A company has been using Amazon Redshift and loaded a number of tables in the cluster.
After a series of operations over a couple of months, the performance of the queries seems to be deteriorating.
Which of the following is an ideal approach to improve the performance of the queries?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer - A.
The AWS Documentation mentions the following.
Amazon Redshift does not automatically reclaim and reuse space that is freed when you delete rows and update rows.
To perform an update, Amazon Redshift deletes the original row and appends the updated row, so every update is effectively a delete followed by an insert.
When you perform a delete, the rows are marked for deletion, but not removed.
The query processor needs to scan the deleted rows as well as undeleted rows, so too many deleted rows can cost unnecessary processing.
You should vacuum following a significant number of deletes or updates to reclaim space and improve query performance.
Option B is incorrect since you will first need to get the latest data and then perform the COPY command.
And why do this when you can use the VACCUM command to improve performance.
Option C is incorrect since this is done when the table is created.
Option D is incorrect since this is do with the size and not the performance of queries.
For more information on reclaiming storage in Redshift, please refer to the below URL.
https://docs.aws.amazon.com/redshift/latest/dg/t_Reclaiming_storage_space202.htmlThe ideal approach to improve the performance of queries in Amazon Redshift after a series of operations over a couple of months is to carry out the VACUUM command.
Explanation: Amazon Redshift is a data warehousing solution that is designed to manage petabyte-scale data warehouses. Amazon Redshift automatically distributes data and query load across all nodes in a cluster, providing fast query performance for data analytics. However, as more and more data is loaded into the cluster, and as queries run over time, query performance can begin to degrade.
The VACUUM command is used to reclaim space that is occupied by rows that have been deleted or updated. When data is deleted or updated, Amazon Redshift does not immediately reclaim the space used by the deleted or updated rows. Instead, the space is marked as available for future use. This approach allows for faster data modification operations, but it can result in wasted disk space and degraded query performance over time. Running the VACUUM command periodically helps to reclaim the wasted space, which can improve query performance.
Therefore, option A - Carry out the VACUUM command is the correct answer.
Option B - Carry out the COPY command on the table again, is not an ideal approach to improve query performance in this scenario. The COPY command is used to load data into a Redshift table from a data source. Re-loading the data will not necessarily address the issue of degraded query performance.
Option C - Enable compression on the columns, can help to reduce the amount of storage space used by the table. However, enabling compression will not necessarily improve query performance, and it may even degrade query performance if the compression algorithm used is not optimal for the data in the table.
Option D - Disable compression on the columns, will not improve query performance. Disabling compression may actually increase the amount of storage space used by the table, which can further degrade query performance.