Question

Define the violations caused by each of the following: dirty read, nonrepeatable read, and phantoms.

Short answer

A dirty read happens when a transaction reads data that hasn't been committed, potentially leading to inconsistencies if the changes aren't saved. Nonrepeatable read occurs when a transaction reads the same row twice and gets different results, breaking consistency. Phantoms occur when a new row fitting a certain search condition appears in the data set due to another recently committed transaction, breaking two reads' isolation from each other.

Step-by-step solution

Dirty Read Definition

A dirty read transpires when a transaction reads data that hasn't been committed yet. This means that if a transaction T1 modifies a piece of data, and - before T1 is committed or rolled back - another transaction T2 reads that data, T2 has executed a dirty read. It is considered a violation because T1's changes might not be saved, leading to inconsistency.

Nonrepeatable Read Definition

A nonrepeatable read happens when a transaction reads the same row twice, and see different data each time. For instance, consider a transaction T1 which reads a data item. If another transaction (say T2) modifies or deletes that data item and commits, now if T1 reads the same data item again, it gets a changed value, leading to a nonrepeatable read. This is problematic because the same transaction, when executed twice, can lead to different results, causing inconsistency.

Phantoms Definition

Phantoms are a phenomenon that occurs when a transaction re-executes a query returning a set of rows that satisfy a search condition and finds that the set of rows satisfying the condition has changed due to another recently committed transaction. In essence, new records, 'phantoms', have appeared in the data set. It is a violation because it breaks the isolation property of transactions as the result of the query differs when it is executed at different times in a same transaction.

Key concepts

Understanding Dirty Reads

Imagine you are reading a draft version of a report that your friend is still editing. You take some information from that draft and use it in your own work, but then your friend decides not to include that information in the final version of their report. This is akin to a dirty read in database transactions.

During a dirty read, a transaction may read data that has not been finalized, or 'committed,' by another transaction. If the original transaction that made the changes to the data is cancelled or 'rolled back,' those changes are undone. However, the transaction that read the uncommitted data (imagine this as your notes from the draft report) now has incorrect or 'dirty' information that does not reflect the true state of the database. This can lead to data inconsistency and various other problems if that dirty data is used for further operations.

Any system concerned with maintaining data integrity must carefully manage dirty reads, often through isolation levels that either allow or prevent this behavior depending on the requirements for data accuracy versus system performance.

Nonrepeatable Read Explained

Nonrepeatable read occurs in a scenario where you take a photo of a scene, and when you try to take the same photo again, something has changed. Apply this to database transactions, and you get a clearer picture of what nonrepeatable read is.

A nonrepeatable read happens when a transaction reads the same data twice and finds a different result each time. This is similar to reading a value from a cell in a spreadsheet, and then reading it again later to find the value has been altered by someone else's edits. In database terms, if during the course of one transaction, another transaction alters the data (either updates or deletes it) and commits those changes, the first transaction sees a different value when it accesses that data again. This violates the principle of transaction isolation which aims to ensure that one transaction does not interfere with another.

Preventing nonrepeatable reads is crucial for operations where consistency of the data read multiple times during a single transaction is necessary, like generating reports or conducting complex calculations.

Dealing with Phantoms in Transactions

The concept of phantoms in database transactions can be likened to having an unexpected guest show up at a meeting. You've planned for a certain number of attendees, but someone shows up you didn't account for, altering the dynamics.

In databases, phantoms occur when new records are added by one transaction to the results of a query that another transaction is still executing. For example, if you run the same search query twice during one transaction, and between those two times, another transaction has committed new records that fit your search criteria, your second query will return additional results that weren't there the first time—these new records are the 'phantoms.'

This phenomenon can cause issues in scenarios where the consistency of query results is expected, such as when you calculate summaries or generate lists that should remain constant throughout a transaction. Phantoms are particularly troublesome in systems that require strict reporting accuracy or precise control over records. Addressing phantom reads often involves implementing higher isolation levels in the database system, such as Serializable, which can prevent new records from becoming visible to a transaction until it is completed.