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Exam SnowPro Core All Questions

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Exam SnowPro Core topic 1 question 1095 discussion

Actual exam question from Snowflake's SnowPro Core
Question #: 1095
Topic #: 1
[All SnowPro Core Questions]

How should clustering be used to optimize the performance of queries that run on a very large table?

  • A. Manually re-cluster the table regularly.
  • B. Choose one high cardinality column as the clustering key.
  • C. Use the column that is most-frequently used in query select clauses as the clustering key.
  • D. Assess the average table depth to identify how clustering is impacting the query.
Show Suggested Answer Hide Answer
Suggested Answer: D 🗳️

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d22770a
1 month ago
Selected Answer: D
D is correct
upvoted 2 times
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joshguy40
2 months, 2 weeks ago
Selected Answer: D
its D select clause is the column you choose to select. We dont care about that. We care about the columns being filtered in the WHERE clause.
upvoted 4 times
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08c95eb
5 months, 2 weeks ago
Selected Answer: D
selective filters is different than select clause
upvoted 4 times
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Jacobr5000
6 months ago
Selected Answer: C
"Snowflake recommends prioritizing keys in the order below: Cluster columns that are most actively used in selective filters."
upvoted 2 times
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Lematthew31
6 months, 2 weeks ago
Selected Answer: C
It's C : https://docs.snowflake.com/en/user-guide/tables-clustering-keys#strategies-for-selecting-clustering-keys "Selecting the right columns/expressions for a clustering key can dramatically impact query performance. Analysis of your workload will usually yield good clustering key candidates. Snowflake recommends prioritizing keys in the order below: Cluster columns that are most actively used in selective filters"
upvoted 3 times
d22770a
1 month ago
SELECTIVE FILTER means WHERE clause, Option D talks SELECT column. So that is wrong
upvoted 1 times
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yaho5
7 months, 1 week ago
Selected Answer: C
C Snowflake recommends prioritizing keys in the order below: Cluster columns that are most actively used in selective filters. For many fact tables involved in date-based queries (for example “WHERE invoice_date > x AND invoice date <= y”), choosing the date column is a good idea. For event tables, event type might be a good choice, if there are a large number of different event types. (If your table has only a small number of different event types, then see the comments on cardinality below before choosing an event column as a clustering key.) If there is room for additional cluster keys, then consider columns frequently used in join predicates, for example “FROM table1 JOIN table2 ON table2.column_A = table1.column_B”.
upvoted 3 times
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NachoPrendes
7 months, 2 weeks ago
Selected Answer: C
C https://docs.snowflake.com/en/user-guide/tables-clustering-keys#:~:text=Cluster%20columns%20that%20are%20most%20actively%20used%20in%20selective%20filters
upvoted 3 times
induna
7 months, 2 weeks ago
I think it is D, per the doc you listed: The number of distinct values (i.e. cardinality) in a column/expression is a critical aspect of selecting it as a clustering key. It is important to choose a clustering key that has: A large enough number of distinct values to enable effective pruning on the table. A small enough number of distinct values to allow Snowflake to effectively group rows in the same micro-partitions.
upvoted 2 times
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simus90
7 months, 2 weeks ago
Selected Answer: D
it s D
upvoted 4 times
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