Scenarios

36 of 36 scenarios

Equal SalaryQuery to get workers who are getting equal salary

Status Change DatesGet dates when order status changes

Sensor Value DiffCalculate difference between consecutive sensor values

Unique Customer AddressesList unique customers with their distinct addresses

Filter & PartitionRead, merge, filter invalid emails and write partitioned

Employee DesignationAssign Manager/Employee designation based on salary

Top Quantity Per YearGet product with highest quantity sold per year

Cricket Match PairsGenerate all possible match combinations between teams

Most Rank-1 ParticipantFind participant who has rank=1 most number of times

Min Commission MonthGet month with minimum commission per employee

Salary GradeGrade employees A/B/C based on salary ranges

Mask PII DataMask email and mobile number for data privacy

Department CountCount number of employees per department

Total MarksCalculate total marks across all subjects

Extend vs Append ListDifference between extend and append in Python/Scala

Remove DuplicatesRemove duplicate records based on name and salary

Merge DataFramesMerge two employee dataframes with different columns

Reverse Each WordReverse each word in a string individually

Flatten Complex DFFlatten struct and array nested columns

Generate Complex DFGenerate complex nested dataframe from flat structure

Round Trip DistanceCalculate total round trip distance between cities

Cumulative SumRunning total of price partitioned by product

Customers Bought AllFind customers who purchased every product

User Page JourneyCollect ordered list of pages visited per user

Handle Bad RecordsRead CSV and drop corrupt/malformed records on read

Source vs Target DiffCompare two tables — mismatch, new in source/target

Salary IncrementCalculate year-on-year salary increment per employee

Grandparent MappingFind grandparent of each child via self join

Symmetric DifferenceFind values in either table but not both (XOR)

2nd Highest Salary/DeptSecond highest salary per department with dept name

Unpivot Columns to RowsConvert multiple columns into rows via explode

Star Rating DisplayJoin food and ratings, display stars as repeated *

Max Discount ToursFamily that can access most discount tour countries

Age Group CountCount customers grouped into age buckets

IBM: Null HandlingIBM question — null count, fill with mean, filter age

Products Per Sell DateCollect distinct products and count per sell date

Scenarios

36 of 36 scenarios

Equal SalaryQuery to get workers who are getting equal salary

Status Change DatesGet dates when order status changes

Sensor Value DiffCalculate difference between consecutive sensor values

Unique Customer AddressesList unique customers with their distinct addresses

Filter & PartitionRead, merge, filter invalid emails and write partitioned

Employee DesignationAssign Manager/Employee designation based on salary

Top Quantity Per YearGet product with highest quantity sold per year

Cricket Match PairsGenerate all possible match combinations between teams

Most Rank-1 ParticipantFind participant who has rank=1 most number of times

Min Commission MonthGet month with minimum commission per employee

Salary GradeGrade employees A/B/C based on salary ranges

Mask PII DataMask email and mobile number for data privacy

Department CountCount number of employees per department

Total MarksCalculate total marks across all subjects

Extend vs Append ListDifference between extend and append in Python/Scala

Remove DuplicatesRemove duplicate records based on name and salary

Merge DataFramesMerge two employee dataframes with different columns

Reverse Each WordReverse each word in a string individually

Flatten Complex DFFlatten struct and array nested columns

Generate Complex DFGenerate complex nested dataframe from flat structure

Round Trip DistanceCalculate total round trip distance between cities

Cumulative SumRunning total of price partitioned by product

Customers Bought AllFind customers who purchased every product

User Page JourneyCollect ordered list of pages visited per user

Handle Bad RecordsRead CSV and drop corrupt/malformed records on read

Source vs Target DiffCompare two tables — mismatch, new in source/target

Salary IncrementCalculate year-on-year salary increment per employee

Grandparent MappingFind grandparent of each child via self join

Symmetric DifferenceFind values in either table but not both (XOR)

2nd Highest Salary/DeptSecond highest salary per department with dept name

Unpivot Columns to RowsConvert multiple columns into rows via explode

Star Rating DisplayJoin food and ratings, display stars as repeated *

Max Discount ToursFamily that can access most discount tour countries

Age Group CountCount customers grouped into age buckets

IBM: Null HandlingIBM question — null count, fill with mean, filter age

Products Per Sell DateCollect distinct products and count per sell date

Home/Scenario 25

#25

Handle Bad Records

Read CSV and drop corrupt/malformed records on read

Solution Code

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