Combining Java and SQL: The Main Points

combining java and sql

Why Mixing Java and SQL in the First Place

In order to make their codes much better today, many Java developers and programmers are mixing together both imperative and object-oriented concepts into one broth. And although it’s proven helpful in a large number of ways, a developer’s ease and success in doing so depend on quite a number of factors:

  • Their level of skills.
  • Their dogma, or in simpler terms, their ability to use the same pattern everywhere having given each of these patterns a specific name.

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But when it comes to Java developers taking up SQL, everything appears to go in a u-turn! That’s because SQL language is declarative; meaning that it has no association to both imperative or object-oriented school of thought. But how to connect Java program to SQL database? Let’s dig a little further. For example, it can be quite simple to write a query in SQL. But, you can’t really express it correctly. That’s because there are some common and repetitive errors we make when writing SQL. It could be either through jOOQ or JDBC. So here are a few things you need to be cautious about when connecting java program to SQL database and using Java SQL editor which is a great addition to any development kit, as well as Smart Connect.

The Niceties of Combining Java and SQL

1. NULL Tends to Fizzle out of Your Mind

That’s because NULL goes also by the name UKNOWN. Truth be told, if it only went by the name unknown, it would be much simpler to grasp. But that’s not the case! In fact, most developers get confused when row value expressions are used with NULL predicates. And to make it even more confusing, you can easily misinterpret the definition of NULL especially in NOT IN anti-joins.

So how do you remedy this? Well, practice makes perfect! You need to consistently train yourself to always have NULL at the FRONT of your mind whenever you’re writing SQL.

2. Data Processing in Java Memory

Very few Java developers have a strong grasp of SQL to actually make the connection Java SQL. They may know one or two things here or there, but generally, they aren’t that well endowed. For example, plenty of Java developers like to load SQL data to memory first, then transform the data into a suitable collection type, before proceeding to execute not so tidy maths on the collections. So what can you as a developer do to get this right? Well, you can take this always as a precaution. Every time you execute a data-based algorithm in Java, just ask yourself this question; Is there a way I can make the database perform this work for me?

3. The UNION and UNION ALL Confusion

We know; it’s tough that UNION and UNION ALL are not one and the same thing! One word difference can really be frustrating. In fact, it would have been much easier if the SQL standard had been established for this type of support.

  • UNION (allows or permits duplicates)
  • UNION DISTINCT (eliminates or removes duplicates)

To build on this further, the removal of the duplicate is quite unnecessary and at times, may not be the right move. It is also quite a slow process that results in massive upsets with multiple columns. So what can you do to counter this error? The rule of thumb is that every time you think of UNION, you should assume you were thinking of UNION ALL all along.

4. The Mistake of Using JBC Pagination When It Comes to Large Results

Most databases have their own solid way of paginating results in an orderly manner. This can be through OFFSET, START AT…etc. In the case that there is no support for the mentioned clauses, you can end up in a real problem. The best thing to do in such situations is to use a tool such as JOOQ that can easily create the clauses.

5. Joining Data in Java Memory

Some developers dread the idea of using JOIN when it comes to writing SQL. There is an inherent belief among developers that JOIN is really slow. This can be true in the event that a cost-based optimiser executes a nested loop, then resulting in the loading of complete tables to the database memory; ultimately leading to a joined table source.

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But what are the odds of this happening? Rare. MERGE JOIN and HASH JOIN are generally very fast when used with the right metadata. But many programmers still struggle with this issue. We advise that you get into the habit of expressing queries in a single statement whenever you’re selecting from a large number of tables.

6. The Removal of Duplicates from a Cartesian Product Using DISTINCT or UNION

When you’re doing a lot of joining, it can be easy to lose yourself when trying to keep track of the relations that are involved in your SQL statement. This can happen especially when they are multiple foreign relationships in question, and you can forget to add or even use the JOIN predicate. In turn, most developers turn to the DISTINCT option; which is wrong in the following ways.

  • It may solve the small glitches, but not the actual problem.
  • It is quite slow for large sets of results with multiple columns
  • It is quite slow for Cartesian products that have stored a lot of data in their memory.

To remedy this, always make sure to reassess your JOIN predicates whenever you receive unwanted predicates.

7. Failing to Use the MERGE Statement

Although this does not really count as a mistake, some of us rarely use the MERGE statement or do not use it at all. But MERGE is quite a powerful tool; specifically in databases like the SQL server. So we encourage you to use it more frequently.

That being said, always make sure to avoid these simple errors when merging Java and SQL. Not only will you be more efficient, but it will also make the combination process so much easier. To polish your code, you are free to get some java programming help at any time.

To find out more tips on SQL and Java connection, or how to use the Java SQL editor efficiently, our professionals will be here to help and guide you through every step!