Challenges and Handling Mechanisms of Database Transactions
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Challenges and Handling Mechanisms of Database Transactions
Authors:
Arjun Reddy Lingala
Abstract—Modern computing relies heavily on distributed sys- tems to achieve scalability, fault tolerance, and high availability. However, ensuring reliable transaction management across multi- ple independent nodes introduces several complexities, including maintaining consistency, managing concurrency, and recovering from failures. In reality of data systems many things can go wrong, the database software or hardware may fail at any time, the application may crash at any time, interruptions in the network can unexpectedly cut off the application from the database, or one database node from another, several clients may write to the database at the same time, overwriting each other’s changes, client may read data that doesn’t make sense because it has only partially been updated, race conditions between clients can cause surprising bugs. In order to be reliable, a system has to deal with these faults and ensure that they don’t cause catastrophic failure of the entire system. However, implementing fault- tolerance mechanisms is a lot of work. It requires a lot of careful thinking about all the things that can go wrong, and a lot of testing to ensure that the solution actually works. For decades, transactions have been the mechanism of choice for simplifying these issues. A transaction is a way for an application to group several reads and writes together into a logical unit. Conceptually, all the reads and writes in a transaction are executed as one operation: either the entire transaction succeeds (commit) or it fails (abort, rollback). If it fails, the application can safely retry. In this paper, we will examine many examples of things that can go wrong, and explore the algorithms that databases use to guard against those issues. We will go especially deep in the area of concurrency control, discussing various kinds of race conditions that can occur and how databases implement isolation levels such as read committed, snapshot isolation, and serializability.
Keywords—Transactions, Distributed Transaction, ACID, Atomicity, Consistency, Isolation, Durability, Read Committed, Snapshot Isolation, Serializability, Two Phase Locking, Serializ- able Snapshot Isolation