rdlc data matrix

rdlc data matrix

rdlc data matrix

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Solving for the unknown voltage Vx = 5 20 + 12 + 18 = 5 V EXAMPLE 2-4 Consider the circuit shown in Fig 2-6 Find the unknown voltages SOLUTION To be consistent and therefore reduce our chances for error, we again consider clockwise loops, taking each voltage drop we encounter to be positive and each voltage rise we encounter to be negative There are three loops in the circuit and we apply KVL to each loop individually Starting on the left side of the circuit V1 + 5 + 10 = 0 V1 = 5 + 10 = 15 V Next, moving to the loop on the top-right side of the circuit 5 + 7 + V2 + 3 = 0 V2 = 5 7 3 = 5 V Since V2 < 0, the actual polarity is the opposite of what is shown in the gure, ie, the actual +/ signs are reversed for V2 Continuing by considering the

13

CHAPTER 15:

We can scan the inner loop alternately forward and backward This scanning method orders the requests for disk blocks so that the data remaining in the buffer from the previous scan can be reused, thus reducing the number of disk accesses needed If an index is available on the inner loop s join attribute, we can replace le scans with more ef cient index lookups Section 1353 describes this optimization

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loop in the lower-right part of the circuit 10 3 + V3 = 0 V3 = 10 + 3 = 13 V Now we ve found all the voltages in the circuit, but we must note one other fact KVL is a general law that applies to the voltages around any loop KVL can therefore be applied to the outside loop in Fig 2-6 Hence V1 + 7 + V2 + V3 = 0 Is this true given the results we have found Let s insert the numbers V1 + 7 + V2 + V3 = 15 + 7 5 + 13 = 15 + 2 + 13 = 0 So KVL is indeed satis ed for the outer loop

In a nested-loop join (Figure 134), if an index is available on the inner loop s join attribute, index lookups can replace le scans For each tuple tr in the outer relation r, the index is used to look up tuples in s that will satisfy the join condition with tuple tr This join method is called an indexed nested-loop join; it can be used with existing indices, as well as with temporary indices created for the sole purpose of evaluating the join Looking up tuples in s that will satisfy the join conditions with a given tuple tr is essentially a selection on s For example, consider depositor 1 customer Suppose that we have a depositor tuple with customer-name John Then, the relevant tuples in s are those that satisfy the selection customer-name = John The cost of an indexed nested-loop join can be computed as follows For each tuple in the outer relation r, a lookup is performed on the index for s, and the relevant tuples are retrieved In the worst case, there is space in the buffer for only one page of r and one page of the index Then, br disk accesses are needed to read relation r, where br denotes the number of blocks containing records of r For each tuple in r, we perform an index lookup on s Then, the cost of the join can be computed as br + nr c, where nr is the number of records in relation r, and c is the cost of a single selection on s using the join condition We have seen in Section 133 how to estimate the cost of a single selection algorithm (possibly using indices); that estimate gives us the value of c The cost formula indicates that, if indices are available on both relations r and s, it is generally most ef cient to use the one with fewer tuples as the outer relation For example, consider an indexed nested-loop join of depositor 1 customer, with depositor as the outer relation Suppose also that customer has a primary B+ -tree index on the join attribute customer-name, which contains 20 entries on an average in each index node Since customer has 10,000 tuples, the height of the tree is 4, and one more access is needed to nd the actual data Since ndepositor is 5000, the total cost is 100 + 5000 5 = 25, 100 disk accesses This cost is lower than the 40, 100 accesses needed for a block nested-loop join.

The merge join algorithm (also called the sort merge join algorithm) can be used to compute natural joins and equi-joins Let r(R) and s(S) be the relations whose natural join is to be computed, and let R S denote their common attributes Suppose