RIGHT JOIN is an esoteric feature in the SQL language, and hardly ever seen in the real world, because almost every RIGHT JOIN can just be expressed as an equivalent LEFT JOIN. The following two statements are equivalent: -- Popular SELECT c.first_name, c.last_name, p.amount FROM customer AS c LEFT JOIN payment AS p ON c.customer_id … Continue reading Think About SQL MERGE in Terms of a RIGHT JOIN
Tag: PostgreSQL
An Efficient Way to Check for Existence of Multiple Values in SQL
In a previous blog post, we've advertised the use of SQL EXISTS rather than COUNT(*) to check for existence of a value in SQL. I.e. to check if in the Sakila database, actors called WAHLBERG have played in any films, instead of: SELECT count(*) FROM actor a JOIN film_actor fa USING (actor_id) WHERE a.last_name = … Continue reading An Efficient Way to Check for Existence of Multiple Values in SQL
How to Turn a List of Flat Elements into a Hierarchy in Java, SQL, or jOOQ
Occasionally, you want to write a SQL query and fetch a hierarchy of data, whose flat representation may look like this: SELECT id, parent_id, label FROM t_directory; The result might be: |id |parent_id|label | |---|---------|-------------------| |1 | |C: | |2 |1 |eclipse | |3 |2 |configuration | |4 |2 |dropins | |5 |2 |features | … Continue reading How to Turn a List of Flat Elements into a Hierarchy in Java, SQL, or jOOQ
The Performance Impact of SQL’s FILTER Clause
I've found an interesting question on Twitter, recently. Is there any performance impact of using FILTER in SQL (PostgreSQL, specifically), or is it just syntax sugar for a CASE expression in an aggregate function? https://twitter.com/Ivan73965858/status/1622487080088600576 As a quick reminder, FILTER is an awesome standard SQL extension to filter out values before aggregating them in SQL. … Continue reading The Performance Impact of SQL’s FILTER Clause
LATERAL is Your Friend to Create Local Column Variables in SQL
The standard SQL WITH clause has been tremendously helpful in structuring SQL queries. Instead of nesting everything in unreadable derived tables like this: SELECT actor_id, name, COUNT(*) FROM ( SELECT actor_id, first_name || ' ' || last_name AS name FROM actor ) AS a JOIN film_actor AS fa USING (actor_id) GROUP BY actor_id, name ORDER … Continue reading LATERAL is Your Friend to Create Local Column Variables in SQL
How to Plot an ASCII Bar Chart with SQL
No need for expensive Tableau subscriptions. Ditch Microsoft Excel. Just use native PostgreSQL to quickly visualise your data! Here's an idea I had for a while. As you may know, jOOQ can produce fancy charts from your jOOQ results. But that requires you use jOOQ, and you may not be using jOOQ, because you're not … Continue reading How to Plot an ASCII Bar Chart with SQL
The Best Way to Call Stored Procedures from Java: With jOOQ
jOOQ is mainly known for its powerful type safe, embedded, dynamic SQL capabilities that are made available through code generation. However, a secondary use case of code generation is to use it for stored procedures (possibly exclusively for stored procedures). Stored procedures are powerful ways of moving complex data processing logic to the server. This … Continue reading The Best Way to Call Stored Procedures from Java: With jOOQ
3.17.0 Release with Computed Columns, Audit Columns, Pattern Matching, Reactive Transactions and Kotlin Coroutine Support
This release contiues the work from previous releases around more sophisticated SQL transformation capabilities, including: Client side computed columns for both read and write operationsAudit columnsPattern matching SQL transformationsMore implicit JOIN capabilities Client side computed columns A ground breaking new core feature available in all commercial distributions isthe new client side computed columns feature, building … Continue reading 3.17.0 Release with Computed Columns, Audit Columns, Pattern Matching, Reactive Transactions and Kotlin Coroutine Support
The Performance of Various To-Many Nesting Algorithms
It's been a while since jOOQ 3.15 has been released with its revolutionary standard SQL MULTISET emulation feature. A thing that has been long overdue and which I promised on twitter a few times is to run a few benchmarks comparing the performance of various approaches to nesting to-many relationships with jOOQ. This article will … Continue reading The Performance of Various To-Many Nesting Algorithms
Setting the JDBC Statement.setFetchSize() to 1 for Single Row Queries
An interesting hint by Vladimir Sitnikov has made me think about a new benchmark for jOOQ: https://twitter.com/lukaseder/status/1407662449331949568 The benchmark should check whether single row queries should have a JDBC Statement.setFetchSize(1) call made to them by default. The Javadoc of the method says: Gives the JDBC driver a hint as to the number of rows that … Continue reading Setting the JDBC Statement.setFetchSize() to 1 for Single Row Queries
