I am assuming by CST and CDT you mean North American Central Standard Time and Central Daylight Time such as observed in Rainy River, Chicago and Mexico (the city) among other places. More on this ambiguity later.
For 99.977 % of all times it is fairly easy to know whether they are standard time or daylight saving time. Only times from the two hours around the transition from DST to standard time are ambiguous, and as said in the comments, there is no way to know from the time stamp which is the right way to resolve this ambiguity.
java.time
This answer will take you as far into the future as possible without taking you away from Java 7. You can still use java.time, the modern Java date and time API also known as JSR-310. It has been backported to Java 6 and 7 in the ThreeTen Backport, so it’s a matter of getting this and adding it to your project (just until one day you upgrade to Java 8 or later).
I am taking your word for your date-time string format. What we can do with it:
DateTimeFormatter storedFormatter = new DateTimeFormatterBuilder()
.parseCaseInsensitive()
.appendPattern("d-MMM-uu hh.mm.ss.SSSSSSSSS a")
.toFormatter(Locale.US);
ZoneId zone = ZoneId.of("America/Mexico_City");
String storedTime = "22-NOV-17 05.33.51.937000000 PM";
LocalDateTime dateTime = LocalDateTime.parse(storedTime, storedFormatter);
// First shot -- will usually be correct
ZonedDateTime firstShot = ZonedDateTime.of(dateTime, zone);
System.out.println(firstShot);
This prints:
2017-11-22T17:33:51.937-06:00[America/Mexico_City]
You can see that it picked an offset of -06:00, which means that the time is in standard time (CDT is -05:00).
Since your month abbreviation is in all uppercase, I needed to tell the formatter to parse case insensitively. If America/Mexico_City time zone is not appropriate for you, pick a better one, for example America/Rainy_River or America/Chicago.
Ambiguous times in fall
I once had to parse a log file containing date-times without indication of standard time and summer time (DST). Since we assumed time would always move forward, we failed at the transition to standard time, and one hour of the log file was lost. In this case we might have solved it using the information that times were in summer time until the leap backward by an hour, from there they were in standard time. You may want to think about whether something similar will be possible for you.
Other options include just taking DST time every time — this is what the above code will do — or taking an average and living with the error thus introduced.
We can at least detect the ambiguous times:
ZoneOffset standardOffset = ZoneOffset.ofHours(-6);
ZoneOffset dstOffset = ZoneOffset.ofHours(-5);
// check if in fall overlap
ZonedDateTime standardDateTime
= ZonedDateTime.ofLocal(dateTime, zone, standardOffset);
ZonedDateTime dstDateTime
= ZonedDateTime.ofLocal(dateTime, zone, dstOffset);
if (! standardDateTime.equals(dstDateTime)) {
System.out.println("Ambiguous, this could be in CST or CDT: " + dateTime);
}
Now if the string was 29-OCT-17 01.30.00.000000000 AM, I get the message
Ambiguous, this could be in CST or CDT: 2017-10-29T01:30
ZonedDateTime.ofLocal() will use the provided offset for resolving the ambiguity if it is a valid offset for the date-time and zone.
Non-existing times in the spring
Similarly we can detect if your date-time falls in the gap where the clock is moved forward in the transition to DST:
// Check if in spring gap
if (! firstShot.toLocalDateTime().equals(dateTime)) {
System.out.println("Not a valid date-time, in spring gap: " + dateTime);
}
This can give a message like
Not a valid date-time, in spring gap: 2018-04-01T02:01
I suggest you can safely reject such values. They cannot be correct.
Avoid the three letter time zone abbreviations
CST may refer to Central Standard Time (in North and Central America), Australian Central Standard Time, Cuba Standard Time and China Standard Time. CDT may mean Central Daylight Time or Cuba Daylight Time. The three and four letter abbreviations are not standardized and are very often ambiguous. Prefer time zone IDs in the region/city format, for example America/Winnipeg.
