: 732.030263ms
dbgStats(hash: 122.518k, dbGet: 1, dbPut: 122.520k)
TestDbgStats
add in loop in emptyTree dbgStats(hash: 141.721k, dbGet: 134.596k, dbPut: 161.721k)
addbatch caseEmptyTree dbgStats(hash: 24.402k, dbGet: 1, dbPut: 24.404k)
addbatch caseNotEmptyTree dbgStats(hash: 26.868k, dbGet: 2.468k, dbPut: 26.872k)
CASE D: Already populated Tree
==============================
- Use A, B, C, D as subtree
- Sort the Keys in Buckets that share the initial part of the path
- For each subtree add there the new leafs
R
/ \
/ \
/ \
* *
/ | / \
/ | / \
/ | / \
L: A B C D
/\ /\ / \ / \
... ... ... ... ... ...
CASE C: ALMOST CASE B --> if Tree has few Leafs (but numLeafs>=minLeafsThreshold)
==============================================================================
- Use A, B, G, F as Roots of subtrees
- Do CASE B for each subtree
- Then go from L to the Root
R
/ \
/ \
/ \
* *
/ | / \
/ | / \
/ | / \
L: A B G D
/ \
/ \
/ \
C *
/ \
/ \
/ \
... ... (nLeafs >= minLeafsThreshold)
CASE B: ALMOST CASE A, Almost empty Tree --> if Tree has numLeafs < minLeafsThreshold
==============================================================================
- Get the Leafs (key & value) (iterate the tree from the current root getting
the leafs)
- Create a new empty Tree
- Do CASE A for the new Tree, giving the already existing key&values (leafs)
from the original Tree + the new key&values to be added from the AddBatch call
R R
/ \ / \
A * / \
/ \ / \
B C * *
/ | / \
/ | / \
/ | / \
L: A B G D
/ \
/ \
/ \
C *
/ \
/ \
/ \
... ... (nLeafs < minLeafsThreshold)
arnaucube