Search results
Results from the WOW.Com Content Network
Full table scan occurs when there is no index or index is not being used by SQL. And the result of full scan table is usually slower that index table scan. The situation is that: the larger the table, the slower of the data returns. Unnecessary full-table scan will lead to a huge amount of unnecessary I/O with a process burden on the entire ...
To process this statement without an index the database software must look at the last_name column on every row in the table (this is known as a full table scan). With an index the database simply follows the index data structure (typically a B-tree) until the Smith entry has been found; this is much less computationally expensive than a full ...
Tables grow automatically in response to data creation. Tables have one or more indexes. There must be at least one clustered index for record data. When no clustered index is defined by the application, an artificial index is used which orders and clusters records by the chronological order of record insertion.
The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]
A cell on a different sheet of the same spreadsheet is usually addressed as: =SHEET2!A1 (that is; the first cell in sheet 2 of the same spreadsheet). Some spreadsheet implementations in Excel allow cell references to another spreadsheet (not the currently open and active file) on the same computer or a local network.
This plan table will return the cost and time for executing a query. Oracle offers two optimization approaches: CBO or Cost Based Optimization; RBO or Rule Based Optimization; RBO is slowly being deprecated. For CBO to be used, all the tables referenced by the query must be analyzed. To analyze a table, a DBA can launch code from the DBMS_STATS ...
Consider a set of points in some space to be clustered. Let ε be a parameter specifying the radius of a neighborhood with respect to some point. For the purpose of DBSCAN clustering, the points are classified as core points, (directly-) reachable points and outliers, as follows:
The standard algorithm for hierarchical agglomerative clustering (HAC) has a time complexity of () and requires () memory, which makes it too slow for even medium data sets. . However, for some special cases, optimal efficient agglomerative methods (of complexity ()) are known: SLINK [2] for single-linkage and CLINK [3] for complete-linkage clusteri