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DBMS Dynamic Hashing MCQs

DBMS Dynamic Hashing MCQs: This section contains multiple-choice questions and answers on Dynamic Hashing in DBMS.
Submitted by Anushree Goswami, on April 23, 2022

1. Static hashing has problems such as bucket overflows, which can be overcome by __ hashing.

1. Simple
2. Dynamic
3. Overflow
4. None

Answer: B) Dynamic

Explanation:

Static hashing has problems such as bucket overflows, which can be overcome by dynamic hashing.

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2. According to this method, data buckets expand or contract as the number of records increases or decreases.

1. Increases
2. Decreases
3. Both A and B
4. None of the above

Answer: C) Both A and B

Explanation:

According to this method, data buckets expand or contract as the number of records increases or decreases.

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3. What is Dynamic Hashing also known as?

1. Extendable Hashing Method
2. Extra Hashing Method
3. Extendable Dynamic Method
4. Extra Dynamic Method

Answer: A) Extendable Hashing Method

Explanation:

Dynamic Hashing is also known as Extendable Hashing Method.

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4. Hashing is dynamic with this method, i.e., it allows for insertions or deletions without affecting performance.

1. Insertions
2. Deletions
3. Both A and B
4. None of the above

Answer: C) Both A and B

Explanation:

Hashing is dynamic with this method, i.e., it allows for insertions or deletions without affecting performance.

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5. Which of the following comes in the steps of search a key?

1. Using the key's hash address, calculate the address.
2. In the directory, i refers to the number of bits used.
3. Take the i bits of the hash address that are the least significant.
4. All of the above

Answer: D) All of the above

Explanation:

The steps that come in the search of a key -

1. Using the key's hash address, calculate the address.
2. In the directory, i refers to the number of bits used.
3. Take the i bits of the hash address that are the least significant.

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6. Which of the following comes in the steps of insert a new record?

1. The retrieval procedure is the different, you should end up in some bucket.
2. Place the record in that bucket if there is nol space.
3. The bucket will be split if it is full, and records will be redistributed.
4. All of the above

Answer: C) The bucket will be split if it is full, and records will be redistributed

Explanation:

The bucket will be split if it is full, and records will be redistributed.

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7. Data growth in the system does not affect ____ with this method.

1. Database
2. System
3. Performance
4. Memory

Answer: C) Performance

Explanation:

Data growth in the system does not affect performance with this method.

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8. By increasing the memory ___, the data can be accommodated.

1. Lane
2. Size
3. Data
4. None

Answer: B) Size

Explanation:

By increasing the memory size, the data can be accommodated.

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9. Since memory grows and shrinks with the data, this method makes the ____ of memory.

1. Least
2. Average
3. Most
4. None

Answer: C) Most

Explanation:

Since memory grows and shrinks with the data, this method makes the most of memory.

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10. By using this method, ____ memory will be left over.

1. Unused
2. No unused
3. Used
4. No Used

Answer: B) No unused

Explanation:

By using this method, no unused memory will be left over.

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11. Data in dynamic databases that grow and shrink frequently benefit from this method.

1. Static
2. Dynamic
3. Hash
4. None

Answer: B) Dynamic

Explanation:

Data in dynamic databases that grow and shrink frequently benefit from this method.

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12. By using this method, bucket sizes are also increased as data sizes ___.

1. Increase
2. Decrease
3. Minimized
4. Maximized

Answer: A) Increase

Explanation:

By using this method, bucket sizes are also increased as data sizes increase.

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13. The ____ address table will maintain the addresses.

1. Bucket
2. Data
3. Block
4. Log

Answer: A) Bucket

Explanation:

The bucket address table will maintain these addresses.

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14. As buckets grow and shrink, the address of the data ___ accordingly.

1. Repeats
2. Changes
3. Flows
4. None

Answer: B) Changes

Explanation:

As buckets grow and shrink, the address of the data changes accordingly.

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15. It becomes tedious to maintain the bucket address table if there is a big ___ in data.

1. Increase
2. Decrease
3. Flow
4. None

Answer: A) Increase

Explanation:

It becomes tedious to maintain the bucket address table if there is a big increase in data.

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16. There will also be a ___ situation in the dynamic hashing.

1. Data Overflow
2. Data Underflow
3. Bucket Overflow
4. Bucket Underflow

Answer: C) Bucket Overflow

Explanation:

There will also be a bucket overflow situation in this case.

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17. The bucket overflow situation might be reached much faster than static hashing.

1. Static
2. Dynamic
3. Both a and b
4. None of the above

Answer: A) Static

Explanation:

However, this situation might be reached much faster than static hashing.

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