Vladimir, Thanks for a throughout overview and proposal. > Also we could try employing tiered approach > 1) Try to keep everything in-memory to minimize writes to blocks > 2) Fallback to persistent lock data if certain threshold is reached.
What are the benefits of the backed-by-persistence approach in compare to the one based on tuples? Specifically: - will the persistence approach work for both 3rd party and Ignite persistence? - any performance impacts depending on a chosen method? - what’s faster to implement? — Denis > On Dec 13, 2017, at 2:10 AM, Vladimir Ozerov <voze...@gridgain.com> wrote: > > Igniters, > > As you probably we know we work actively on MVCC [1] and transactional SQL > [2] features which could be treated as a single huge improvement. We face a > number of challenges and one of them is locking. > > At the moment information about all locks is kept in memory on per-entry > basis (see GridCacheMvccManager). For every locked key we maintain current > lock owner (XID) and the list of would-be-owner transactions. When > transaction is about to lock an entry two scenarios are possible: > 1) If entry is not locked we obtain the lock immediately > 2) if entry is locked we add current transaction to the wait list and jumps > to the next entry to be locked. Once the first entry is released by > conflicting transaction, current transaction becomes an owner of the first > entry and tries to promote itself for subsequent entries. > > Once all required locks are obtained, response is sent to the caller. > > This approach doesn't work well for transactional SQL - if we update > millions of rows in a single transaction we will simply run out of memory. > To mitigate the problem other database vendors keep information about locks > inside the tuples. I propose to apply the similar design as follows: > > 1) No per-entry lock information is stored in memory anymore. > 2) The list of active transactions are maintained in memory still > 3) When TX locks an entry, it sets special marker to the tuple [3] > 4) When TX meets already locked entry, it enlists itself to wait queue of > conflicting transaction and suspends > 5) When first transaction releases conflicting lock, it notifies and wakes > up suspended transactions, so they resume locking > 6) Entry lock data is cleared on transaction commit > 7) Entry lock data is not cleared on rollback or node restart; Instead, we > will could use active transactions list to identify invalid locks and > overwrite them as needed. > > Also we could try employing tiered approach > 1) Try to keep everything in-memory to minimize writes to blocks > 2) Fallback to persistent lock data if certain threshold is reached. > > Thoughts? > > [1] https://issues.apache.org/jira/browse/IGNITE-3478 > [2] https://issues.apache.org/jira/browse/IGNITE-4191 > [3] Depends on final MVCC design - it could be per-tuple XID, undo vectors, > per-block transaction lists, etc.. > > Vladimir.
