Database Key Generation in Java Applications

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Database Key Generation in Java Applications

September 3rd, 2008 by Scott Selikoff

All JDBC programmers at one time or another have had to deal with key generation for new records, or more precisely, how to retrieve keys for newly created records. This article discusses some of the techniques and limitations offered to Java JDBC programmers.


  • Unique Keys

Most (good) database systems assign a unique key, usually a large number, to every record in the database. For example, a user “Bob Jones” might have a User Id associated with the record of 808182313713. This key is unique for Bob and is a lot easier to pass around a system then Bob’s full name, since there may be other Bob Jones’s in the system. We could spend time discussing Natural Keys, although I would argue there is no such thing as natural keys. As an example, Bob’s social security number might seem like a natural key since it is unique to Bob but it may be the case Bob is a visiting foreigner (or the application is deployed outside the country) in which a US social security number is not applicable. Also, it’s been reported the government has been known to recycle social security numbers, as well as the fact that people can be issued new social security numbers during their lifetime. Even if unique natural keys did exist – e-mail for example – what if a user wants to change their address down the road?

This leads us to our second requirement of unique keys: Unique keys should not change throughout the life of the system. Changing unique keys is often an extremely difficult, highly risk process. A third, less followed, requirement is that unique keys should be private and only used internally by the application server. This is a huge boon to security and prevents users from attacking the system. In the case the system does need to expose a key, such as an eBay item number found in the URL of the auction, the system may create two keys: an Internal Id that is used for table relations within a database, and an External Id used to perform lookups on behalf of the user. The key here is that the External Id the user sees only exists in one record, whereas the Internal Id is used throughout the system to connect different records.

For the purpose of this article, we’ll assume key generation is the common approach of assigning long integers to each record in a table. In most database systems, this corresponds to the BIGINT type.

Helpful Advice: Always use the largest integer type the database has to offer for unique keys – numeric wrap-around is something to be concerned about, especially on smaller data types.

  • Defining the Problem

Most systems generate keys sequentially starting with a low number such as 1000. Why? Well, for starters it makes it easy to find new unused key value. Just find the max value of the table, and any value above this will be an unused available key. You could randomly generate a key, but then creating a new key would be a time consuming processing of generating a random number that has not been used.

Now, let’s say a user is in the process of creating a new record in your system. For each user record, you also have a set of postal addresses. For example, Bob may be purchasing items on NewEgg and have a home address and a work address. Furthermore, Bob enters his two addresses at the time he creates his account, so the application server receives the information to create all 3 records at once. In such a situation, you would normally have 3 records: 1 user record for Bob and 2 address records. You could add the address info in the user table, although then you have to restrict the number of addresses Bob can have and/or have a user table with a lot of extra columns.

Inserting Bob into the user table is straight forward enough, but there is a problem when you go to insert users into the address table, namely that you need Bob’s newly generated User Id in order to insert any records into the address table. After all, you can’t insert addresses without being connected to a specific user, lest chaos ensue in your data management system.

Most database systems provide a technique for the database to create keys for you in the event you do not specify them. In this situation, the first insert would leave the User Id for Bob as blank, or more precisely null, and the database would fill in a new value on insertion. The problem is the database isn’t really obligated to tell you what this newly created value is. The rest of this article will be devoted to discussing how you can get this generated key in your application.

  • Technique 1: Get the max id

Probably the most common approach is the quick and dirty one; perform a select query immediately after your insert and retrieve the max value:

SELECT max(id) FROM users

The good: In a lot of systems this actually works pretty well. It’s easy to implement and is extremely database independent.
The bad: It’s extremely risky in high concurrency environments. For example, if two users perform inserts at nearly the same time, they will both get the same max value from this query, leading to a huge breach in security (both users may have access to one of the users records if the application server returns the same id). There are ways to set your transaction isolation level to avoid problems like this, but that can be tricky and often requires more skill and experience than someone implementing this solution regularly is likely to have.

Also, you have to be *very* sure the system always creates keys strictly in ascending order. A database system that reused old or skipped key values would be incompatible with this approach.

  • Technique 2: JDBC to the Rescue!

Many JDBC programmers are unaware that there is built-in JDBC method for retrieving the newly generated keys immediately after an insert. It is appropriately named getGeneratedKeys() and can be used as follows:

Connection con = // connect to database
final PreparedStatement ps = con.prepareStatement("INSERT INTO users (...) VALUES (...)");
final int insertStatus = ps.executeUpdate();
int newKey = -1;
if(insertStatus == 1) {
     final ResultSet rs = ps.getGeneratedKeys();
     if( {
          newKey = rs.getInt(1);
          if( {
               // Probably should throw some exception if rs returns a second, unexpected record
     } else {
          // Probably should throw some exception if no generated keys created
} else {
     // Definitely should throw an error if insert failed
System.out.println("The key value for the newly created record is: "+newKey);

A reminder: JDBC starts with 1 (instead of 0) for accessing columns based on an index number.

The good: Don’t need to write any special or tricky logic to get the key. Works in systems that use ascending and non-ascending key value generation. No risk of getting the wrong key value even if you fail to set transaction or isolation levels properly.
The bad: Not supported by all JDBC drivers. Need to test it out in your real system to verify it works before relying on it.

  • Technique 3: Application Server Controlled Keys

One approach used in most large J2EE systems is to build a key generation service within the application tier. In this manner, all generated keys are created ahead of time by the application server without the use of any database-specific features. In the example above, the system would generate all the keys for the user and addresses before the first insert even occurs. Then it would insert the 3 records, one after another, using the keys it had at the start of the service. Keep in mind, the order of insert still matters, i.e. you can’t insert an address for a user that does not yet exist; but in this case, you don’t need to stop after the first insert to figure out information for the next insert.

Such a key generation module would have to be application-wide (static) and thread safe to prevent two requests from getting the same key at the same time. Also, such a system would have to be fault tolerant; if the system crashes it should not reassign any of the same keys after the next restart.

Often this is implemented with a database table that keeps track of the most recently assigned key for each record. To make the service perform well, keys are often released in blocks. For example, the system might say “The last key used was 4100, and I’m going to request 4101-4200”. In this manner the system would update the database record for that table to 4200 and only change this value when it used up all 100 keys in memory. It’s fault tolerant because even if not all keys from 4101-4200 are used, if the system crashes, it knows it can just request 4201-4300 next time.

The good: Performs better than any of the other solutions since it takes the load off of the database entirely. All inserts can be performed immediately without requesting information from the database in between inserts. Safer than any of the solutions because its is 100% database independent. Supports composite keys and distributed database systems.
The bad: Requires the most overhead of any of the solutions since you need to implement a server wide key generation tool. Requires the application server to know the name of each table (or some reference to each table) to track the key generation values for each table. Also, you could skip a lot of keys (sparse key range) if your system restarts frequently, although servers shouldn’t be restarting frequently! Lastly, it tends to require an experienced developer to implement properly (prevent errors) and perform well (using blocking properly).

  • Technique 4: Database-specific techniques

Lastly, you may want to rely on database-specific techniques. For example, Oracle allows you to write queries such as:

INSERT INTO Users (...) VALUES (...) RETURNING (id) INTO newUserId

In this case you would perform an executeQuery() instead of an executeUpdate(), so that the results of the insert could be read in a Result Set.

There are numerous other database-specific techniques for retrieving newly generated keys, but since I advocate against database-specific code in Java applications, I’ll leave a more detailed discussion for someone else.

The good: It’s safer than technique 1 since it works in systems with non-sequential keys.
The bad: It’s database-specific. Not only that but as shown above, all of your insert statements would be database specific. Would make moving the code to another database system very difficult (often impossible).

  • Final Thoughts

Generally, for smaller systems Technique #2 using getGeneratedKeys() is the best solution. Larger systems with composite key generation or distributed databases often require Technique #3 for an application controlled key generator.

As for the other two approaches, I would strongly advise against ever using Technique #4, lest you want to give future developers of your source code a huge headache in management and portability. Lastly, Technique #1 is sometimes safe to use, especially in single threaded systems, although is often evidence of a beginner JDBC developer.


Comment from Avi Abrami
Posted: September 4, 2008 at 12:13 am

Regarding technique 4: Database-specific techniques, how often does the database server get changed? May be a moot argument, no?


Comment from scott
Posted: September 4, 2008 at 2:04 am

Actually I’ve changed databases on a number of projects. It does happen fairly often. Also, its a little bit like the chicken and the egg paradox. If you use a ton of database specific features, then you’re less likely to be able to change database systems. But then if you consign yourself to never changing databases, you’re more likely to fall into the trap of depending on database specific features. In short, its rarely a good practice to depend entirely on database specific features in modern programming world.

Comment from JLB
Posted: October 8, 2008 at 8:26 pm

In Technique 2, shouldn’t we use the Connection.prepareStatement(String, String[]) and specify the column names of the keys? Oracle requires the column names (see MySQL lets you use prepareStatement(String, Statement.RETURN_GENERATED_KEYS) as well. But if you use the explicit column names, you should have code that works for at least Oracle and MySQL.

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