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StringToDate() converts a string value containing a date into a DateTime value. It understands that an empty String should be converted to either the smallest or the largest date, based on an optional parameter. It also handles translation of shortcut values to valid date values. The characters ., +, and correspond to today, tomorrow, and yesterday, respectively. Additionally, the values t, today, tom, tomorrow, y, and yesterday work in a similar manner. These text values are defined in the project s Resource.resx file, and so are subject to localization for other languages. Here s the code: Public Shared Function StringToDate(ByVal value As String) As Date Return StringToDate(value, True) End Function Public Shared Function StringToDate( _ ByVal value As String, ByVal emptyIsMin As Boolean) As Date If Len(value) = 0 Then If emptyIsMin Then Return Date.MinValue Else Return Date.MaxValue End If ElseIf IsDate(value) Then Return CDate(value) Else Select Case LCase(Trim(value)) Case My.Resources.SmartDateT, My.Resources.SmartDateToday, "." Return Now Case My.Resources.SmartDateY, My.Resources.SmartDateYesterday, "-" Return DateAdd(DateInterval.Day, -1, Now) Case My.Resources.SmartDateTom, My.Resources.SmartDateTomorrow, "+" Return DateAdd(DateInterval.Day, 1, Now) Case Else Throw New ArgumentException(My.Resources.StringToDateException) End Select End If End Function Given a String of nonzero length, this function attempts to parse it directly to a DateTime field. If that fails, then the various shortcut values are checked. If that fails as well, then an exception is thrown to indicate that the String value couldn t be parsed into a date.

Note You can find the UDP server and client sample projects in this chapter s directory in the Sockets

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If we have a REPEATABLE READ isolation, the results from a given query must be consistent with respect to some point in time. Most databases (not Oracle) achieve repeatable reads via the use of row-level shared read locks. A shared read lock prevents other sessions from modifying data that we have read. This, of course, decreases concurrency. Oracle opted for the more concurrent, multi-versioning model to provide read-consistent answers. In Oracle, using multi-versioning, we get an answer that is consistent with respect to the point in time the query began execution. In other databases, using shared read locks, we get an answer that is consistent with respect to the point in time the query completes that is, when we can get the answer at all (more on this in a moment). In a system that employs a shared read lock to provide repeatable reads, we would observe rows in a table getting locked as the query processed them. So, using the earlier example, as our query reads the ACCOUNTS table, it would leave shared read locks on each row, as shown in Table 7-5. Table 7-5. Timeline 1 in Non-Oracle Database Using READ REPEATABLE Isolation

SmartDate can translate dates the other way as well, such as converting a DateTime field into a String and retaining the concept of an empty date. Again, an optional parameter controls whether an empty date represents the smallest or the largest possible date. Another parameter controls the format of the date as it s converted to a String. Table 5-5 illustrates the results for various inputs. Table 5-5. Results of the DateToString Method Based on Various Inputs

Reads row 1. Sum = $500.00 so far. Block 1 has a shared read lock on it. Reads row 2. Sum = $740.25 so far. Block 2 has a shared read lock on it.

True (default) False True (default) False True or False (ignored)

Attempts to update row 1 but is blocked. Transaction is suspended until it can obtain an exclusive lock. Reads row N. Sum = . . .

This section teaches you how you can obtain information about the network capabilities of your device and configure your device programmatically.

Updates row 1 and puts an exclusive lock on this block. Row 1 now has $100.00. Updates row 342,023 and puts an exclusive lock on this block. Row 342,023 now has $500.00. Commits transaction.

Result of DateToString()

Table 7-5 shows that we now get the correct answer, but at the cost of physically blocking one transaction and executing the two transactions sequentially. This is one of the side effects of shared read locks for consistent answers: readers of data will block writers of data. This is in addition to the fact that, in these systems, writers of data will block readers of data. Imagine if automatic teller machines (ATMs) worked this way in real life. So, you can see how shared read locks would inhibit concurrency, but they can also cause spurious errors to occur. In Table 7-6, we start with our original table, but this time with the goal of transferring $50.00 from account 987 to account 123. Table 7-6. Timeline 2 in Non-Oracle Database Using READ REPEATABLE Isolation

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