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Actor & Director Collaboration | Advanced SQL Interview Question | Data Engineer Interview Question

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Video 331: This is the 22nd video of the SQL Interview Question series.
00:00 - Introduction to dataset and Question
02:40 - Approach 1: Using Aggregate Function
04:10 - Approach 2: Using Windows Function
06:15 - Conclusion
We are given a ActorDirector table which has a sequence of Actors and Directors who collaborate for a movie.
The seq column is the unique identifier for this table.
We are asked to write a solution to find all the pairs of actor_id and director_id, where the actor has cooperated with the director at least three times.
In this video, I delve into the problem of identifying actor-director pairs that have collaborated at least three times. Using the ActorDirector table, I explore two distinct SQL approaches to solve this problem efficiently.
*** Approach 1: Using Aggregation Method ***
The first approach leverages the power of aggregation to group data and filter results based on the count of collaborations. This method is straightforward and effective for summarizing data and applying conditional logic.
*** Approach 2: Using Window Functions ***
The second approach employs window functions to dynamically calculate the count of collaborations across the dataset. This method provides a flexible and powerful way to analyze data and extract meaningful insights.
For a comprehensive understanding of these SQL methodologies and their application, please refer to this explanatory video.
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00:00 - Introduction to dataset and Question
02:40 - Approach 1: Using Aggregate Function
04:10 - Approach 2: Using Windows Function
06:15 - Conclusion
We are given a ActorDirector table which has a sequence of Actors and Directors who collaborate for a movie.
The seq column is the unique identifier for this table.
We are asked to write a solution to find all the pairs of actor_id and director_id, where the actor has cooperated with the director at least three times.
In this video, I delve into the problem of identifying actor-director pairs that have collaborated at least three times. Using the ActorDirector table, I explore two distinct SQL approaches to solve this problem efficiently.
*** Approach 1: Using Aggregation Method ***
The first approach leverages the power of aggregation to group data and filter results based on the count of collaborations. This method is straightforward and effective for summarizing data and applying conditional logic.
*** Approach 2: Using Window Functions ***
The second approach employs window functions to dynamically calculate the count of collaborations across the dataset. This method provides a flexible and powerful way to analyze data and extract meaningful insights.
For a comprehensive understanding of these SQL methodologies and their application, please refer to this explanatory video.
Follow me on,
#sql #dataengineers #tablejoins #ceil #floor #bucket #meta #google #facebook #apple #paypal #netflix #amazon #deinterview #sqlinterview #interviewquestions #leetcode #faang #maanga #mysql #oracle #dbms #query #sqlserver #mysql #coderpad #aggregates #aggregation #nonaggregation #database #placementpreparation #lead #lag #windowsfunction #nullcheck #coalesce #sqlperformance #ifnull #case #lead #lag #windowsfunction #tamil #tamilpython #tamilinterview #tamilinterviewlatest #tamilinterviewquestions #sqlintamil
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