Consider two relations R(a,b) and S(c,d) that are both horizontally partitioned across N = 3 nodes as shown in the diagram below. Each node locally stores approximately of the tuples in R and of the tuples in S. The tuples of R are randomly organized across machines (i.e., R is block partitioned across machines) while the tuples of S are hash-partitioned on S.c.
Consider two relations R(a,b) and S(c,d) that are both horizontally partitioned across N = 3 nodes as shown in the diagram below. Each node locally stores approximately of the tuples in R and of the tuples in S. The tuples of R are randomly organized across machines (i.e., R is block partitioned across machines) while the tuples of S are hash-partitioned on S.c.
Computer Networking: A Top-Down Approach (7th Edition)
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Chapter1: Computer Networks And The Internet
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
Transcribed Image Text:CONTEXT:
Consider two relations R(a,b) and S(c,d) that are both horizontally
partitioned across N = 3 nodes as shown in the diagram below. Each node locally
stores approximately i of the tuples in R and of the tuples in S. The tuples
of R are randomly organized across machines (i.e., R is block partitioned across
machines) while the tuples of S are hash-partitioned on S.c.
QUERY:
SELECT a, avg(d) as avg
FROM R, S
WHERE R.b = S.c
S.c
%3D
AND S.d > 0
GROUP BY a
PLEASE SOLVE THE FOLLOWING:
Assume the same query as before, only now the data is distributed on
300 servers instead of just 3 servers. We expect a linear speedup, in other words
we expect the runtime to be about 100 times faster. However, if the values of some
attribute are skewed, then the performance of a parallel query plan can be far from
a linear speedup. Indicate with of the attributes below, if skewed, can significantly
prevent your query plan from achieving linear speedup.
• Skew on attribute R.a.
• Skew on attribute R.b.
• Skew on attribute S.c.
• Skew on attribute S.d.
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