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Silberschatz Korth Sudarshan: Database System Concepts, Fourth Edition
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22 Advanced Querying and Information Retrieval
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The McGraw Hill Companies, 2001
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tion The function row number sorts the rows and gives each row a unique number corresponding to its position in the sort order; different rows with the same ordering value would get different row numbers, in a nondeterministic fashion Finally, for a given constant n, the ranking function ntile(n) takes the tuples in each partition in the speci ed order, and divides them into n buckets with equal numbers of tuples4 For each tuple, ntile(n) then gives the number of the bucket in which it is placed, with bucket numbers starting with 1 This function is particularly useful for constructing histograms based on percentiles For instance, we can sort employees by salary, and use ntile(3) to nd which range (bottom third, middle third, or top third) each employee is in, and compute the total salary earned by employees in each range: select threetile, sum(salary) from ( select salary, ntile(3) over (order by (salary)) as threetile from employee) as s group by threetile The presence of null values can complicate the de nition of rank, since it is not clear where they should occur rst in the sort order SQL:1999 permits the user to specify where they should occur by using nulls rst or nulls last, for instance select student-id, rank () over (order by marks desc nulls last) as s-rank from student-marks
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An example of a window query is query that, given sales values for each date, calculates for each date the average of the sales on that day, the previous day, and the next day; such moving average queries are used to smooth out random variations Another example of a window query is one that nds the cumulative balance in an account, given a relation specifying the deposits and withdrawals on an account Such queries are either hard or impossible (depending on the exact query) to express in basic SQL SQL:1999 provides a windowing feature to support such queries In contrast to group by, the same tuple can exist in multiple windows Suppose we are given a relation transaction(account-number, date-time, value), where value is positive for a deposit and negative for a withdrawal We assume there is at most one transaction per date-time value Consider the query
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4 If the total number of tuples in a partition is not divisible by n, then the number of tuples in each bucket can differ by at most 1 Tuples with the same value for the ordering attribute may be assigned to different buckets, nondeterministically, in order to make the number of tuples in each bucket equal
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Silberschatz Korth Sudarshan: Database System Concepts, Fourth Edition
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22 Advanced Querying and Information Retrieval
The McGraw Hill Companies, 2001
22
Advanced Querying and Information Retrieval
select account-number, date-time, sum(value) over (partition by account-number order by date-time rows unbounded preceding) as balance from transaction order by account-number, date-time The query gives the cumulative balances on each account just before each transaction on the account; the cumulative balance of the account is the sum of values of all earlier transactions on the account The partition by clause partitions tuples by account number, so for each row only the tuples in its partition are considered A window is created for each tuple; the keywords rows unbounded preceding specify that the window for each tuple consists of all tuples in the partition that precede it in the speci ed order (here, increasing order of date-time) The aggregate function sum(value) is applied on all the tuples in the window Observe that the query does not use a group by clause, since there is an output tuple for each tuple in the transaction relation While the query could be written without these extended constructs, it would be rather dif cult to formulate Note also that different windows can overlap, that is, a tuple may be present in more than one window Other types of windows can be speci ed For instance, to get a window containing the previous 10 rows for each row, we can specify rows 10 preceding To get a window containing the current, previous, and following row, we can use between rows 1 preceding and 1 following To get the previous rows and the current row, we can say between rows unbounded preceding and current Note that if the ordering is on a nonkey attribute, the result is not deterministic, since the order of tuples is not fully de ned We can even specify windows by ranges of values, instead of numbers of rows For instance, suppose the ordering value of a tuple is v; then range between 10 preceding and current row would give tuples whose ordering value is between v 10 and v (both values inclusive) When dealing with dates, we can use range interval 10 day preceding to get a window containing tuples within the previous 10 days, but not including the date of the tuple Clearly, the windowing functionality of SQL:1999 is very rich and can be used to write rather complex queries with a small amount of effort
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