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    Assignment No. 3
Semester: Spring 2019
    CS614 – Data Warehousing

    Total Marks: 20

    Due Date:
    August 01, 2019

    Objectives:
    After completing this assignment the students will be able to:
    • Understand parallelism
    • Calculate speed-up time for pipelining
    • Calculate Costs associated with nested loop joins while indexing is not used

    Instructions
    Please read the following instructions carefully before submitting assignment:
    It should be clear that your assignment will not get any credit if:

    o Assignment is submitted after due date.
    o Submitted assignment does not open or file is corrupt.
    o Assignment is copied (From internet/ to from students).
    o Assignment is submitted other than word format (.doc, .docx).

    Assignment

    Question No. 1

    Consider a garments factory where a Men’s casual shirts are manufactured. Each Shirt requires 15 minutes for completion. The factory management is now interested in introducing a pipeline where cutting, stitching and finalizing the shirt will be done in parallel.

    You are required to calculate the Speed-up that could be achieved after implementing pipeline for manufacturing of 25 shirts in a row.

    Question No. 2
    Consider two database tables X and Y, we are required to join these tables using Nested-Loop Join, Assume that indexing is not used in mentioned tables.
    The table information is given as:
    Size of Table X = 600 blocks
    Size of Table Y = 900 blocks
    Qualifying blocks for Table X = 50
    Qualifying blocks for Table Y = 100

    Calculate the join cost for X&Y and also for Y&X; after calculations mention which Table should be the outer one X or Y.

    Deadline:
    Your assignment must be uploaded on VULMS on or before August 01, 2019. While August 02, 2019 will be a bonus day for assignment submission. After the bonus day, no assignment would be entertained via email.

  • Cyberian's Gold

    Answer will be same after convert.

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  • Cyberian's Gold

  • Cyberian's Gold

  • Cyberian's Gold

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