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Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [ 1 ]
For example, removing duplicates using distinct may be slow in the database; thus, it makes sense to do it outside. On the other side, if using distinct significantly (x100) decreases the number of rows to be extracted, then it makes sense to remove duplications as early as possible in the database before unloading data.
By allowing a false positive rate for the duplicates, the communication volume can be reduced further as the PEs don't have to send elements with duplicated hashes at all and instead any element with a duplicated hash can simply be marked as a duplicate. As a result, the false positive rate for duplicate detection is the same as the false ...
These examples, one from mathematics and one from natural language, illustrate the concept of vacuous truths: "For any integer x, if x > 5 then x > 3." [11] – This statement is true non-vacuously (since some integers are indeed greater than 5), but some of its implications are only vacuously true: for example, when x is the integer 2, the statement implies the vacuous truth that "if 2 > 5 ...
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The following is a list of the 172 most common word duplicates (number after word is count of occurrences) extracted from a search of all English Wikipedia articles existing on 21 February 2006. Most punctuation was automatically removed and so the count is unlikely to be 100% accurate.
1. Mouse over the folder you want to add a subfolder to. 2. Click the Folder Options icon . 3. Select Create subfolder. 4. Enter a new subfolder name. 5. Click the Save icon.
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