A Data Engineer enables a result cache at the session level with the following command:ALTER SESSION SET USE_CACHED_RESULT = TRUE;The Engineer then runs the following SELECT query twice without delay:SELECT *FROM SNOWFLAKE_SAMPLE_DATA.TPCH_SF1.CUSTOMERSAMPLE(10) SEED (99);The underlying table does not change between executions.What are the results of both runs?
Answer(s): B
A company built a sales reporting system with Python, connecting to Snowflake using the Python Connector. Based on the user's selections, the system generates the SQL queries needed to fetch the data for the report. First it gets the customers that meet the given query parameters (on average 1000 customer records for each report run), and then it loops the customer records sequentially. Inside that loop it runs the generated SQL clause for the current customer to get the detailed data for that customer number from the sales data table.When the Data Engineer tested the individual SQL clauses, they were fast enough (1 second to get the customers, 0.5 second to get the sales data for one customer), but the total runtime of the report is too long.How can this situation be improved?
Answer(s): D
A Data Engineer is building a pipeline to transform a 1 TB table by joining it with supplemental tables. The Engineer is applying filters and several aggregations leveraging Common Table Expressions (CTEs) using a size Medium virtual warehouse in a single query in Snowflake.After checking the Query Profile, what is the recommended approach to MAXIMIZE performance of this query if the Profile shows data spillage?
A Data Engineer needs to know the details regarding the micro-partition layout for a table named Invoice using a built-in function.Which query will provide this information?
Answer(s): A
What action could a Data Engineer take to increase the query performance of an external table?
Answer(s): C
External tables in Snowflake store metadata about files in external cloud storage (e.g., Amazon S3, Azure Blob Storage, Google Cloud Storage) rather than the data itself. Since external tables do not benefit from Snowflake's micro-partitioning or clustering, query performance can be improved by a materialized view (MV) precomputes and stores query results, reducing the need to scan external storage repeatedly.
Post your Comments and Discuss Snowflake SnowPro Advanced Data Engineer exam prep with other Community members:
Our website is free, but we have to fight against AI bots and content theft. We're sorry for the inconvenience caused by these security measures. You can access the rest of the SnowPro Advanced Data Engineer content, but please register or login to continue.