With that in mind, let's jump right into best practices: You should be thinking by default on how you're going to be reading the data you're about to store in the database.Statistically speaking, the average user is going to spend more time reading data from the database than writing it, so you'll want to make sure reading the data is as painless and uses as little resources as possible.This article introduces the new MERGE SQL command (sometimes referred to as "UPSERT").MERGE is a DML command that enables us to optionally update or insert data into a target table, depending on whether matching records already exist.In this post he writes about how to structure and update your data in a No SQL database like Firebase.As a new Firebase user, you're probably still trying to wrap your head about all the querying possibilities you used to have when working with My SQL or Postgre SQL databases.We will replace the two-part SQL solution with a PL/SQL loop that will attempt an update first and insert only if the update affects no rows.
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For example, our user table in Firebase would look like this instead: Basically, you can just add whatever information you want to add to the user's node.Without the outer join, Oracle would need to implement a "two-pass" solution such as we might code ourselves with a separate INSERT and UPDATE statement.Major performance gains will be achieved by tuning the source-target join (for example, using indexes, hints, partitioning etc) or by tuning the USING clause if it is a complex in-line view.We will start by creating the source table as a selection of ALL_OBJECTS data.
In the following example, we will merge the source table into the target table.
SQL databases use tables to store data, those tables have columns and rows where the data is stored. For example, a table could have 3 columns: ID, First Name, Last Name.