After checking the monitor tab in the Azure Synapse Studio environment, you realize that you can improve the performance of the run.
Now, you decide to use bucketed tables to improve the performance.
Which of the following are the recommended practices to consider while using bucketed tables? (Select all options that are applicable)
Click on the arrows to vote for the correct answer
A. B. C. D. E. F.Correct Answers: A, D, E and F
While using bucketed tables, you need to deal with Merge join.
A correctly pre-sorted and pre-partitioned dataset will skip the costly sort phase from a SortMerge join.
The order of joins does matter, especially in more complex queries.
Start with the most selective joins.
You should also consider moving the joins that increase the number of rows after aggregations, whenever possible.
Option A is correct.
While using bucketed tables, you should avoid the use of SortMerge join whenever possible.
Option B is incorrect.
You should avoid using expensive SortMerge join while using bucketed tables.
Option C is incorrect.
Instead of prefering the use of SortMerge join as much as you can, you should start with the most selective joins.
Option D is correct.
You should start with the most selective joins to improve the performance.
Option E is correct.
To increase the performance using bucketed tables, you should move joins that increase the number of rows after aggregations whenever possible.
Option F is correct.
The order of various types of joins matters when it comes to the resource consumption.
To know more about Apache Spark Performance, please visit the below-given performance:
When using bucketed tables in Azure Synapse Studio environment to improve performance, there are several recommended practices to consider. Let's go through each option:
A. Avoid the use of SortMerge join whenever possible: SortMerge join is a type of join operation that can be resource-intensive and time-consuming. When possible, it is best to avoid using this type of join, as it can negatively impact performance.
B. Prefer the use of SortMerge join as much as you can: This option contradicts with option A. As discussed earlier, SortMerge join can be resource-intensive and time-consuming, so it's not recommended to use it as much as you can.
C. Never consider the most selective joins: This option is incorrect. Selective joins are the ones that reduce the number of rows that need to be processed, so they can improve performance. Therefore, it is recommended to consider the most selective joins.
D. Start with the most selective joins: This option is correct. When using bucketed tables, it is recommended to start with the most selective joins as they can significantly reduce the amount of data that needs to be processed. This can result in faster query performance and reduced resource consumption.
E. Move joins that increase the number of rows after aggregations whenever possible: This option is correct. When using bucketed tables, it is recommended to move joins that increase the number of rows after aggregations whenever possible. This is because aggregations can significantly reduce the number of rows that need to be processed, so moving the join after the aggregation can improve performance.
F. The order of various types of joins matters when it comes to resource consumption: This option is correct. The order of various types of joins can significantly impact resource consumption. For example, a join operation that reduces the number of rows before another join operation can reduce the amount of data that needs to be processed in the subsequent join operation. Therefore, it is recommended to carefully consider the order of various types of joins to optimize performance and reduce resource consumption.
In summary, the recommended practices to consider when using bucketed tables in Azure Synapse Studio environment are to avoid using SortMerge join whenever possible, start with the most selective joins, move joins that increase the number of rows after aggregations whenever possible, and carefully consider the order of various types of joins.