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What happens to the underlying table data when a CLUSTER BY clause is added to a Snowflake table?
Suggested Answer: D
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When aCLUSTER BYclause is added to a Snowflake table, it specifies one or more columns to organize the data within the table's micro-partitions. This clustering aims to colocate data with similar values in the same or adjacent micro-partitions. By doing so, it enhances the efficiency of query pruning, where the Snowflake query optimizer can skip over irrelevant micro-partitions that do not contain the data relevant to the query, thereby improving performance.
References:
Snowflake Documentation on Clustering Keys & Clustered Tables1.
Community discussions on how source data's ordering affects a table with a cluster key
23 comments · newest first
LE
Lenna
9 months ago
Wait, are we sure about B? Larger micro-partitions?
GL
Glenn
10 months ago
I think D makes more sense for pruning performance.
NO
Noe
10 months ago
A is correct! It helps with faster searches.
LI
Lili
10 months ago
Totally agree with D, colocating data is key!
CE
Celeste
11 months ago
I thought clustering just reorganized data, not hashed it.
FA
Fausto
11 months ago
I believe that clustering can help reduce the number of partitions scanned, so maybe option B is correct, but I’m not entirely confident.
RY
Ryan
11 months ago
I practiced a similar question, and I feel like the hashing aspect is important, but I can't recall if that's the main effect of CLUSTER BY.
KI
Kiley
11 months ago
I remember something about how data is colocated by the cluster key, which improves pruning performance. That sounds like option D to me.
BI
Billy
11 months ago
I think the CLUSTER BY clause helps with data organization, but I'm not sure if it actually creates larger or smaller micro-partitions.
PE
Pearlie
12 months ago
The CLUSTER BY clause is all about optimizing the micro-partitions, so I'm guessing it's either option B or C. I'll need to think through the tradeoffs a bit more to decide.
KA
Karl
12 months ago
I'm pretty confident that the CLUSTER BY clause is about hashing the data to facilitate faster searches. I think option A is the right answer here.
DA
Danica
12 months ago
Based on the options, it seems like the CLUSTER BY clause helps with data pruning and parallelism. I'm leaning towards option D, since that sounds the most relevant.
EM
Emeline
1 year ago
Hmm, I'm a bit confused on the exact impact of the CLUSTER BY clause. Is it just about creating larger or smaller micro-partitions, or is there more to it?
OZ
Ozell
1 year ago
I think the key here is understanding how Snowflake's micro-partitioning works. The CLUSTER BY clause should help group common data values together to improve query performance.
TA
Tawna
1 year ago
I see your point, Brandee. Colocating data by the cluster key could indeed improve performance.
BR
Brandee
1 year ago
I believe the answer is D) Data may be colocated by the cluster key within the micro-partitions to improve pruning performance.
ED
Edgar
1 year ago
Option D sounds the most accurate to me. Clustering the data by the key should help optimize pruning during query execution.
QU
Quinn
9 months ago
True, but D really focuses on optimizing queries.
EL
Elli
9 months ago
I think option A is also valid. Fast searches are important too.
LE
Leota
10 months ago
Yeah, colocating data should help with pruning.
CO
Cordelia
10 months ago
I agree, option D seems right. It makes sense for performance.
BE
Bettye
1 year ago
I agree with Vincenza, hashing the data by the cluster key makes sense for faster searches.
VI
Vincenza
1 year ago
I think the answer is A) Data is hashed by the cluster key to facilitate fast searches for common data values.