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Besides managing a database structures, Liquibase can also load data into an existing table. If there are many rows to insert, the loadData change may be especially useful. It allows to load data from a CSV file to an existing database table. In many cases preconfigured settings are enough to do the job. But it also allows customizations like defining a separator, reordering the columns or even skipping some columns.
Caching may save performance of your system. For example, Caffeine Cache is one of powerful cache libraries that offer various configuration options. Speaking of options... do you know how to configure Caffeine Cache? Check sixty second question of full-stack dev quiz to check it.
Adding cache to a Spring Boot 3 application is very quick and easy. It is a matter of choosing one of a few supported cache managers and putting relevant annotations to proper places in the code. Caffeine cache is one of the options.
Do you know how to prepare update and rollback SQL scripts with Liquibase that can be provided to a DBA? Check sixty second question of full-stack dev quiz to verify that.
Liquibase is a tool to automate database upgrades starting from a script, through testing, till a deployment to production. However, sometimes we want to take care of deployment ourselves. In that case, the possibility to generate an SQL script is extremely useful.
You may create a primary key in a few different ways using Liquibase. Do you know which Liquibase changes support autorollback and which don't? Check sixty first question of full-stack dev quiz to test your knowledge.
Creating a table is one of the most basic elements of Data Definition Language (DDL). Or a phrase commonly used would be better. There is no useful relational database without tables. Even though tables are very common, creating them isn't the most straightforward operation you can think of. One of the reasons is a primary key. How to create a table with a primary key? How to add or modify a primary key later when a table already exists?
In November 2022, Open AI released ChatGPT 3. It quickly went viral. Social media is still massively flooded with screenshots and screencasts from the chat. Until now I calmly observed the situation sitting in the corner. But I have recently watched a non-technical video in which the speaker shared his opinion that now developers will lose their jobs, as now ChatGPT can do their tasks. The speaker was not an IT expert in any sense, but that was his impression, and he was sure about what he was saying.
Besides exchanging JSON objects in a request or a response body, REST API can also use files. Doing so is not a big deal when the files are small. Things get a little bit more complicated when we have to respond with a big file. No one wants to keep in memory a few hundred megabytes of data waiting on the client to slowly download it. It must be streamed.
