SQL

SQL Interview Questions

What does UNION do? What is the difference between UNION and UNION ALL?

UNION merges the contents of two structurally-compatible tables into a single combined table. The difference between UNION and UNION ALL is that UNION will omit duplicate records whereas UNION ALL will include duplicate records.

It is important to note that the performance of UNION ALL will typically be better than UNION, since UNION requires the server to do the additional work of removing any duplicates. So, in cases where is certain that there will not be any duplicates, or where having duplicates is not a problem, use of UNION ALL would be recommended for performance reasons.

List and explain the different types of JOIN clauses supported in ANSI-standard SQL.

ANSI-standard SQL specifies five types of JOIN clauses as follows:

• INNER JOIN (a.k.a. “simple join”): Returns all rows for which there is at least one match in BOTH tables. This is the default type of join if no specific JOIN type is specified.

• LEFT JOIN (or LEFT OUTER JOIN): Returns all rows from the left table, and the matched rows from the right table; i.e., the results will contain all records from the left table, even if the JOIN condition doesn’t find any matching records in the right table. This means that if the ON clause doesn’t match any records in the right table, the JOIN will still return a row in the result for that record in the left table, but with NULL in each column from the right table.

• RIGHT JOIN (or RIGHT OUTER JOIN): Returns all rows from the right table, and the matched rows from the left table. This is the exact opposite of a LEFT JOIN; i.e., the results will contain all records from the right table, even if the JOIN condition doesn’t find any matching records in the left table. This means that if the ON clause doesn’t match any records in the left table, the JOIN will still return a row in the result for that record in the right table, but with NULL in each column from the left table.

• FULL JOIN (or FULL OUTER JOIN): Returns all rows for which there is a match in EITHER of the tables. Conceptually, a FULL JOIN combines the effect of applying both a LEFT JOIN and a RIGHT JOIN; i.e., its result set is equivalent to performing a UNION of the results of left and right outer queries.

• CROSS JOIN: Returns all records where each row from the first table is combined with each row from the second table (i.e., returns the Cartesian product of the sets of rows from the joined tables). Note that a CROSS JOIN can either be specified using the CROSS JOIN syntax (“explicit join notation”) or (b) listing the tables in the FROM clause separated by commas without using a WHERE clause to supply join criteria (“implicit join notation”).

What is an execution plan? When would you use it? How would you view the execution plan?

An execution plan is basically a road map that graphically or textually shows the data retrieval methods chosen by the SQL server’s query optimizer for a stored procedure or ad hoc query. Execution plans are very useful for helping a developer understand and analyze the performance characteristics of a query or stored procedure, since the plan is used to execute the query or stored procedure.

In many SQL systems, a textual execution plan can be obtained using a keyword such as EXPLAIN, and visual representations can often be obtained as well. In Microsoft SQL Server, the Query Analyzer has an option called “Show Execution Plan” (located on the Query drop down menu). If this option is turned on, it will display query execution plans in a separate window when a query is run.

List and explain each of the ACID properties that collectively guarantee that database transactions are processed reliably.

ACID (Atomicity, Consistency, Isolation, Durability) is a set of properties that guarantee that database transactions are processed reliably. They are defined as follows:

• Atomicity. Atomicity requires that each transaction be “all or nothing”: if one part of the transaction fails, the entire transaction fails, and the database state is left unchanged. An atomic system must guarantee atomicity in each and every situation, including power failures, errors, and crashes.
• Consistency. The consistency property ensures that any transaction will bring the database from one valid state to another. Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof.

• Isolation. The isolation property ensures that the concurrent execution of transactions results in a system state that would be obtained if transactions were executed serially, i.e., one after the other. Providing isolation is the main goal of concurrency control. Depending on concurrency control method (i.e. if it uses strict - as opposed to relaxed - serializability), the effects of an incomplete transaction might not even be visible to another transaction.
• Durability. Durability means that once a transaction has been committed, it will remain so, even in the event of power loss, crashes, or errors. In a relational database, for instance, once a group of SQL statements execute, the results need to be stored permanently (even if the database crashes immediately thereafter). To defend against power loss, transactions (or their effects) must be recorded in a non-volatile memory.

What are the NVL and the NVL2 functions in SQL? How do they differ?

Both the NVL(exp1, exp2) and NVL2(exp1, exp2, exp3) functions check the value exp1 to see if it is null.

With the NVL(exp1, exp2) function, if exp1 is not null, then the value of exp1 is returned; otherwise, the value of exp2 is returned, but case to the same data type as that of exp1.

With the NVL2(exp1, exp2, exp3) function, if exp1 is not null, then exp2 is returned; otherwise, the value of exp3 is returned.

What is the difference between the WHERE and HAVING clauses?

When GROUP BY is not used, the WHERE and HAVING clauses are essentially equivalent.

However, when GROUP BY is used:

• The WHERE clause is used to filter records from a result. The filtering occurs before any groupings are made.
• The HAVING clause is used to filter values from a group (i.e., to check conditions after aggregation into groups has been performed).

What is the difference between single-row functions and multiple-row functions?

Single-row functions work with single row at a time. Multiple-row functions work with data of multiple rows at a time.

What is the group by clause used for?

The group by clause combines all those records that have identical values in a particular field or any group of fields.

What is the difference between char and varchar2?

When stored in a database, varchar2 uses only the allocated space. E.g. if you have a varchar2(1999) and put 50 bytes in the table, it will use 52 bytes.

But when stored in a database, char always uses the maximum length and is blank-padded. E.g. if you have char(1999) and put 50 bytes in the table, it will consume 2000 bytes.

What is the difference between IN and EXISTS?

IN:

• Works on List result set
• Doesn’t work on subqueries resulting in Virtual tables with multiple columns
• Compares every value in the result list
• Performance is comparatively SLOW for larger resultset of subquery

EXISTS:

• Works on Virtual tables
• Is used with co-related queries
• Exits comparison when match is found
• Performance is comparatively FAST for larger resultset of subquery

How can you use a CTE to return the fifth highest (or Nth highest) salary from a table?

Declare @N int
set @N = 5;
WITH CTE AS
(
    SELECT Name, Salary, EmpID, RN = ROW_NUMBER() 
	OVER (ORDER BY Salary DESC)
    FROM Employee
)
SELECT Name, Salary, EmpID
FROM CTE
WHERE RN = @N