In the query profiler view for a query, which components represent areas that can be used to help optimize query performance? (Choose two.)
In the query profiler view for a query, which components represent areas that can be used to help optimize query performance? (Choose two.)
Bytes scanned indicates the amount of data read by the query. Minimizing the number of bytes scanned can significantly improve query performance by reducing the volume of data processed. The number of partitions scanned represents the partitions accessed during query execution. Optimizing the number of partitions scanned helps improve performance by limiting the amount of partition data processed. These two components are key areas to focus on when optimizing query performance as they directly affect the query's efficiency and processing time.
I think that the right answer si C,D. Because the number of bytes scanned has no values if don't know if your query has or not make a prune, reducing the number of partition tha has scanned. I have a good query if my filters reduce the number of (micro) partiotion that the query must access to get the data.
A. Bytes scanned represents the amount of data scanned by the query. By minimizing the number of bytes scanned, query performance can be improved. C. Number of partitions scanned represents the number of partitions read during query execution. By minimizing the number of partitions scanned, query performance can be improved. B, D, and E are incorrect statements. Bytes sent over the network, percentage scanned from cache, and external bytes scanned may provide useful information for monitoring or troubleshooting, but they are not directly related to optimizing query performance.
I correct myself the right answer is A, C, bracause i have the cache only in next executions of the query
Bytes scanned — the number of bytes scanned so far. Percentage scanned from cache — the percentage of data scanned from the local disk cache.
Common Query Problems Identified by Query Profile: - https://docs.snowflake.com/en/user-guide/ui-query-profile.html#queries-too-large-to-fit-in-memory - https://docs.snowflake.com/en/user-guide/ui-query-profile.html#inefficient-pruning
QUERY RESULT CACHE IS NOT HELPFULL
AC are correct
The answer is A,D
https://docs.snowflake.com/en/user-guide/ui-query-profile.html
IO section: https://docs.snowflake.com/en/user-guide/ui-query-profile.html#when-to-use-query-profile
pruning and memory consumption are the two main factors
Number of partitions being scanned (in relation to the total number) -> Pruning Cache usage can significantly boost the performance
bytes scanned, partition scanned
CORRECT
reference to this question https://community.snowflake.com/s/question/0D7Do000000cglDKAQ/detail
A. Bytes scanned: This indicates the amount of data scanned from the tables or files involved in the query. By minimizing the number of bytes scanned, you can optimize query performance by reducing the amount of data processed. C. Number of partitions scanned: This represents the number of partitions accessed during the query execution. Optimizing the number of partitions scanned can improve query performance, as accessing fewer partitions typically requires less processing time. So, the correct options are A. Bytes scanned and C. Number of partitions scanned
AC is the answer
Explanation: A. Bytes scanned Represents the total amount of data scanned during query execution. High values indicate that the query is scanning a large dataset, which can impact performance. Optimization: Reduce bytes scanned by applying filters, leveraging clustering, or optimizing table design. C. Number of partitions scanned Represents the number of partitions read during query execution. Scanning too many partitions can slow down query performance. Optimization: Use clustering, partition pruning, or query predicates to minimize the number of partitions scanned.
AC for me, because bytes scanned and number of partitions scanned referenced in the doc: https://docs.snowflake.com/en/user-guide/ui-query-profile.html#queries-too-large-to-fit-in-memory
https://docs.snowflake.com/en/user-guide/ui-query-profile
I would go for AC. The query should not rely on cache.
CD is correct
Should be correct
C and D are correct
D & E D: Inefficient Pruning https://docs.snowflake.com/en/user-guide/ui-query-profile.html#inefficient-pruning E: Queries Too Large to Fit in Memory: https://docs.snowflake.com/en/user-guide/ui-query-profile.html#queries-too-large-to-fit-in-memory
A and C should be the correct answers
The components in the Snowflake query profiler that help optimize query performance are Bytes scanned (A) and Number of partitions scanned (C). Bytes scanned (A) directly impacts performance, as reducing the volume of data processed through efficient filtering or clustering improves speed and cost. Number of partitions scanned (C) reflects partition pruning efficiency. Scanning fewer partitions (via proper clustering or filters) minimizes unnecessary data access. These metrics are critical for identifying bottlenecks in data retrieval and optimizing query execution.