Deprecation notice After encountering numerous problems building the jOOQ-refaster module in various JDK versions and after receiving no feedback from the community about this feature, we have decided to remove it again in jOOQ 3.15: https://github.com/jOOQ/jOOQ/issues/10803 Starting with jOOQ 3.13, we're offering a new module called jOOQ Refaster, which provides refaster templates for automatic API … Continue reading Use the jOOQ-Refaster Module for Automatic Migration off of Deprecated jOOQ API
jOOQ 3.13 Released with More API and Tooling for DDL Management
jOOQ 3.13 has been released with CockroachDB support, much more API and tooling for DDL management, and SQL:2011 temporal table support Starting with this release, we will further embrace our support for parsing, translating, executing, and now also interpreting DDL statements. The driving force is better code generation support, but in the future, also better … Continue reading jOOQ 3.13 Released with More API and Tooling for DDL Management
Stop Mapping Stuff in Your Middleware. Use SQL’s XML or JSON Operators Instead
It's been a while since I've ranted on this blog, but I was recently challenged by a reddit thread to write about this topic, so here goes... So, you're writing a service that produces some JSON from your database model. What do you need? Let's see: Read a book on DDD Read another book on … Continue reading Stop Mapping Stuff in Your Middleware. Use SQL’s XML or JSON Operators Instead
A Guide to SQL Naming Conventions
One of Java's big strengths, in my opinion, is the fact that most naming conventions have been established by the creators of the language. For example: Class names are in PascalCase Member names are in camelCase Constants are in SNAKE_CASE If someone does not adhere to these conventions, the resulting code quickly looks non-idiomatic. What … Continue reading A Guide to SQL Naming Conventions
Dogfooding in Product Development
Dogfooding, or eating your own dog food, is a practice that all product developers should implement all the time. According to wikipedia: Dogfooding, occurs when an organization uses its own product. This can be a way for an organization to test its products in real-world usage. Hence dogfooding can act as quality control, and eventually … Continue reading Dogfooding in Product Development
A Quick Trick to Make a Java Stream Construction Lazy
One of the Stream APIs greatest features is its laziness. The whole pipeline is constructed lazily, stored as a set of instructions, akin to a SQL execution plan. Only when we invoke a terminal operation, the pipeline is started. It is still lazy, meaning that some operations may be short circuited. Some third party libraries … Continue reading A Quick Trick to Make a Java Stream Construction Lazy
How to Map MySQL’s TINYINT(1) to Boolean in jOOQ
MySQL 8 does not yet support the BOOLEAN type as specified in the SQL standard. There is a DDL "type" called BOOL, which is just an alias for TINYINT: create table t(b bool); select table_name, column_name, data_type, column_type from information_schema.columns where table_name = 't'; The above produces: TABLE_NAME|COLUMN_NAME|DATA_TYPE|COLUMN_TYPE| ----------|-----------|---------|-----------| t |b |tinyint |tinyint(1) | Notice … Continue reading How to Map MySQL’s TINYINT(1) to Boolean in jOOQ
What’s Faster? COUNT(*) or COUNT(1)?
One of the biggest and undead myths in SQL is that COUNT(*) is faster than COUNT(1). Or was it that COUNT(1) is faster than COUNT(*)? Impossible to remember, because there's really no reason at all why one should be faster than the other. But is the myth justified? Let's measure! How does COUNT(...) work? But … Continue reading What’s Faster? COUNT(*) or COUNT(1)?
Oracle’s BINARY_DOUBLE Can Be Much Faster Than NUMBER
Using the right data type for some calculation sounds like some obvious advice. There are many blogs about using temporal data types for temporal data, instead of strings. An obvious reason is data integrity and correctness. We don't gain much in storing dates as 2019-09-10 in one record, and as Nov 10, 2019 in the … Continue reading Oracle’s BINARY_DOUBLE Can Be Much Faster Than NUMBER
Using DISTINCT ON in Non-PostgreSQL Databases
A nice little gem in PostgreSQL's SQL syntax is the DISTINCT ON clause, which is as powerful as it is esoteric. In a previous post, we've blogged about some caveats to think of when DISTINCT and ORDER BY are used together. The bigger picture can be seen in our article about the logical order of … Continue reading Using DISTINCT ON in Non-PostgreSQL Databases