Which of these components breaks pipeline parallelism?

To answer this question, we need to understand what pipeline parallelism is and how each component affects it:

Pipeline parallelism is a technique used in parallel computing where a task is divided into multiple stages, and each stage is executed concurrently. Each stage performs a specific operation on the data and passes it to the next stage. This allows for efficient utilization of resources and faster execution.

Now, let's analyze each option:

Option A) Sort - This option breaks pipeline parallelism. Sorting requires the entire dataset to be available before it can start the sorting process. This means that the sort stage cannot start until all previous stages have completed, causing a break in the pipeline parallelism.

Option B) Reformat - Reformatting the data does not break pipeline parallelism. It can be done concurrently with other stages, as it typically involves transforming the data in a way that does not depend on the order or content of other data elements.

Option C) Partition by key - Partitioning the data by key does not break pipeline parallelism. It can be done concurrently with other stages, as it involves dividing the data into multiple partitions based on a specified key.

Option D) Filter by expression - Filtering the data by expression does not break pipeline parallelism. It can be done concurrently with other stages, as it involves selecting or excluding data elements based on a specified condition.

Based on the analysis above, the correct answer is:

A) Sort - This option breaks pipeline parallelism because sorting requires the entire dataset to be available before it can start the sorting process, causing a break in the pipeline parallelism.

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