Question

Which of these characteristics of BigQuery workers (slots) is true?

Workers only execute a single stage of work, if there are not enough workers to do it all at once the query will fail


* Workers consume data in parallel


* Workers communicate data and query progress between each other by shuffling


* The amount of workers issued for a query is dynamic based on the query needs


* Workers prefer to have all of the data values needed for an operation stored locally on their memory for fast processing


* Workers execute as many stages of work (shuffling) needed to process all of the data in the query

Answer 1

BigQuery workers, or slots, consume data in parallel, communicate via shuffling, and the number of workers for a query is dynamic. They prefer local data for fast processing and can execute multiple stages of work as needed.

Step-by-step explanation:

The characteristics of BigQuery workers, also known as slots, include the following:

• Workers consume data in parallel, which means they process data simultaneously to speed up query execution times.
• Workers communicate data and query progress between each other by shuffling. Shuffling is the process of redistributing data so that all the necessary information for a particular stage of a query is available to the worker performing that stage.
• The amount of workers issued for a query is dynamic and adjusts based on the needs of the query, which ensures efficient resource utilization.
• Workers do prefer to have all of the data values needed for an operation stored locally in their memory, as it allows for fast processing.
• Workers are capable of executing as many stages of work (shuffling) as needed to process all of the data in the query, ensuring that the entire operation is completed.

To address the listed characteristics, it's not true that workers will only execute a single stage of work or that the query will fail if there aren't enough workers to do all work at once; instead, BigQuery provisions workers dynamically.