If you have a table that represents time-varying info, e.g. with From and To date/time columns, you have a few options with regards to the problem of overlapping dates:
1. Check for overlapping dates in the application layer.
2. Use an off-the-shelf product to generate the appropriate triggers, e.g. Oracle CDM*RuleFrame or Toon Koppelaars’ RuleGen.
3. Roll your own, in the database.
4. Use a different data model that can use a unique constraint.
5. Forget about it.
One reason it’s difficult is that this is an example of a cross-row constraint, i.e. one that cannot merely be checked for the current row by itself. Oracle supports a few cross-row constraints, i.e. Primary Key, Unique and Foreign Key constraints; but it doesn’t natively support arbitrary assertions, which would allow us to easily declare this sort of constraint.
The real challenge comes from the fact that Oracle is a multi-user system and concurrent sessions cannot see the uncommitted data from other sessions; so some form of serialization will be required to ensure that when one session wishes to insert/update the data for a particular entity, no other session is allowed to start working on the same entity until the first session commits (or issues a rollback).
The problem is not new; it’s been around for a long time, and tripped many a new (and old) programmer.
There are two problems with option #1 (code in the application layer): firstly, you have to repeat the code for each different type of client (e.g. you might have a Java UI on one side, as well as some batch script somewhere else); secondly, usually the programmer involved will not understand the concurrency problem mentioned above and will not take it into account.
Option #2 is probably the best, most of the time. The solution is implemented at the database level, and is more likely to work correctly and efficiently.
Option #4 (change the data model) involves not storing the From and To dates, but instead dividing up all time ranges into discrete chunks, and each row represents a single chunk of time. This solution is valid if the desired booking ranges are at predictable discrete ranges, e.g. daily. You can then use an ordinary unique constraint to ensure that each chunk of time is only booked by one entity at any one time. This is the solution described here.
Option #5 (forget about it) is also a viable option, in my opinion. Basically it entails designing the rest of the application around the fact that overlapping date ranges might exist in the table – e.g. a report might simply merge the date ranges together prior to output.
Option #3, where you implement the triggers yourself on the database, has the same advantage as Option #2, where it doesn’t matter which application the data is coming from, the constraint will hold true. However, you have to be really careful because it’s much easier to get it wrong than it is to get right, due to concurrency.
I hear you scoffing, “Triggers?!?”. I won’t comment except to refer you to this opinion, which I couldn’t say it better myself: The fourth use-case for Triggers.
There is another Option #3 using a materialized view instead of triggers; I’ll describe this alternative at the end of this post.
So, here is a small example showing how an overlapping date constraint may be implemented. It is intentionally simple to illustrate the approach: it assumes that the From and To dates cannot be NULL, and its rule for detecting overlapping dates requires that the dates not overlap at all, to the nearest second.
- Create the tables
CREATE TABLE room (room_no NUMBER NOT NULL ,CONSTRAINT room_pk PRIMARY KEY (room_no) ); CREATE TABLE room_booking (room_no NUMBER NOT NULL ,booked_from DATE NOT NULL ,booked_to DATE NOT NULL ,CONSTRAINT room_booking_pk PRIMARY KEY (room_no, booked_from) ,CONSTRAINT room_booking_fk FOREIGN KEY (room_no) REFERENCES room (room_no) );
- Create the validation trigger (note – I’ve used an Oracle 11g compound trigger here, but it could easily be rewritten for earlier versions by using two triggers + a database package):
CREATE OR REPLACE TRIGGER room_booking_trg FOR INSERT OR UPDATE OF room_no, booked_from, booked_to ON room_booking COMPOUND TRIGGER TYPE room_no_array IS TABLE OF CHAR(1) INDEX BY BINARY_INTEGER; room_nos room_no_array; PROCEDURE lock_room (room_no IN room.room_no%TYPE) IS dummy room.room_no%TYPE; BEGIN SELECT r.room_no INTO dummy FROM room r WHERE r.room_no = lock_room.room_no FOR UPDATE; END lock_room; PROCEDURE validate_room (room_no IN room.room_no%TYPE) IS overlapping_booking EXCEPTION; dummy CHAR(1); BEGIN -- check for overlapping date/time ranges BEGIN SELECT 'X' INTO dummy FROM room_booking rb1 ,room_booking rb2 WHERE rb1.room_no = validate_room.room_no AND rb2.room_no = validate_room.room_no AND rb1.booked_from != rb2.booked_from AND ( rb1.booked_from BETWEEN rb2.booked_from AND rb2.booked_to OR rb1.booked_to BETWEEN rb2.booked_from AND rb2.booked_to ) AND ROWNUM = 1; RAISE overlapping_booking; EXCEPTION WHEN NO_DATA_FOUND THEN -- good, no constraint violations NULL; END; EXCEPTION WHEN overlapping_booking THEN RAISE_APPLICATION_ERROR(-20000, 'Overlapping booking for room #' || room_no); END validate_room; PROCEDURE validate_rooms IS room_no room.room_no%TYPE; BEGIN room_no := room_nos.FIRST; LOOP EXIT WHEN room_no IS NULL; validate_room (room_no); room_no := room_nos.NEXT(room_no); END LOOP; room_nos.DELETE; EXCEPTION WHEN OTHERS THEN room_nos.DELETE; RAISE; END validate_rooms; BEFORE EACH ROW IS BEGIN -- lock the header record (so other sessions -- can't modify the bookings for this room -- at the same time) lock_room(:NEW.room_no); -- remember the room_no to validate later room_nos(:NEW.room_no) := 'Y'; END BEFORE EACH ROW; AFTER STATEMENT IS BEGIN validate_rooms; END AFTER STATEMENT; END room_booking_trg; /
That’s all you need. The trigger locks the header record for the room, so only one session can modify the bookings for a particular room at any one time. If you don’t have a table like “room” in your database that you can use for this purpose, you could use DBMS_LOCK instead (similarly to that proposed in the OTN forum discussion here).
It would not be difficult to adapt this example for alternative requirements, e.g. where the From and To dates may be NULL, or where the overlapping criteria should allow date/time ranges that coincide at their endpoints (e.g. so that the date ranges (1-Feb-2000 to 2-Feb-2000) and (2-Feb-2000 to 3-Feb-2000) would not be considered to overlap). You’d just need to modify the comparison in the query in validate_room to take these requirements into account.
Test case #1
INSERT INTO room (room_no) VALUES (101); INSERT INTO room (room_no) VALUES (201); INSERT INTO room (room_no) VALUES (301); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (101, DATE '2000-01-01', DATE '2000-01-02' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (101, DATE '2000-01-02', DATE '2000-01-03' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-02-01', DATE '2000-02-05' - 0.00001);
Expected: no errors
Test case #2
INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-02-01', DATE '2000-02-02' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-02-02', DATE '2000-02-04' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-02-03', DATE '2000-02-05' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-02-03', DATE '2000-02-06' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-01-31', DATE '2000-02-01'); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-01-31', DATE '2000-02-02' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-01-31', DATE '2000-02-06' - 0.00001); INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (201, DATE '2000-02-05' - 0.00001, DATE '2000-02-06' - 0.00001); UPDATE room_booking SET booked_to = '2000-01-02' - 0.00001 WHERE room_no = 101 AND booked_from = DATE '2000-01-02';
Expected: constraint violation on each statement
Test case #3
in session #1:
INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (301, DATE '2000-01-01', DATE '2000-02-01' - 0.00001);
in session #2:
INSERT INTO room_booking (room_no, booked_from, booked_to) VALUES (301, DATE '2000-01-15', DATE '2000-01-16' - 0.00001);
Expected: session #2 will wait until session #1 issues a COMMIT or ROLLBACK. If session #1 COMMITs, session #2 will then report a constraint violation. If session #2 rolls back, session #2 will complete without error.
The No-Trigger option #3: Materialized View
This is similar to a solution proposed by Rob Van Wijk. It uses a constraint on a materialized view to stop overlapping date ranges.
So, instead of the trigger, you would do something like this:
CREATE MATERIALIZED VIEW LOG ON room_booking WITH ROWID; CREATE MATERIALIZED VIEW room_booking_date_ranges REFRESH FORCE ON COMMIT AS SELECT 'X' AS dummy FROM room_booking rb1 ,room_booking rb2 WHERE rb1.room_no = rb2.room_no AND rb1.booked_from != rb2.booked_from AND ( rb1.booked_from BETWEEN rb2.booked_from AND rb2.booked_to OR rb1.booked_to BETWEEN rb2.booked_from AND rb2.booked_to ); ALTER TABLE room_booking_date_ranges ADD CONSTRAINT no_overlapping_dates_ck CHECK ( dummy = 'Z' );
The nice thing about this solution is that it is simpler to code, and seems more “declarative” in nature. Also, you don’t have to worry about concurrency at all.
The constraint is checked at COMMIT-time when the materialized view is refreshed; so it behaves like a deferred constraint, which may be an advantage for some scenarios.
I believe it may perform better than the trigger-based option when large volumes of data are inserted or updated; however it may perform worse than the trigger-based option when you have lots of small transactions. This is because, unfortunately, the query here cannot be a “REFRESH FAST ON COMMIT” (if you know how this could be changed into a REFRESH FAST MV, please let me know!).
What do you think? If you see any potential issues with the above solutions please feel free to comment.
EDIT 30/8: added some more test cases