1/3/2024 0 Comments Sqlite inner join on subquery![]() ![]() The table lists the most recent order for each customer. Let’s say for each customer, we want to know the date and the status of his/her most recent order. ![]() you can see, every customer has several orders at our store. To demonstrate several possible solutions to this problem, we use the following tables that list the customers and their respective orders. In all these cases, you may order the table with many corresponding records accordingly (e.g., by item price, observation date, etc.), and therefore, turn your problem into selecting the first, or the top, row. ![]() The most recent order for each customer.The most experienced employee in each department.The most recently observed temperature for each location.There are many different scenarios where you have a one-to-many relationship between two tables and you need to join only the first match from one table to the corresponding record in another. It contains 88 hands-on exercises to help you refresh your SQL skills, starting with the basics and going to challenging problems. The best way to practice basic and advanced SQL is our interactive SQL Practice Set course. In this article, I’ll go through several ways to do this in SQL. Monitoring PostgreSQL with Navicat Monitor 3.In your projects, you may encounter situations when you have many orders corresponding to one customer or many temperature observations corresponding to the same location, but you only need to join the first row with the most recent order or the most recently observed temperature to the corresponding record in another table.Trace Queries on your PostgreSQL Instances with Navicat Monitor 3.Viewing PostgreSQL Instance Details in Navicat Monitor 3.A Quick Guide to Naming Conventions in SQL - Part 2. ![]() A Quick Guide to Naming Conventions in SQL - Part 3.Selecting Distinct Values From a Relational Database.Implement Audit Trail Logging Using Triggers.Multi-Version Concurrency Control in PostgreSQL.A Guide to MySQL Foreign Key Constraints.In any event, there are still times that a subquery is advantageous over joins, such as when you have to calculate an aggregate value on-the-fly and use it in the outer query for comparison. While this blog seems to confirm the conclusion reached by Joins versus Subqueries: Which Is Faster? article, it can be a worthwhile exercise to compare both a join and subquery approach. Even without digging deeper, we can already see that there is an additional step required to execute the second (subquery) statement: Conclusion Meanwhile, the Explain2 tab lists one PRIMARY select, followed by three DEPENDENT SUBQUERIES. We can see at a glance that it involves 3 SIMPLE selects: The Explain1 tab shows the Execution Plan for the first (join) query. While it takes some practice to become adept at interpreting the results of Explain, doing so can pay dividends when trying to ascertain a query's efficiency. In Navicat, we can view the Execution Plan by clicking the Explain button. A minute difference, but one that would grow as the volume of data increases: Comparing Execution PlansĪ query's Execution Plan can reveal a lot of information about how quickly it will execute. An Elapsed Time of 0.020s can be seen at the bottom of the screen:ĭoing the same with the second statement yields an Elapsed Time of 0.021s. To do that, we can select an individual statement, and click the Run button, whose label changes to Run Selected whenever text is selected in the editor. Having verified that both statements are equivalent, we can now compare their execution times. In the image below, the contents of the Result 2 tab is shown next to Result 1 for quick comparison: Query Execution Time Each result set is shown in its own tab below the SQL Editor. We can easily compare the results in Navicat, because it can run multiple queries simultaneously. WHERE C.country_id=co.country_id) AS address_cnt WHERE Ci.country_id=co.country_id) AS city_cnt, The first SELECT statement uses joins while the second one fetches the exact same data using subqueries: To illustrate, here is a query that selects countries, along with their associated cities and addresses from the MySQL Sakila Sample Database. Most of the time, a query can be written using joins or subqueries. This article will present a couple of quick tests you can perform to compare a query that employs joins to one that contains subqueries so that you can choose which performs best. As mentioned in that article, if you need to add many joins to a query, the database server has to do more work, which can translate to slower data retrieval times. Having said that, it's not a universal rule, so you may not want to automatically assume that a join will be preferable. In the Joins versus Subqueries: Which Is Faster? blog article we learned that joins tend to execute faster than subqueries. Choosing between a Subquery and Join by Robert Gravelle ![]()
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