Snowflake Exam ARA-C01 Topic 2 Question 43 Discussion

Actual exam question for Snowflake's ARA-C01 exam

Question #: 43
Topic #: 2

A company has built a data pipeline using Snowpipe to ingest files from an Amazon S3 bucket. Snowpipe is configured to load data into staging database tables. Then a task runs to load the data from the staging database tables into the reporting database tables.

The company is satisfied with the availability of the data in the reporting database tables, but the reporting tables are not pruning effectively. Currently, a size 4X-Large virtual warehouse is being used to query all of the tables in the reporting database.

What step can be taken to improve the pruning of the reporting tables?

AEliminate the use of Snowpipe and load the files into internal stages using PUT commands.

BIncrease the size of the virtual warehouse to a size 5X-Large.

CUse an ORDER BY <cluster_key (s) > command to load the reporting tables.

DCreate larger files for Snowpipe to ingest and ensure the staging frequency does not exceed 1 minute.

Show Suggested Answer

Suggested Answer: C

Effective pruning in Snowflake relies on the organization of data within micro-partitions. By using an ORDER BY clause with clustering keys when loading data into the reporting tables, Snowflake can better organize the data within micro-partitions. This organization allows Snowflake to skip over irrelevant micro-partitions during a query, thus improving query performance and reducing the amount of data scanned12.

Reference =

* Snowflake Documentation on micro-partitions and data clustering2

* Community article on recognizing unsatisfactory pruning and improving it1

by Della at Dec 09, 2024, 11:58 AM

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