12/9/2023 0 Comments Case statement in postgresql![]() ![]() How to Write a Derived Table in jOOQ February 24, 2023.How to use jOOQ’s Converters with UNION Operations March 2, 2023.3.18.0 Release with Support for more Diagnostics, SQL/JSON, Oracle Associative Arrays, Multi dimensional Arrays, R2DBC 1.0 March 8, 2023.How to Turn a List of Flat Elements into a Hierarchy in Java, SQL, or jOOQ March 24, 2023.How to Pass a Table Valued Parameter to a T-SQL Function with jOOQ April 25, 2023.How to Generate Package Private Code with jOOQ’s Code Generator June 28, 2023.A Beginner's Guide to the True Order of SQL Operations.The Many Different Ways to Fetch Data in jOOQ.Using IGNORE NULLS With SQL Window Functions to Fill Gaps.Faster SQL Pagination with jOOQ Using the Seek Method.How to Write a Multiplication Aggregate Function in SQL.How SQL DISTINCT and ORDER BY are Related.Selecting all Columns Except One in PostgreSQL.Say NO to Venn Diagrams When Explaining JOINs.SQL IN Predicate: With IN List or With Array? Which is Faster?.Join 2,144 other subscribers Top Posts & Pages The benchmark technique is described here. RAISE INFO 'Run %, Statement 2: %', r, (clock_timestamp() - v_ts) ![]() SUM(CASE WHEN rating = 'PG' THEN length END) SUM(CASE WHEN rating = 'R' THEN length END), RAISE INFO 'Run %, Statement 1: %', r, (clock_timestamp() - v_ts) Repeat the whole benchmark several times to avoid warmup penalty Benchmark codeĪs promised, this was the benchmark code used for this blog post: Do measure things yourself, and if you cannot reproduce a performance problem, then don’t necessarily touch perfectly sound logic just because a blog post told you so. While in this case, the improvement is worth it irrespective of actual measurements (because performance can hardly be worse, and readability actually improves), always be careful with such benchmark results. You can safely switch to this nice standard SQL syntax already now. ) is such a popular idiom, and 8% is quite the significant improvement, that I think PostgreSQL should fix this. I think this is a case where it’s worth looking into simple patterns of expressions in aggregate functions. In RDBMS that don’t have such a cache, optimisation time is more costly per query, so less can be expected. Db2, Oracle, SQL Server), in case of which the optimisation needs to be done only once per cached plan, and then the plan can be reused. There was a tendency of such optimisations being favoured by RDBMS that have an execution plan cache (e.g. In a previous blog post (which is probably outdated by now), I’ve shown a lot of these cases, where the optimisation decision doesn’t depend on any cost model and data sets and should always be done, ideally. But this isn’t always the case in the real world, where optimisers make tradeoffs between: In a perfect world, two provably equivalent SQL syntaxes also perform the same way. But still, the FILTER clause outperforms CASE clause usage. The optimiser doesn’t optimise this as well as it could). The execution block contains all the code that needs to be executed, including the EXIT condition.So, indeed, the redundant predicate improved things (in a perfect world, it shouldn’t, but here we are. The LOOP keyword declares the beginning of the loop, and END LOOP declares the end of the loop. SELECT last_name, job_id, salary,ĮLSE salary END "REVISED_SALARY" FROM employees ![]() For all other job roles, there is no increase in salary. We can use CASE to evaluate multiple conditions for a single variable, “job_id.” If “job_id” is “ACCOUNT,” the salary increase is 10% if “job_id” is “IT_PROG,” the salary increase is 15% if “job_id” is “SALES,” the salary increase is 20%. It facilitates conditional inquiries by doing the work of an IF-THEN-ELSE statement and applying it to many possible conditions. The CASE statement uses IF-THEN-ELSE logic within a single statement. Next, there is one condition: when x is greater than y it raises notice that “x is greater than y.” When that condition is not met, it raises the notice “x is not greater than y.” In this case, the condition is not met, so the ELSE clause is executed and the output for the ELSE part is printed. ![]() If the condition is false then it goes to the next statement after END IF.Īs in the first example, here 2 variables are declared at the start: x=10 and y=20. The IF condition runs when a condition is evaluated as true. There are three main types of control structures available with PostgreSQL to use with stored procedures: IF, CASE, and LOOP. Stored procedures in PostgreSQL are ones that define a function for creating triggers or custom functions. SUMMARY: This article reviews control structures that can be used in PostgreSQL stored procedures, with syntax and examples provided for each. ![]()
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