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Advanced WordPress Comment Management Through SQL

Without a doubt WordPress is the most popular PHP based CMS. Additionally WordPress offer the most popular commenting system, however due to popularity, commenting system is abused by spammers. It is not a secret that WordPress based websites and blogs leave a lot of footprints, that are used by spammers. Actually some of these footprints are integrated into some of the black hat spam applications like ScrapeBox or simply can be used with Google as advanced search operators. There are number of anti-spam extensions that can reduce levels of spam like Akismet, GASP, integrating captcha images, etc... However bulk deleting or deleting comments from particular name, date, URL, etc can be very difficult and I don't think that there is plug-in that can do this job. In this article, I will review some advanced techniques that can assist you with some time consuming tasks – deleting comments directly from database. IMPORTANT! Before you try any of these, please back-up your database, in case something go wrong! Your database may use different prefix, in our example we are using the default “wp_”, replace the prefix to match your database prefix. Delete All SPAM Comment Yes, there is in-build function of WordPress to...
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Non Clustered Indexes in SQL Server - I

In the previous two articles we looked into the structure and performance of a Clustered Index in the table. In this article we will look into another of the most fundamental indexes in SQL Server called Non Clustered Index and how the optimizer traverses the Non clustered index to find the desired piece of data. Clustered Index Structure: As we already know that a B Tree can have a root level,one or more intermediate level and a leaf level depending on the number of rows in an index. In a non-clustered index the root , intermediate and the leaf level contains index pages which hold index rows. The data in all these index rows are key values normally called as indexing keys and have a pointer to the next immediate intermediate level or the leaf level. Unlike the clustered indexes non clustered index  leaf levels contain pointers to the data pages in case the table is a heap table in form of a row ID (RID) compressing the file number, page number and the slot number or a clustering key in case the underlying table is a clustered table. Also the logical order does not match the physical order of the...
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