As you review your incident ticket volume, you realize that there is an upward trend observed in the incidents regarding Azure Cognitive Search queries.
Following the next practices, you can identify and address the performance concerns.
Review the answer choices below and choose the options that you will prefer to improve Cognitive Search queries performance.
Keep the operational costs low.
(select two answer choices)
Click on the arrows to vote for the correct answer
A. B. C. D. E.Correct Answers: A and D.
Option A is correct because smaller indexes would bring in faster query results.
As data grows, the index becomes large, thereby slowing the search queries.
Option B is incorrect because selecting fewer properties or only the properties that you need would improve query performance.
Option C is incorrect because adding additional disk would not improve query performance.
It would also increase your operational cost.
Option D is correct because complex data types require additional storage and hence increases your operational cost.
However, if there is an opportunity to map a complex data type to a simpler type field, you can save additional storage and resource cost while maintaining the search query performance.
Option E is incorrect because upgrading to standard S2 storage and adding additional search units will increase the operational costs.
Reference:
To learn more about performance tips of cognitive search index, use the link given below:
When addressing performance concerns in Azure Cognitive Search, it is important to consider both the effectiveness and efficiency of the search service. Here are some options that can help improve the Cognitive Search queries performance while keeping the operational costs low:
A. Reduce the content to maintain smaller indexes: One way to improve query performance is to reduce the content being indexed, thereby keeping the index size small. This can be achieved by limiting the number of fields being indexed or by removing unnecessary data.
B. Select all properties of the fields while creating a search index: It is important to select only the necessary properties when creating a search index to avoid indexing unnecessary data. Selecting all the properties of a field can lead to an increase in the index size and a decrease in query performance.
C. Provide additional storage by adding disks: Adding additional storage can help improve the performance of the search service. However, this option can increase the operational costs, so it should be used judiciously.
D. Mapping a complex data type to a simpler type field: When mapping data to an index field, it is important to use the simplest data type possible. Mapping complex data types to a field can lead to a decrease in query performance.
E. Upgrade to standard S2 storage and add additional search units: Upgrading to a higher tier of storage and adding additional search units can help improve query performance, but this option can increase operational costs.
In summary, to improve the performance of Azure Cognitive Search queries while keeping operational costs low, it is important to reduce the content being indexed, select only necessary properties when creating a search index, map data to the simplest data type possible, and use additional storage and search units judiciously.