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In multi-user applications, different users can modify the same data simultaneously. To deal with reads and updates of the same data sets happening in parallel, transactional subsystems of products such as Ignite implement optimistic and pessimistic locking. In the pessimistic mode, an application will acquire locks for all the data it plans to change and will apply the changes after all the locks are owned exclusively while in the optimistic mode the locks acquisition is postponed to a later phase when a transaction is being already committed.
Locks acquisition time also depends on a type of isolation level. Let's start with the review of isolation levels in conjunction with the pessimistic mode.
In pessimistic & read committed mode the locks are acquired before the changes brought by write operations such (as put or putAll) are applied as it's shown below:
The pessimistic mode holds locks until the transaction is finished that prevents accessing locked data from other transactions. Optimistic transactions in Ignite might increase the throughput of an application by lowering contention among transactions by moving the locks acquisition to a later phase.
In optimistic transactions, locks are acquired on primary nodes during the "prepare" phase, then promoted to backup nodes and released once the transaction is committed. Depending on an isolation level, if Ignite detects that a version of an entry has been changed since the time it was requested by a transaction then the transaction will fail at the "prepare" phase and it will be up to an application to decide whether to restart the transaction or not.
For the isolation level Read committed and Repeatable read locks are obtained at the time of implementation of phase "prepare", at the same time check that the version has not changed since the beginning of the transaction is not executed.
This is exactly how optimistic & serializable transactions (aka. deadlock-free transactions) work in Ignite:
On the other hand, repeatable read and read committed optimistic transactions never check if a version of an entry is changed. This mode might bring extra performance benefits but does not give any atomicity guarantees and, thus, rarely used in practice:
Now let's review the entire lifecycle of a transaction in Ignite. Presently it's assumed that the cluster is stable and no any outages happen.
a unique transaction identifier is generated;
the start time of the transaction is recorded;
current topology version/state is recorded;
etc.
Once after that the transaction status is set to "active" and Ignite starts executing read/write operations that are a part of the transaction following rules of either optimistic or pessimistic modes and specific isolation levels.