PySpark Certification Practice Test 09

Complete the Logic / Best Coding Solution

Question 1 of 20

📋 Multiple Choice

Question 161

A retail company wants the latest customer record. Input: customer_id | city | update_date ------------|----------|------------ 1 | Bangalore| 2024-01-01 1 | Chennai | 2024-02-01 2 | Mumbai | 2024-01-15 Which window function is the BEST choice?

A. min()

B. avg()

✓

C. row_number()

D. count()

Answer

✅ C. row_number()

Answered: 0 / 20

PySpark Certification Practice Test 09

Complete the Logic / Best Coding Solution

Insightful Saga — Modern Data Engineering Certification Preparation

Question 161

A. min()

B. avg()

C. row_number()

D. count()

Answer: ✅ C. row_number()

Question 162

A banking company wants the Top 5 customers by balance per branch. Which approach is most suitable?

A. Window + row_number()

B. collect()

C. distinct()

D. union()

Answer: ✅ A. Window + row_number()

Question 163

A telecom company wants: Current Month Usage Previous Month Usage Difference Which function should be used?

A. lag()

B. lead()

C. sum()

D. count()

Answer: ✅ A. lag()

Question 164

Find duplicate records based on: customer_id order_id Best solution?

A. collect()

B. cache()

C. coalesce()

D. groupBy().count()

Answer: ✅ D. groupBy().count()

Question 165

A dataset contains: salary Requirement: Find the 3rd highest salary. Best window function?

A. lead()

B. dense_rank()

C. sum()

D. lag()

Answer: ✅ B. dense_rank()

Question 166

Input: customer_id transaction_date amount Requirement: Running Total. Best approach?

A. groupBy()

B. distinct()

C. Window + sum()

D. collect()

Answer: ✅ C. Window + sum()

Question 167

A healthcare company receives late-arriving records. Requirement: Keep latest version per patient. Most suitable pattern?

A. row_number + desc timestamp

B. count()

C. union()

D. min()

Answer: ✅ A

Question 168

Input: employee_id salary department Requirement: Highest-paid employee in each department. Best solution?

A. collect()

B. row_number partitioned by department

C. full join

D. cache()

Answer: ✅ B

Question 169

A table contains: customer_id event_date Requirement: Find consecutive events. Primary functions?

A. avg()

B. sum()

C. union()

D. lag() + datediff()

Answer: ✅ D

Question 170

Requirement: Remove duplicates but keep the latest timestamp row. Most suitable logic?

A. distinct()

B. count()

C. row_number over timestamp desc

D. collect()

Answer: ✅ C

Question 171

Input: sales_date sales_amount Requirement: 7-Day Moving Average. Best solution?

A. left join

B. distinct()

C. repartition()

D. Window Between

Answer: ✅ D

Question 172

A logistics company wants: Current Shipment Cost Previous Shipment Cost Cost Difference Which pattern should be used?

A. count()

B. dense_rank()

C. cache()

D. lag()

Answer: ✅ D

Question 173

Requirement: Identify customers who placed orders on 3 consecutive days. Main concepts?

A. union

B. broadcast

C. cache

D. lag + datediff + window

Answer: ✅ D

Question 174

A retail company wants: Top Product per Category Best coding approach?

A. collect

B. row_number partitionBy(category)

C. repartition(1)

D. distinct

Answer: ✅ B

Question 175

Requirement: Find customers whose current order amount is greater than previous order amount. Best function?

A. lag()

B. lead()

C. rank()

D. avg()

Answer: ✅ A

Question 176

A bank wants: Monthly Balance Trend with month-over-month comparison. Which function is most appropriate?

A. collect()

B. union()

C. broadcast()

D. lag()

Answer: ✅ D

Question 177

Input: transaction_date amount Requirement: Cumulative yearly revenue. Best solution?

A. collect()

B. Window + sum()

C. distinct()

D. min()

Answer: ✅ B

Question 178

A manufacturing company wants anomalies where: today_temperature > previous_temperature * 2 Best window function?

A. lag()

B. count()

C. union()

D. cache()

Answer: ✅ A

Question 179

Find customers with no orders. Best join type?

A. Right Join

B. Left Anti Join

C. Inner Join

D. Cross Join

Answer: ✅ B

Question 180

A senior PySpark interviewer asks: "Which PySpark concepts are most important for advanced analytics problems?"

A. print()

B. Window Functions

C. show()

D. limit()

Answer: ✅ B. Window Functions