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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)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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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.
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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