Can an action in a smart contract concurrently executed?

Question

In a smart contract if an action is executed simultaneously and if it tries to modify the same record in a table(using multi index API), How to add mutual exclusion to the shared resources?

For eg. In eosio.token smart contract, if the transfer function is called simultaneously with the same "from account_name" then Will there be a chance of improper token deduction in the from account?

Answer 1

If I understood everything correctly:

A transaction stores multiple actions. Transactions are stored in blocks. Every block producer has its turn (approx. 0.5 sec for this DPOS) to create a block and execute the corresponding transactions including their actions deterministically. If there would be concurrent write access of multiple block producers to the shared data, it would break consensus.

What could be a problem is, that you could access the data from between the time a block producer has created the block (where a write happened), but others did not yet mirrow the updates. Then you would have old data. But it would not be a big deal, if you try to change the data with a new write based on the old values, because the transactions/actions would be invalidated by the block producers.

Please correct me if I am wrong or do miss something.

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Edit:

I reread the whitepaper. In fact for databases the access is serializable. This will likely be handled like in conventional DBMS.

To support parallel execution, each account can also define any number of scopes within their database. The block producers will schedule transaction in such a way that there is no conflict over memory access to scopes and therefore they can be executed in parallel.

For the June 2018 release everything seems to be single threaded. For later releases there is this concept of cycles and shards:

 Block

    Region

      Cycles (sequential)

        Shards (parallel)

          Transactions (sequential)

            Actions (sequential)

              Receiver and Notified Accounts (parallel)

I would recommend to reread the whitepaper as well.