Why PostgreSQL advanced features matter - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select all columns from the table named employees.

PostgreSQL

SELECT [1] FROM employees;

Drag options to blanks, or click blank then click option'

A*

Ball

Ceverything

Dcolumns

Attempts:

3 left

💡 Hint

Common Mistakes

Using words like 'all' or 'columns' instead of the symbol *

Leaving the SELECT statement incomplete

The asterisk (*) selects all columns from the table.

2fill in blank

medium

Complete the code to filter rows where the salary is greater than 50000.

PostgreSQL

SELECT * FROM employees WHERE salary [1] 50000;

Drag options to blanks, or click blank then click option'

A=

B>

C<

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' which selects only salaries exactly 50000

Using '<' which selects salaries less than 50000

The greater than symbol (>) filters salaries above 50000.

3fill in blank

hard

Fix the error in the query to count the number of employees.

PostgreSQL

SELECT COUNT([1]) FROM employees;

Drag options to blanks, or click blank then click option'

Aemployee_id

Bsalary

Cname

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Counting a specific column which may miss rows with NULL values

Leaving COUNT empty or with invalid syntax

Using COUNT(*) counts all rows regardless of column values.

4fill in blank

hard

Fill both blanks to create a dictionary of employee names and their salaries where salary is above 60000.

PostgreSQL

SELECT jsonb_object_agg([1], [2]) FROM employees WHERE salary > 60000;

Drag options to blanks, or click blank then click option'

Aname

Bsalary

Cemployee_id

Ddepartment

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping keys and values

Using columns not relevant to the dictionary

jsonb_object_agg(key, value) creates a JSON object with keys and values. Here, names are keys and salaries are values.

5fill in blank

hard

Fill all three blanks to create a JSON object with employee names as keys, their salaries as values, but only include those in the 'Sales' department.

PostgreSQL

SELECT jsonb_object_agg([1], [2]) FROM employees WHERE department = '[3]';

Drag options to blanks, or click blank then click option'

Aname

Bsalary

CSales

DMarketing

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong department name

Swapping keys and values in jsonb_object_agg

This query creates a JSON object mapping employee names to salaries, filtered to only those in the Sales department.

Practice

1. Which of the following is a key advantage of PostgreSQL's advanced features?

easy

A. They allow storing complex data types like JSON and arrays.

B. They make the database only work with simple text data.

C. They remove the need for any indexes.

D. They prevent any data from being updated.

Solution

1. Step 1: Understand PostgreSQL advanced features

   PostgreSQL supports complex data types such as JSON, arrays, and custom types, which allow flexible data storage.

2. Step 2: Compare options with this knowledge

   They allow storing complex data types like JSON and arrays. correctly states this advantage, while others describe incorrect or impossible behaviors.

3. Final Answer:

   They allow storing complex data types like JSON and arrays. -> Option A

4. Quick Check:

   Advanced features = complex data support [OK]

Hint: Remember: PostgreSQL handles complex data types easily [OK]

Common Mistakes:

• Thinking PostgreSQL only supports simple text
• Believing indexes are not needed
• Assuming data cannot be updated

2. Which of the following is the correct syntax to create a table with a JSONB column in PostgreSQL?

easy

A. CREATE TABLE data (info JSONB);

B. CREATE TABLE data (info JSON);

C. CREATE TABLE data (info TEXT[]);

D. CREATE TABLE data (info BLOB);

Solution

1. Step 1: Recall JSONB column syntax in PostgreSQL

   PostgreSQL uses JSONB as a binary JSON storage type, declared as JSONB in table definitions.

2. Step 2: Check each option

   CREATE TABLE data (info JSONB); uses JSONB correctly. CREATE TABLE data (info JSON); uses JSON (also valid but not JSONB). CREATE TABLE data (info TEXT[]); uses TEXT array, not JSONB. CREATE TABLE data (info BLOB); uses BLOB which is not PostgreSQL syntax.

3. Final Answer:

   CREATE TABLE data (info JSONB); -> Option A

4. Quick Check:

   JSONB column syntax = CREATE TABLE ... (info JSONB) [OK]

Hint: Use JSONB for efficient JSON storage in PostgreSQL [OK]

Common Mistakes:

• Confusing JSON and JSONB types
• Using TEXT[] instead of JSONB
• Using BLOB which is not PostgreSQL type

3. Given the table users(id SERIAL PRIMARY KEY, data JSONB) with data:
{"name": "Alice", "age": 30} in the data column, what does this query return?

SELECT data->>'name' FROM users WHERE data->>'age' = '30';

medium

A. Returns all data rows regardless of age.

B. Returns the age 30 as a number.

C. Returns the name 'Alice' for users aged 30.

D. Returns an error due to wrong JSON syntax.

Solution

1. Step 1: Understand JSONB operators in the query

   The operator ->> extracts JSON object field as text. The WHERE clause filters rows where age equals '30' as text.

2. Step 2: Analyze query result

   The SELECT returns the 'name' field as text for rows matching age '30'. So it returns 'Alice'.

3. Final Answer:

   Returns the name 'Alice' for users aged 30. -> Option C

4. Quick Check:

   data->>'name' with age filter = 'Alice' [OK]

Hint: ->> extracts text from JSONB fields [OK]

Common Mistakes:

• Confusing -> and ->> operators
• Expecting numeric type instead of text
• Ignoring WHERE filter on JSONB field

4. Identify the error in this PostgreSQL query using JSONB:

SELECT data->'name' FROM users WHERE data->>'age' = 30;

medium

A. The JSONB column must be cast to text before querying.

B. The operator -> cannot be used in SELECT.

C. The query is correct and will run without errors.

D. The comparison value 30 should be a string '30'.

Solution

1. Step 1: Check WHERE clause comparison

   data->>'age' extracts text, so comparing to number 30 causes type mismatch.

2. Step 2: Correct the comparison

   Comparison should be to string '30' to match extracted text value.

3. Final Answer:

   The comparison value 30 should be a string '30'. -> Option D

4. Quick Check:

   Compare JSON text with string '30' [OK]

Hint: Compare JSON text fields with strings, not numbers [OK]

Common Mistakes:

• Using numeric 30 instead of string '30'
• Thinking -> operator is invalid in SELECT
• Trying to cast JSONB unnecessarily

5. You want to store user preferences as key-value pairs and query them efficiently. Which PostgreSQL feature best supports this need?

hard

A. Storing preferences in separate tables without indexes.

B. Using JSONB columns with GIN indexes.

C. Using arrays of text without indexes.

D. Storing preferences as plain text in VARCHAR columns.

Solution

1. Step 1: Identify data storage needs

   User preferences as key-value pairs fit well into JSONB columns for flexible schema.

2. Step 2: Consider query efficiency

   GIN indexes on JSONB columns speed up key-value queries efficiently.

3. Step 3: Evaluate other options

   Plain text or arrays lack flexibility and indexing; separate tables without indexes are slow.

4. Final Answer:

   Using JSONB columns with GIN indexes. -> Option B

5. Quick Check:

   JSONB + GIN index = fast key-value queries [OK]

Hint: Use JSONB with GIN index for fast key-value queries [OK]

Common Mistakes:

• Ignoring indexing for JSONB queries
• Using plain text which is inflexible
• Not using JSONB for key-value data