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You are designing a date dimension table in an Azure Synapse Analytics dedicated SQL pool. The date
dimension table will be used by all the fact tables.
Which distribution type should you recommend to minimize data movement?
Suggested Answer: B
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A replicated table has a full copy of the table available on every Compute node. Queries run fast on replicated tables since joins on replicated tables don't require data movement. Replication requires extra storage, though, and isn't practical for large tables.
Incorrect Answers:
C: A round-robin distributed table distributes table rows evenly across all distributions. The assignment of rows to distributions is random. Unlike hash-distributed tables, rows with equal values are not guaranteed to be assigned to the same distribution.
As a result, the system sometimes needs to invoke a data movement operation to better organize your data before it can resolve a query.
33 comments · newest first
RO
Ronald
10 months ago
Wait, are we sure REPLICATE is the best choice here? Sounds too easy!
LA
Lanie
10 months ago
HASH is better for larger tables, though.
ZI
Zita
11 months ago
ROUND_ROBIN just spreads it out randomly, right? Not ideal.
EM
Emerson
11 months ago
I thought REPLICATE was only for small tables?
TR
Tracie
11 months ago
I’d go with REPLICATE for the date dimension. Less data movement!
BE
Bette
11 months ago
I agree with Nilsa about REPLICATE, but I wonder if there are any scenarios where HASH could be more beneficial.
RI
Ricarda
12 months ago
I practiced a similar question, and I feel like ROUND_ROBIN is not the best choice for minimizing data movement. It might lead to uneven data distribution.
MO
Moon
12 months ago
I'm not entirely sure, but I remember something about HASH distribution being good for evenly distributing data. Maybe it could work here too?
NI
Nilsa
12 months ago
I think we should go with REPLICATE since the date dimension will be used by all fact tables, which might reduce data movement.
KE
Kenneth
1 year ago
I'm leaning towards ROUND_ROBIN. Since this is a dimension table, the data won't be skewed, so ROUND_ROBIN could provide a good balance of performance and simplicity.
ST
Stephaine
1 year ago
REPLICATE might be a good choice here. That way the date dimension table will be available on all compute nodes, which could help reduce data movement across the fact tables.
TA
Tambra
1 year ago
Hmm, I'm a bit unsure about this one. I know HASH is good for minimizing data movement, but I'm not sure if that's the best choice for a date dimension table that will be used by all the fact tables.
BR
Brittni
1 year ago
I think the key here is to minimize data movement, so HASH distribution seems like the best option to me.
LA
Laquanda
1 year ago
HASH distribution, definitely. Anything to avoid the dreaded 'data movement' in my reports. I'm not trying to be the laughingstock of the data team!
TA
Tabetha
1 year ago
Hmm, HASH distribution seems like the logical choice. Can't go wrong with that. Unless you want to be the one explaining all the extra data movement to the boss.
JO
Josue
1 year ago
User 3: Agreed, no need to complicate things with extra data movement.
SO
Sommer
1 year ago
User 2: Yeah, it will minimize data movement for sure.
AL
Alberta
1 year ago
User 1: I think HASH distribution is the way to go.
LA
Lashon
1 year ago
HASH distribution is the way to go. I don't want to be the one responsible for excessive data movement in the data warehouse!
CH
Charlene
1 year ago
User 3: Definitely, we don't want any unnecessary data shuffling around.
MO
Mozell
1 year ago
User 2: I agree, we need to make sure the data is distributed efficiently.
AN
Antonio
1 year ago
User 1: HASH distribution is definitely the best choice for minimizing data movement.
LI
Lillian
2 years ago
I'm not sure, but I think REPLICATE distribution could also be a good option to consider.
JE
Jesusa
2 years ago
HASH distribution sounds like the way to go here. It will ensure that related data is collocated on the same compute node, reducing data movement.
DA
Dawne
1 year ago
Definitely go with HASH distribution to minimize data movement in this case.
AL
Alecia
1 year ago
I think HASH distribution is the most efficient choice for this scenario.
RE
Regenia
1 year ago
HASH distribution is the best option for ensuring related data is collocated on the same compute node.
SU
Sueann
1 year ago
I agree, using HASH distribution will definitely help with minimizing data movement.
LO
Lorrie
2 years ago
I think the correct answer is HASH distribution. It should minimize data movement across the compute nodes in the dedicated SQL pool.
MI
Mike
1 year ago
Yes, HASH distribution ensures that related data is stored together, reducing the need to move data around.
TO
Toi
1 year ago
I agree, HASH distribution is the way to go for minimizing data movement.
MA
Margret
2 years ago
I agree with Socorro. HASH distribution will help optimize performance for all fact tables.
SO
Socorro
2 years ago
I think we should recommend HASH distribution to minimize data movement.