Multiple choice technology

What is the lowest cost partitioning method for parallel stage to sequential stage?

  1. Sort Merge

  2. Round Robin

  3. Entire

  4. Ordered
Reveal answer Fill a bubble to check yourself
B Correct answer
Explanation

Round Robin has the lowest cost when moving from parallel to sequential because it simply distributes rows sequentially without key calculations. Sort Merge requires sorting (expensive), Entire sends everything to one partition causing bottleneck, and Ordered requires key-based distribution.

AI explanation

To answer this question, we need to understand the concept of partitioning methods for parallel and sequential stages in data processing.

In parallel processing, data is divided into partitions or subsets, which are processed simultaneously by multiple processing units. After the parallel processing stage, the data is combined or merged for further processing in the sequential stage.

The lowest cost partitioning method is the one that minimizes the overhead and resources required for data partitioning and merging. Let's go through each option to understand why it is correct or incorrect:

Option A) Sort Merge - This option is incorrect because the sort merge partitioning method involves sorting the data before partitioning, which can be computationally expensive and may not be the lowest cost option.

Option B) Round Robin - This option is correct because the round robin partitioning method evenly distributes the data across multiple processing units without the need for sorting or any specific order. It is a simple and efficient method that minimizes overhead and is often used for load balancing in parallel processing.

Option C) Entire - This option is incorrect because the entire partitioning method involves processing the entire dataset in each processing unit, which eliminates the benefits of parallel processing and is not suitable for partitioning.

Option D) Ordered - This option is incorrect because the ordered partitioning method involves processing the data in a specific order, which may introduce dependencies and limit the parallel processing capability.

The correct answer is Option B) Round Robin. This option is correct because it evenly distributes the data across multiple processing units without the need for sorting or any specific order, making it the lowest cost partitioning method for parallel to sequential stages.

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