How does a @OneToOne relationship work in Spring Data JPA?

great read. simple explanations. funny though how the first one is the only one worth exploring if you ask me!

Before jumping into @OneToOne examples, be sure to understand the basics of <a id=0 href='https://www.stackchief.com/blog/Spring%20Data%20JPA'>Spring Data JPA</a>.

1) @OneToOne Example Using Shared Primary Key (Best Approach)

    @GeneratedValue(strategy = GenerationType.AUTO)

    @OneToOne(mappedBy = "author", cascade = CascadeType.ALL)

This creates a one-to-one relationship between an author and book table. A book has one author and an author has one book.

Using the @OneToOne annotation, Hibernate knows to create a one-to-one relationship between the two entities.

The mappedBy="author" option tells Hibernate that the owning side of the relationship is the book table. This means the book table will hold the foreign key reference to the author table.

The cascade = CascadeType.ALL tells Hibernate to propagate changes to all associated entities. If you delete an instance of Author it will delete the associated Book entity automatically.

The @PrimaryKeyJoinColumn tells Hibernate that the primary key for the author table will be used as the foreign key in the owning book table.

The @MapsId tells Hibernate that the primary key on the author table will be used as the primary key for the book table. Since the primary key is being reused, we don't need a to specify @GenderatedValue on the book table.

This generates the following in the database...

When retrieving entities from the database, associations will be eagerly loaded by default:

Author author = authorRepo.findById(24) //returns both the author and its associated book in single DB call

By utilizing the primary key of the author as both the primary key and foreign key of the book table, you achieve the same result with fewer keys. This saves operating costs as primary/foreign keys are typically indexed and loaded into memory for efficient lookups. You're achieving the same result with fewer keys via a unidirectional relationship.

With this approach, the author table is the owning side of the relationship. This means the author table will have the foreign key book_id. For these reasons, the mappedBy = is moved to the Book entity definition.

Since the primary key is no longer being reused in both tables, the Book entity must now generate its own id values. For these reasons, the @GeneratedValue annotation exists on both entity classes.

Note: Unlike the last example, we now save the author entity to create the associations in the database. Whichever side owns the relationship must be saved to create entries in both tables.. Otherwise, you will run into issues with transient objects not being saved and exceptions being thrown.

Notice how the author table now has 2 columns.  This is because a foreign key is being used to create a bidirectional relationship between books and authors.

This example clearly demonstrates the advantage of the first approach as an extra book_id is needed to achieve the relationship.

                    { @JoinColumn(name = "author_id", referencedColumnName = "id") },

                    { @JoinColumn(name = "book_id", referencedColumnName = "id") })

One to One Example using Spring Data JPA and Hibernate including shared primary key, unidirectional, and bidirectional examples.

One To One Example | Spring Data JPA

CascadeType is an option that specifies how related entities should be treated...

let's say you have a one-to-many relationship between courses and students...

in your @Entity class you may have something like:

This is saying that every operation you perform on this entity, every associated entity will get the same treatement,

So if you delete a parent entity all of it's children (associations) will also get deleted.

Sometimes this makes sense. Sometimes it doesn't.  BE CAREFUL in using this as it can have unexpected consequences...

What is the purpose of CascadeType in Spring Data JPA / Hibernate?

Can we call garbage collector forcefully in Java

Can we call garbage collector forcefully in Java?

Great 5 minutes explanation.  Implementing your own version of the Observable is a MUTS DO exercise for new developers...

The Promise is still relevant and great for async operations where you are only concerned with the result of one async operation.  While the observable handles this well with Angular, it's still perfectly reasonable to use the Promise library for http requests, etc.

stackchief

Quickly understand JavaScript observables.  Implement the Observable class from scratch and understand what makes observables different from promises.

JavaScript Observables in 5 Minutes

when I read through the "Push vs Pull" section I couldn't help but think about the similarities to a "pull" based system like Kafka.  In Kafka, consumers pull messages from topics.  The advantage is Kafka just sits there so an infinite number of applications can read from Kafka in parallel.

So how does this relate to the "pull" based nature of a Promise.  I suppose a Promise "pulls" the value when it either rejects/resolves.

Does anyone have similar thoughts or comparisons to make?

The difference between Java SE and Java EE are negligible into todays programming world.  I'm sure some will disagree but we use SE in production and have no issues operating at scale.

Well. My company standard it's openJDK 8 since 2019... Cheers!

juanrios.com@localhost

thank you, I finally realize that Java 8 is the most popular version.

Evgeny Ivanov

Alexander Joseph

A discussion surrounding the different versions of Java including the difference between SE and EE as well as key features of Java 7, 8, and 9.

Which Version of Java Should You Use?

When people talk about a "Kafka consumer" they can mean different things...and it leads to some confusion.

A Kafka consumer is technically a process that is part of a larger group.  This collective group of consumers is called a "consumer group".

It is the collective responsibility of a consumer group to process messages from a given topic.  Each consumer within the group ideally will read from one partition.  Kafka balances the number of partitions across the number of available consumers in the group.

The groupId associates a Kafka consumer with a consumer group....

If a topic has 3 partitions and you have 2 consumers operating within the same consumer group, one of the consumers will read from 2 partitions and the other will read from 1.

If a topic has 4 partitions and you have 2 consumers operating within the same group then both consumers will read from 2 partitions.

If a topic has 1 partition and you have 2 consumers then 1 consumer reads from 1 partition and the other just sits there...

What is Kafka Consumer Group ID?

Yes super annoying.  I have to continuously manually reset offset to latest to get it to skip past the bad record and keep consuming. Not sustainable for sure. Any help is greatly appreciated on this.

I am trying to use the JSON deserializer for Kafka (with Spring) and keep having issues.  Specifically it seems to throw the service into an infinite loop resulting in out of memory error...

Does anyone have issues with JSON Serializer in Kafka

Does anyone have issues with JSON Serializer in Kafka?

You use the poll() method to read messages from a given topic. This method takes a single argument of type Duration specifying how long to listen for messages before returning an empty list of records.

If records are immediately available, the poll() method will return immediately.

What is Kafka consumer poll?

Yes blazing..this is a common problem with using the JsonDeserializer class provided by Kafka.

EatFreshRupesh

How does a @OneToOne relationship work in Spring Data JPA?

great read. simple explanations. funny though how the first one is the only one worth exploring if you ask me!

CascadeType is an option that specifies how related entities should be treated...

System.gc();

Great 5 minutes explanation. Implementing your own version of the Observable is a MUTS DO exercise for new developers...

when I read through the "Push vs Pull" section I couldn't help but think about the similarities to a "pull" based system like Kafka. In Kafka, consumers pull messages from topics. The advantage is Kafka just sits there so an infinite number of applications can read from Kafka in parallel.

The difference between Java SE and Java EE are negligible into todays programming world. I'm sure some will disagree but we use SE in production and have no issues operating at scale.

When people talk about a "Kafka consumer" they can mean different things...and it leads to some confusion.

Yes super annoying. I have to continuously manually reset offset to latest to get it to skip past the bad record and keep consuming. Not sustainable for sure. Any help is greatly appreciated on this.

You use the <span class='code-bite'>poll()</span> method to read messages from a given topic. This method takes a single argument of type <span class='code-bite'>Duration</span> specifying how long to listen for messages before returning an empty list of records.

Yes blazing..this is a common problem with using the <span class='code-bite'>JsonDeserializer</span> class provided by Kafka.