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Correct option is (B) Logical OR

Easiest explanation: The logical OR operation is used for the COMPUTATION of the UNION of bitmaps. This is similar to the BINARY set union operation.

Right answer is (b) False

To ELABORATE: Intersection operations are extremely fast on bitmaps making them ideal for SUPPORTING queries on MULTIPLE attributes.

Right CHOICE is (a) It RECOGNIZES deleted RECORDS

Easy explanation: An existence BITMAP is used to recognize deleted records and not to prevent deletion of records. It ALSO does not insert any records into empty bitmaps.

Correct ANSWER is (a) LOGICAL AND

The explanation: The intersection of the bitmaps is DONE by the logical AND operation. This is similar to the binary SET intersection operation which is done by the logical AND operation.

Right OPTION is (b) Bitmap index

For explanation: A bitmap index on the attribute A of RELATION r CONSISTS of one bitmap for each value that A can take. Each bitmap CONTAINS as many bits as the number of records in the relation.

The correct answer is (a) An ARRAY of BITS

Easiest explanation: A bitmap is simply an array of bits. A bitmap can be used for various purposes such as bitmap INDEXING.

Correct choice is (d) SUM of DIGITS

To explain I would say: The sum of the digits hash function CLASSIFIES the data into 10 DIFFERENT buckets thus MAKING it the highest.

The CORRECT CHOICE is (a) SUM of digits modulo 8

For explanation I would SAY: The sum of digits modulo 2 CLASSIFIES the data into only 2 buckets i.e. 0 and 1.

The correct ANSWER is (a) Frequency of INSERTION and deletion

For explanation I would SAY: The frequency of insertion and deletion has to be taken into consideration while CHOOSING an indexing technique. The frequency of insertion and deletion DETERMINES the hash index.

Correct CHOICE is (c) A search KEY on which range queries are likely

For explanation I would say: Hash structures are not the best choice for search KEYS on which range queries are likely because the range queries might contain DIFFERENT values of the search keys which might RESULT in improper placement in the hash table.

The CORRECT ANSWER is (a) Linear HASHING

The best explanation: The form of dynamic hashing that avoids the additional LEVEL of indirection is called as Linear hashing. This has more overflow BUCKETS than extendable hashing.

The correct ANSWER is (b) Lookup involves additional LEVEL of INDIRECTION

The explanation: In DYNAMIC HASHING, lookup involves an additional level of indirection. The rest of the options are the advantages of dynamic hashing.

Correct ANSWER is (b) Less

To explain: The space overhead in dynamic HASHING is less than that of static hashing. This is because the HASH FUNCTION is chosen based on the size of the file at some ANTICIPATED point in the future.

Right OPTION is (d) All of the mentioned

Best EXPLANATION: We can perform LOOKUP, INSERTION and deletion on a dynamic hash structure.

Correct choice is (B) Extendable HASHING

To ELABORATE: DYNAMIC hashing is also called as extendable hashing because it can accommodate the growth and shrinkage of the database.

The correct ANSWER is (a) True

To explain: HASH indices are only secondary index STRUCTURES. A hash index is NEVER needed as a clustering index structure.

Correct answer is (a) True

For EXPLANATION: A hash INDEX organizes the SEARCH keys, with their associated pointers, into a hash file structure. We can construct a hash index by applying a hash function on a search KEY and store the key and its associated pointers in the bucket.

Right answer is (b) Overflow chaining

Explanation: All the overflow buckets are chained together in a linked LIST. Overflow HANDLING USING a linked list of buckets is CALLED as Overflow chaining.

Correct option is (c) Bucket skew

To explain: Some buckets are ASSIGNED more records than the others which causes bucket overflow, this CONDITION is called as Bucket skew. Skew occurs if multiple records have the same SEARCH key or if the given hash function is NON UNIFORM.

Correct OPTION is (b) Hash index organization

Explanation: Hashing can be used for 2 DIFFERENT purposes, hash file organization and hash index organization. In a hash index organization, we organize the SEARCH KEYS, with their associated pointers, into a hash file structure.

The correct option is (a) Hash file organization

The explanation is: HASHING can be used for 2 DIFFERENT purposes, hash file organization and hash index organization. In a Hash file organization, we obtain the address of the DISK block containing a desired record directly by computing a function on the SEARCH KEY value of the record.

Right ANSWER is (b) Bucket

Best EXPLANATION: The term bucket is used to DENOTE a unit of STORAGE that can store one or more records. A bucket is typically a disk block but it can ALSO be larger than a disk block.

The correct option is (b) Covering INDICES

To explain I would say: Covering indices are the indices that STORE the values of some attributes along with the pointers to the RECORD. STORING extra attribute values is USEFUL as they allow us to Answer queries without actually looking up the records.

Correct option is (a) BULK loading

To ELABORATE: Insertion of a large NUMBER of entries at a time into an index is referred to as bulk loading of the index. This reduces the time complexity as MULTIPLE entries are loaded at the same time.

The CORRECT answer is (a) Prefix compression

Best explanation: The FANOUT of NODES can be increased by using a technique called prefix compression. In this, we do not store the entire value of the search key at the NODE. We only store the prefix of the search key.

The CORRECT option is (B) Non UNIQUE search key

For EXPLANATION: If a relation can have more than one record containing the same search key value, the search key is said to be a non-unique search key. A problem with non-unique search keys is inefficiency during delete operations.

The correct CHOICE is (a) Both the statements are true

To explain I WOULD say: Both insertion and deletion of records might require the change in position of the initial nodes because the new data value might not exactly fit into the B+ tree. THUS rotation of the nodes is generally REQUIRED.

The correct option is (a) INTERNAL nodes

Easy explanation: Non leaf nodes are also KNOWN as internal nodes. A non-leaf node MAY hold up to N pointers and should hold at least n/2 pointers.

The CORRECT choice is (B) The bottommost NODES

Easy explanation: The bottommost nodes that mark the end of a tree are KNOWN as the leaf nodes in a B+ tree.

Right option is (B) False

To EXPLAIN I WOULD say: B+ TREES are always balanced. Every path from the root to the leaf of the tree is of the same length.

The correct answer is (B) MULTILEVEL indices

Easiest explanation: Indices with two or more levels are called as multilevel indices. They REQUIRE significantly few I/O OPERATIONS than SEARCHING using binary search.

The CORRECT OPTION is (a) True

The explanation is: If the file containing the RECORDS is sequentially ordered, a CLUSTERING index is an index whose search key ALSO defines the sequential order of the file. Clustering indices are also called as primary indices.

The correct choice is (b) Cluttering index

Easiest EXPLANATION: If the file containing the records is SEQUENTIALLY ordered, a Clustering index is an index whose search key also defines the sequential order of the file. Clustering indices are also called as primary indices but they do not denote an index on the primary key. Such indices can be BUILT on any search key.

Right choice is (d) Space OVERHEAD

The EXPLANATION is: The additional space occupied by an index structure is called as space overhead. It is usually a WORTHWHILE sacrifice to achieve IMPROVED performance.

The correct CHOICE is (B) Deletion time

Explanation: The time it takes to DELETE a data item is CALLED as deletion time. This value includes finding the item to be deleted and the time taken to update the index structure.

Right choice is (a) INSERTION time

To explain: The time it TAKES to insert a NEW data item is called Insertion time. This value includes the time taken to find the correct PLACE to insert the new data item as well as the time it takes to UPDATE the index structure.

Correct option is (d) Access TIME

For explanation: The time it TAKES to find a particular data item or a set of data ITEMS using the TECHNIQUE in question is called as access time.

Right choice is (B) ACCESS types

Easy explanation: The types of access that are SUPPORTED efficiently are called as Access types. Access types can include finding records with a specified attribute VALUE or within a particular range.