Database Management DBAS32100

<p>Non-repeatable read (D)</p> Signup and view all the answers

<p>Sees consistent data throughout its transaction (D)</p> Signup and view all the answers

<p>Reading newly added rows that were committed after the initial read. (A)</p> Signup and view all the answers

<p>READ UNCOMMITTED (A)</p> Signup and view all the answers

<p>It prevents dirty reads but allows non-repeatable reads. (D)</p> Signup and view all the answers

<p>Transaction A reads a value, then Transaction B updates it before Transaction A reads it again. (D)</p> Signup and view all the answers

<p>SERIALIZABLE (C)</p> Signup and view all the answers

<p>Data may be inconsistent due to concurrent transactions. (D)</p> Signup and view all the answers

<p>It can read committed data but may experience phantom reads. (D)</p> Signup and view all the answers

<p>SERIALIZABLE (B)</p> Signup and view all the answers

<p>Preventing non-repeatable reads (C)</p> Signup and view all the answers

<p>A user checking a bank balance before a pending deposit is completed (D)</p> Signup and view all the answers

<p>Transactions appear to run in sequential order (C)</p> Signup and view all the answers

<p>When using the Repeatable Read isolation level (B)</p> Signup and view all the answers

<p>It prevents dirty reads by only allowing committed data to be read (D)</p> Signup and view all the answers

<p>It may lead to phantom reads (A)</p> Signup and view all the answers

<p>The read may reflect incorrect data prior to rollback (A)</p> Signup and view all the answers

<p>Serializable (D)</p> Signup and view all the answers

<p>All components of a transaction must succeed or fail together. (D)</p> Signup and view all the answers

<p>DDL operations commit any outstanding work before executing. (D)</p> Signup and view all the answers

<p>Database state remains valid after the transaction. (A)</p> Signup and view all the answers

<p>Requires atomic values in each column. (B)</p> Signup and view all the answers

<p>To ensure no redundancies exist in data. (A)</p> Signup and view all the answers

<p>Constraints and data types help maintain data integrity. (D)</p> Signup and view all the answers

<p>They must be dependent on the entire primary key. (C)</p> Signup and view all the answers

<p>Once a transaction is committed, it remains permanent. (B)</p> Signup and view all the answers

<p>Transaction B ends up with incorrect data. (A)</p> Signup and view all the answers

<p>A later read receives a value that has been changed by another transaction. (B)</p> Signup and view all the answers

<p>A transaction inserts a new row while another transaction is reading. (C)</p> Signup and view all the answers

<p>Transaction A reads an uncommitted update made by Transaction B. (C)</p> Signup and view all the answers

<p>Counting people in a room that changes while counting. (A)</p> Signup and view all the answers

<p>By reading data, then experiencing an update from another transaction. (C)</p> Signup and view all the answers

<p>Worker B will experience confusion due to incorrect data. (D)</p> Signup and view all the answers

<p>The data can change between multiple read operations by the same transaction. (B)</p> Signup and view all the answers

<p>To deduct $500 from the checking account balance (A)</p> Signup and view all the answers

<p>A transaction can read uncommitted data from another transaction (B)</p> Signup and view all the answers

<p>To keep a record of past transactions including details like time and amount (A)</p> Signup and view all the answers

<p>INSERT INTO Bank_Account (D)</p> Signup and view all the answers

<p>Account_Number (A)</p> Signup and view all the answers

<p>UPDATE Bank_Account with COMMIT option (D)</p> Signup and view all the answers

<p>Dirty Reads (D)</p> Signup and view all the answers

<p>The data becomes accessible for dirty reads (B)</p> Signup and view all the answers

<p>All changes made since the last COMMIT are discarded. (D)</p> Signup and view all the answers

<p>To serve as a rollback marker within the same transaction. (D)</p> Signup and view all the answers

<p>Transactions are executed as atomic units, either fully completed or fully undone. (D)</p> Signup and view all the answers

<p>Two processes are simultaneously waiting for each other to release locks. (A)</p> Signup and view all the answers

<p>If ROLLBACK is called after it has been run. (B)</p> Signup and view all the answers

<p>To obtain results in a specific order regardless of insertion sequence. (B)</p> Signup and view all the answers

<p>Either all changes are applied or none at all. (B)</p> Signup and view all the answers

<p>Both processes are indefinitely stalled until locks are released. (D)</p> Signup and view all the answers

<p>Reading uncommitted data that could be rolled back. (B)</p> Signup and view all the answers

<p>Reading the same row multiple times with different data values. (B)</p> Signup and view all the answers

<p>Querying accounts and finding a new account added after the initial query. (A)</p> Signup and view all the answers

<p>Non-repeatable read (C)</p> Signup and view all the answers

<p>When one transaction updates data and another transaction reads it before it is committed. (A)</p> Signup and view all the answers

<p>The existence of new results emerging after a data insertion while querying. (B)</p> Signup and view all the answers

<p>It can lead to incorrect conclusions from reading uncommitted data. (A)</p> Signup and view all the answers

<p>A transaction reads data before and after another transaction's commit. (D)</p> Signup and view all the answers

<p>The transaction may read uncommitted data which might be incorrect. (A)</p> Signup and view all the answers

<p>READ COMMITTED (A)</p> Signup and view all the answers

<p>SERIALIZABLE (D)</p> Signup and view all the answers

<p>Seeing newly added rows after another transaction has committed changes. (B)</p> Signup and view all the answers

<p>Guarantees that committed data remains unchanged during the transaction. (D)</p> Signup and view all the answers

<p>When a transaction reads data before another transaction commits. (A)</p> Signup and view all the answers

<p>READ COMMITTED (B)</p> Signup and view all the answers

<p>It allows reading of potentially incorrect data before it is finalized. (C)</p> Signup and view all the answers

<p>Aggregated values for specified combinations of groups (B)</p> Signup and view all the answers

<p>To group data based on multiple distinct attributes (D)</p> Signup and view all the answers

<p>To generate subtotals for groups within groups (C)</p> Signup and view all the answers

<p>It only aggregates data based on the first column specified (D)</p> Signup and view all the answers

<p>ROLLUP generates more aggregated data than GROUP BY (C)</p> Signup and view all the answers

<p>To perform calculations on a set of values and return a single result (B)</p> Signup and view all the answers

<p>It aggregates data for every unique value in a column or set of columns (A)</p> Signup and view all the answers

<p>It selects rows that meet a specific condition after aggregation (C)</p> Signup and view all the answers

<p>It delivers cross-tabulation values for all combinations of columns (C)</p> Signup and view all the answers

<p>It creates groups based on all combinations of the provided column values (B)</p> Signup and view all the answers

<p>Cannot perform calculations on a per row basis (C)</p> Signup and view all the answers

<p>It generates subtotals and grand totals across one or more dimensions (B)</p> Signup and view all the answers

<p>A single value summarizing the calculations (B)</p> Signup and view all the answers

<p>Whether the column is part of the aggregated result (B)</p> Signup and view all the answers

<p>To return an integer representing the aggregation level of columns (A)</p> Signup and view all the answers

<p>Only the first column is not null (C)</p> Signup and view all the answers

<p>By combinations of class, color, and price (A)</p> Signup and view all the answers

<p>To provide subtotals across specified dimensions (A)</p> Signup and view all the answers

<p>To filter groups based on aggregate conditions (A)</p> Signup and view all the answers

<p>Aggregate based on combinations of class, color, and quantity (C)</p> Signup and view all the answers

<p>GROUPING_ID returns 3 (A)</p> Signup and view all the answers

Transaction A consistently sees the same balance, even if Transaction B makes changes during its execution.

A problem where a transaction sees different results when reading the same data multiple times.

Ensures that transactions appear as if they ran one after the other, preventing any interference.

A transaction reads data that has not yet been committed

A transaction re-reads a range of data that has change in number, but does not reflect on the first read.

Ensures a transaction sees the same data throughout its duration, preventing non-repeatable reads, but phantom reads are still possible.

The highest isolation level that ensures transactions execute sequentially. This prevents all types of anomalies (dirty reads, non-repeatable reads, and phantom reads).

Transaction reads data before the transaction modifying that data has been committed (making it non-atomic); incorrect, temporary data may lead to faulty conclusions.

Transaction reads committed data; no temporary, incomplete data is visible.

A mechanism to control how data is accessed in concurrent transactions, hence reducing errors.

A transaction is a group of database operations (like insertions, updates, deletions) that are treated as a single, indivisible unit. It's either completed entirely, or none of its operations take effect.

Atomic means that a transaction is indivisible. It's either fully applied to the database or completely discarded, preventing partial updates.

COMMIT is a command that makes all changes within a transaction permanent in the database.

ROLLBACK is a command that undoes all changes made within a transaction, returning the database to the state before the transaction began.

ROLLBACK essentially reverses the effects of each operation in a transaction, bringing the database back to its previous state—either the last committed point or the start of the session.

SAVE POINT is a marker within a transaction that allows you to rollback to a specific point within the ongoing transaction. This is useful for partial rollbacks.

The order in which you insert data into a database doesn't necessarily guarantee the order you'll retrieve it. You might need to use 'ORDER BY' to retrieve data in a specific order.

No, updates are not permanently saved to the database until a COMMIT command is issued. Until then, they can be undone with a ROLLBACK.

A setting that controls how transactions interact with each other, preventing anomalies like dirty reads, non-repeatable reads, and phantom reads.

They ensure data consistency and integrity by preventing conflicting data accesses, especially in multi-user database systems.

If Transaction A rolls back, the changes it made to the database are undone, and the data reverts to its previous state. Any transaction that read the uncommitted data from Transaction A will have inaccurate information.

A second read within a transaction finds different data because another transaction changed the data, even if the first transaction hasn't committed yet.

The transaction sees an inconsistent view of the data. Changes by another transaction might not be reflected in the first transaction's result set.

Isolation levels control how transactions access data in a multi-user environment, minimizing data inconsistencies and ensuring accuracy.

Transactions may rely on incomplete or incorrect data leading to errors or inconsistent outcomes.

By controlling how data is accessed, isolation levels prevent inconsistent results due to concurrent transactions.

A set of properties (Atomicity, Consistency, Isolation, Durability) that ensure reliable database transactions. These properties guarantee data integrity and consistency even when multiple transactions occur simultaneously.

They help maintain data integrity and consistency in multi-user environments, ensuring reliable and accurate data processing.

Different isolation levels offer varying levels of protection from data inconsistency issues, ranging from Read Uncommitted to Serializable.

A transaction is considered atomic if it either completes entirely (all components succeed) or fails completely (one or more components fail). It cannot partially succeed or fail.

A transaction must bring the database to a valid state. It shouldn't introduce incorrect data or violate the database's rules and constraints.

Transactions happen independently of each other. One transaction shouldn't interfere with another, even if they access the same data.

Once a transaction is successfully completed, its changes are permanently recorded in the database and survive any system crashes or failures.

A database design principle that aims to eliminate data redundancy and update anomalies by ensuring that all non-key attributes (attributes not part of the primary key) depend only on the entire primary key, not just part of it.

Data Definition Language (DDL) statements, such as CREATE TABLE or ALTER TABLE, are inherently atomic. They either fully complete or entirely rollback, leaving the database in a consistent state.

ACID properties ensure data integrity and consistency in a multi-user, concurrent environment. They prevent data corruption, ensure accurate data representation, and guarantee a predictable and reliable database system.

These functions perform calculations on a set of rows in a table, returning a single value. They help answer questions like 'How many students have a GPA above 4?' or 'What is the maximum grade in the class?'

This function creates calculations for each unique value in a column or group of columns. It's used for questions like 'What is the average student GPA for each program?' or 'How many students are in each class?'

This creates groups based on all possible combinations of values from multiple columns. Each combination forms a unique group, leading to more detailed calculations

This clause selects the rows that will be included in your calculations before grouping. It filters rows based on certain criteria.

This clause filters the results after grouping. It's used for selecting groups based on a condition calculated from the grouped data.

This operation generates cross-tabulation values for all possible combinations of your selected columns, including null rows.

CUBE operation returns a comprehensive overview of all possible combinations of values in selected columns, including rows with null values to represent absence of data.

CUBE helps you analyze data across different dimensions, revealing patterns, trends, insights, and relationships within your data.

A SQL function that groups data based on multiple columns and produces subtotal values for each group hierarchy. It's helpful for summarizing data with nested relationships, like sales by day, month, and year.

A SQL function that allows you to create multiple groups within a single query. It allows grouping by different combinations of columns, creating a flexible report.

The ROLLUP function allows you to easily create subtotals for multiple levels of grouping within your data, similar to using a nested GROUP BY clause.

The GROUP SETS function enables you to create a report with multiple group combinations for different analyses. You can group by specific sets of columns, providing more flexibility.

ROLLUP creates subtotals based on hierarchical grouping, while GROUP SETS allows you to define specific combinations of columns for grouping, providing more flexibility in data reporting.

A SQL function that returns an integer representing the group set based on null values in a GROUP BY clause. Helps to identify different group levels by combining null and non-null columns.

Cubes in SQL are a way to represent multi-dimensional data where different combinations of attributes like Class, Color, and Manufacturing Year can be grouped together. It helps analyze data across multiple dimensions.

Cubes can be created by grouping data based on different combinations of attributes. You can group by single attributes, multiple attributes, or the entire data set. This provides different levels of granularity for data analysis.

Cubes offer different levels of data aggregation, allowing you to analyze data at various granularities. You can find patterns, trends, and insights by grouping data based on different attributes or combinations.

You can sort the results of cube queries using the GROUPING_ID function to order the output by group set. This brings all records belonging to the same group together in the result set.

You can group data by individual attributes (like 'class') or combinations of attributes (like 'class AND color'). Different groupings provide different levels of information and insights.

Set operations like UNION, INTERSECT, and EXCEPT can be used to combine, overlap, or remove data from different cubes, allowing for flexible manipulation and analysis of data.