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There is a big assumption being made with the code above: no errors occur . But, of course, errors are always possible, and so we need a way to handle those errors . This is what the exception handling constructs and mechanisms are all about and why we need them as opposed to having methods that return true/false to indicate success/failure the way that Win32 and COM functions do . In addition to code composability, we are productive due to all kinds of great features provided by our compilers . For example, the compiler implicitly: The ConvertIList method specifies two type parameters in which the T parameter is constrained by the TBase type parameter . This means that whatever type argument is specified for T, the type argument must be compatible with whatever type argument is specified for TBase . Here is a method showing some legal and illegal calls to ConvertIList: Allowing Pop-ups from Specific Sites
Any Pending (not completed in Outlook) Past (completed in Outlook) Pending (open in Microsoft Dynamics CRM) Past (completed or canceled in Microsoft Dynamics CRM) Pending (open in Microsoft Dynamics CRM) Past (completed or canceled in Microsoft Dynamics CRM) Pending (open in Microsoft Dynamics CRM) One such situation is when you need to insert or modify large volumes of data and, for practical reasons, you split it into batches, modifying one subset of the data at a time. For example, purging historic data might involve deleting millions of rows of data. Unless the target table is partitioned and you can simply drop a partition, the purging process requires a DELETE statement. Deleting such a large set of rows in a single transaction has several drawbacks. A DELETE statement is fully logged, and it will require enough space in the transaction log to accommodate the whole transaction. During the delete operation (which can take a long time), no part of the log from the oldest open transaction up to the current point can be overwritten. Furthermore, if the transaction breaks in the middle for some reason, all the activity that took place to that point will be rolled back, and this will take a while. Finally, when many rows are deleted at once, SQL Server might escalate the individual locks held on the deleted rows to an exclusive table lock, preventing both read and write access to the target table until the DELETE is completed. It makes sense to break the single large DELETE transaction into several smaller ones small enough to avoid lock escalation (typically, a few thousand rows per transaction) and to allow recycling of the transaction log. You can easily verify that the number you chose doesn t cause lock escalation by testing a DELETE with the TOP option while monitoring Lock < previous page
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