Consider a relational DBMS that has two relations: Emp (employees) and Dept (departments). Emp (id, name, age, salary, dname) Dept (dname, location) • The Emp table has 500 tuples, and each tuple has a fixed length of 500 bytes. The primary key attribute "id" has a length of 40 bytes. • The Dept table has 100 tuples, and each tuple has 200 bytes. The primary key attribute "dname" has a length of 20 bytes. For simplicity, we assume each employee belongs to one and only one department, and each department has 5 employees. Each block has 8K (8192) bytes, in which 100 bytes are reserved for the block header. No records span two or more blocks. Consider the following disk organization strategy: Sequential: All the Emp records are placed sequentially based on their id's. Similarly, all Dept records are stored sequentially based on their names. Suppose we want to build a primary index INDEX1 on Emp.id, and a secondary index INDEX2 on Dept.location. Treat duplicates in the secondary index in a straightforward way; that is, each tuple should have an index entry. Assume: Each block pointer is 6 bytes. • Each record pointer is 8 bytes. • Index entries do not span blocks. For each index type (dense and sparse), compute the minimum number of blocks needed for INDEX1 and INDEX2, respectively. (Notice that some type of index may not make sense.) That is, compute the number of blocks for the following combinations: . INDEX1 + Dense; INDEX1 + Sparse; • INDEX2 + Dense; • INDEX2 + Sparse. a) INDEX1 + Sparse: 1 block. b) INDEX1 + Sparse: 5 blocks. c) INDEX1 + Dense: 4 blocks. d) INDEX2 + Dense: it doesn't make sense.