Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 55 discussion

https://docs.aws.amazon.com/redshift/latest/dg/t_Distributing_data.html Option B, changing the distribution key, is the most effective solution to balance the load more evenly across all five compute nodes. Selecting an appropriate distribution key that aligns with the query patterns and data characteristics can result in a more uniform distribution of data and workloads, thus reducing the likelihood of one node being overutilized while others are underutilized.

In a Redshift cluster with key distribution, data is distributed across compute nodes based on the values of the distribution key. An uneven distribution can lead to skewed workloads on specific nodes. By choosing the table column with the largest dimension (most distinct values) as the distribution key, you ensure a more even spread of data across all nodes. This balances the processing load on each node when queries access that column.

The correct solution is B. Change the distribution key to the table column that has the largest dimension. This will help to distribute the data more evenly across the nodes, reducing the load on the heavily utilized node.

Gemini result: Understanding the Problem: The scenario describes a Redshift cluster with uneven load distribution. This indicates potential issues with either the distribution style or the sort key. Key Distribution: The problem states that the cluster uses key distribution, meaning a specific column is designated as the distribution key. Data rows with matching distribution key values are placed on the same node. Sort Key: A sort key determines the order in which data is physically stored within a table's blocks on a node. A well-chosen sort key can significantly optimize query performance, especially when queries often filter by that column.

B. With "Key distribution". The rows are distributed according to the values in one column. The leader node places matching values on the same node slice. If you distribute a pair of tables on the joining keys, the leader node collocates the rows on the slices according to the values in the joining columns. This way, matching values from the common columns are physically stored together. https://docs.aws.amazon.com/redshift/latest/dg/c_choosing_dist_sort.html