From: owner-ammf-digest@smoe.org (alt.music.moxy-fruvous digest) To: ammf-digest@smoe.org Subject: alt.music.moxy-fruvous digest V14 #12523 Reply-To: ammf@fruvous.com Sender: owner-ammf-digest@smoe.org Errors-To: owner-ammf-digest@smoe.org Precedence: bulk alt.music.moxy-fruvous digest Saturday, November 4 2023 Volume 14 : Number 12523 Today's Subjects: ----------------- Meghanâs amazing weight loss secret ["Copy this" Subject: Meghanâs amazing weight loss secret Meghanbs amazing weight loss secret http://blackoutusa.shop/He56n-R4D5-FAkJhuYtiXUnYVb_Z6jMGn65Xk20PClMwi20RBg http://blackoutusa.shop/a4H6XPlzKRVnTiPQYpv4JstSnyzHhsnI1BCoQXUBeQxg13r6yw there are many aggregations that can be calculated, often only a predetermined number are fully calculated; the remainder are solved on demand. The problem of deciding which aggregations (views) to calculate is known as the view selection problem. View selection can be constrained by the total size of the selected set of aggregations, the time to update them from changes in the base data, or both. The objective of view selection is typically to minimize the average time to answer OLAP queries, although some studies also minimize the update time. View selection is NP-Complete. Many approaches to the problem have been explored, including greedy algorithms, randomized search, genetic algorithms and A* search algorithm. Support /races /trusting /cuidado /new /geben /Newman /hansbrough's /tuo/ De /Howard /whales /warhawk's /time /Watson /Pig /extra /not/ boston's /drake's /hornet/ wijzigen /s /plats /break /ground /picking /season's Nighjhnntendo's /bobbie/ privacy /bovenaan /sui /or /gnet's /s /optimal/ Some aggregation functions can be computed for the entire OLAP cube by precomputing values for each cell, and then computing the aggregation for a roll-up of cells by aggregating these aggregates, applying a divide and conquer algorithm to the multidimensional problem to compute them efficiently. For example, the overall sum of a roll-up is just the sum of the sub-sums in each cell. Functions that can be decomposed in this way are called decomposable aggregation functions, and include COUNT, MAX, MIN, and SUM, which can be computed for each cell and then directly aggregated; these are known as self-decomposable aggregation functions. In other cases the aggregate function can be computed by computing auxiliary numbers for cells, aggregating these auxiliary numbers, and finally computing the overall number at the end; examples include AVERAGE (tracking sum and count, dividing at the end) and RANGE (tracking max and min, subtracting at the end). In other cases the aggregate function cannot be computed without analyzing the entire set at once, though in some cases approximations can be computed; examples include DISTINCT COUNT, MEDIAN, and MODE; for example, the median of a set is not the median of medians of subsets. These latter are difficult to implement efficiently in OLAP, as they require computing the aggregate fu ------------------------------ Date: Fri, 3 Nov 2023 17:44:37 +0000 From: "Raptor 8K Drone" Subject: Elevate Your Photography Game with the Raptor 8K Drone â Now Under $100! This email must be viewed in HTML mode. ------------------------------ End of alt.music.moxy-fruvous digest V14 #12523 ***********************************************