How many nonempty aggregated (I.
E. , non-base) cells a complete cube will contain? Answer: 1918. Exploitation: Initially, for those cuboids with at least one of the first three dimensions not aggregated(I. E. Not *), for example cuboids (dim, t, t, t, t), there are two cells.
The number of such cuboids is (23 - 1) * 27 = 896. Second, for cuboids with the first three dimensions aggregated, for example cuboids (t, t, t, dim, ... , dimly), there is only one cell.
The number of such cuboids is 27 = 128.So the number of non-based cells is 896 * 2 + 128 - 2 = 1918. 2. How many nonempty aggregated cells an iceberg cube will contain, if the condition of the iceberg cube is count 2? Answer: 128. Exploitation: Only those cells with the first three dimensions aggregated (I.
E. *), for example the cell (t, t, t, be, blob), have count 2. And the number of such cells is 27 = 128. 3. How many (non-star) dimensions does the closed cell with count 2 have? Answer: 7.
Exploitation: There is only one closed cell with count 2, I. E. , t, t, be, ... , blob).
So the number of non-star dimensions is 10 - 3 = 7. 4. How many closed cells in the full cube? Answer: 3. Exploitation: A closed cube is a data cube consisting of only closed cells.
The three closed cells are (t, t, t, be, blob),(ay, ay, ay, be, be, blob), and (bal, be, be, be, be, bib). Question 2 1 . How many cuboids are there in this cube Answer: 24 Where is the number of levels associated with dimension I. So for the Total number of cuboids = (2+1) *(1+1) *(1+1)*(1+1) =24 2.
Counting cells in the Answer = 48SELECT distinct city,category,rating,price ,count(*) as tot FROM [assigns_Q]. [db]. [CASES_statement 2_Q] A group by A. Category,A. Rating,A.
Price,A. City 3. Now let's drill up by climbing up in the Location dimension from City to State. How many cells are there in the cuboids. Answer = 34 SELECT distinct state,category,rating,price ,count(*) as tot FROM [assigns_Q].
[db]. Group by A. Category,A. Rating,A. Price,A. State 4.
How many cell in the cuboids(*,category,Rating,Price) Answer = 23 SELECT distinct A. Category,A. Rating,A. Ice,count(*) as tot 2_Q] A group by A. Category,A.
Rating,A. Price FROM [casting_Q]. 5. What is the count for the cell(Location(state)=Illinois,*,rating=3,price='moderate' Answer = 2 (record # 6 ,45) SELECT FROM 2_Q] A where A. State = 'Illinois' and A.
Rating = 3 and A. Price='moderate' 6. What is the count for the cell(Location(city) = 'Chicago',Category = 'food',*,*) Answer = 2 Select count(*) from 2_Q] A where A. City ? 'Chicago' and A. Category = 'food' Mint-PM#3 1) OLAP operation = Drill down Most Sales = Mountain bikeLeast Sales = Trial Bike 2) Popular way Web Searching by Chrome Best visualization of granularity = we can drill down data at multiple granularity level for time ranging from year/quarter,months.
Different granularity levels 3)Total transaction / region, to give the better idea of the concentration of customers in different regions. Also the following cube can be used see the sales trend for the last year among different categories. The following cube can be used as analyzing page views contributed by each browser for different quarters.
