Monday, May 4, 2020

Distributed Database Question Bank with Answers 12

Distributed Database Question Bank with Answers

1. In the Two-Phase Commit Protocol (2PC), why can blocking never be completely eliminated, even when the participants elect a new coordinator?

After the election, the new coordinator may crash as well. In this case, the remaining participants may not be able to reach a final decision, because this requires the vote from the newly elected coordinator, just as before.
The greatest disadvantage of the two-phase commit protocol is that it is a blocking protocol. If the coordinator fails permanently, some participants will never resolve their transactions: After a participant has sent an agreement message to the coordinator, it will block until a commit or rollback is received.

2. How should a small/large relation be partitioned?

It is better to assign a small relation to a single disk (single partition). Partitioning across several sites will never improve the performance.
A large relation should be partitioned across all the available disks (to increase the use of parallelism). In case of large relations, partitioning will be helpful a lot.

3. Which among the three architectures (share disk, shared memory, shared nothing) supports the failure of one processor?

Shared disk architecture is fault-tolerant to the extent that if a processor fails, other processors can take over its tasks as all processors can access the database resident on the disks.

4. Which form of parallelism (inter-query, intra-query, inter-operation, intra-operation) is most likely to advance the following goals and why?

i) Increasing the throughput and response time of the system when there are lots of smaller queries.
Inter-query parallelism is about executing multiple queries simultaneously. When there are smaller queries, this parallelism will increase the throughput, that is, the number of queries executed per unit time will be increased. Other type of parallelism don’t help much for small queries.

ii) Increasing the throughput and response time of the system, when there are a few large queries and the systems consist of several disks and processors.
Intraquery parallelism is likely to reduce throughput times efficiently in the cases of a few large queries. A large number of processors is best made use of using intraoperation parallelism, these queries typically contain  only a few operations (when there are few queries, then the number of simultaneous operation may even be less than the number of processors), but each operation usually refers to large number of tuples.
An example would be parallel sort: each processor executes the same operation, in this case sorting, simultaneously with the other processors. There is no interaction with other processors.

5. Suppose a company which processes transactions is growing rapidly and needs to choose a new, parallel computer. What would be more important, speedup or transaction scale-up? Why?

Since the scale of operations increases, one can expect the number of transactions submitted per unit time to increase. Individual transactions don’t have to take more time, so scale-up is the most important thing.



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