Now, let's try to list all topics in our coffeecake last year and afterwards read the tales about particular
topic in our case, so we will read the tales about topic animals.
So let's first entered this command that is located after topic comment, this one.
And let me do that in a separate tab.
Let me send you to Kafka.
And here is this command.
And as a result, I got two topics.
One is system topic gold to underscore consumer offsets, and the next one is animals.
That is a topic we have created ourselves.
Let's not read the tales about topic animals that we could use this common topic details.
And here will be option.
Describe and name of the topic.
Let me replace death with animals like Soul.
Copy this comment and paste here.
Notice how fast we move when we have all commands here in one single file.
Great.
Let's press enter.
And let me make this output a bit smaller, like Seoul and the U.S. following information, thrust topic
name animals, partition count is three.
That is the count we have specified when we have created this topic.
Next, replication factor one.
We have also specified this option.
If I will get back here to this list, you'll see this option here.
But basically, it is a default option.
Replication factor is set to one by default.
And one of the next examples, we will try to adjust it and make it two or three.
For now, it is one grade after application of Aktau for this particular topic.
You'll see it segment by its option and it is set actually to one gigabyte and it is the size of every
segment for this particular topic.
What the segment segment is actually single file that stores log messages.
And in our case, if I look at the visual studio called files here in animals folders in partitioned
folders, you'll see those log files.
And this option actually specifies maximum size of every log file.
For example, when this log file reaches size one gigabyte, COFCO will create one more log file in
this same partition, Animals one and messages will arrive there to that new file.
That's what segment by its option means.
Next, after details of this specific topic, you'll see the details about every partition of this topic.
So here on this line, you see the tales about partition zero.
On the next line, the tales about partition one.
And finally, last, partition with idee two.
For every partition, you'll see information about LIDAR replicas and in-sync replicas.
And in our case, in this example, everywhere you'll see number zero.
And basically this is idea of specific Breuker.
In our case, we have only a single broker this way.
Everywhere you see here, number zero, it means that for every partition, this one, this one and
this one broker with a zero is leader for this particular partition.
Also, there are no replicas except Brolga with a zero.
So every message is thought only in a single place on a single brolga.
That's why here you see in the replicas list is zero and in-sync replicas parameter shows of replicas
that are synchronized with leader.
And again, in this first example we see here, ID zero, which side of our single broker, because
the single place where our messages for every partition are stored.
And of course, in this example, if this broker fails, we will be able to retrieve messages anymore
and the producers and consumers will be able to communicate with Kafka.
Kloster, this are details about a particular topic, in our case, animals.
Let's not try to read details also about this system topic.
Let me copy its name like so go back to notepad and adjust the name of the topic we want to details
about here like soul.
Copy this command.
And pasted here in the terminal.
And make it a bit smaller.
And here you'll see basically information about 50 partitions of the topic, consumer offsets, and
again, everywhere, leader replicas and in some replicas are set to broker with a zero.
And now you'll see that this topic has 50 partitions and replication factor is one, does default one.
And here you'll see configuration details of this particular topic.
But what is the purpose of this system topic called consumer offsets?
Inside of it, Kafka stories committed of offsets of consumers.
In our case, we have only a single consumer that is around, and the Kafka now knows that it has read
the old messages in Patison number two, starting from Offset Zero, and currently it is at Offset one
and is ready to read new messages that will arrive to this particular partition.
And this information is again stored somewhere in one of partitions here in this system topic.
In simple words, its tracks location of every consumer in Matthijs consumption brought us again.
That's Consumer Offset Storbeck.
Wonderful.
Let's do one more step and let's try to observe logs of Kafka Breuker.
So let me go to this step where we have started Kafka.
And you see here some periodic messages like this one removed zero expired offsets in zero milliseconds.
That actually tracks whether there are some expired offsets.
Also, if you scroll up, you'll see some messages related to console groups like this one, for example,
group console consumer with ID six one one two transitions to death in generation two.
Also, if you scroll up and we see other messages related to consumer groups like this one preparing
to rebalance the group and so on, Rigoberta, they have told you that technically every consumer must
belong to specific consumer group.
And if you don't specify a consumer group name in your consumer group, in our case, in this example,
we didn't specify it then group name will be created automatically and it will get the same unique number.
We will explore it a bit later.
And also later in one of the next examples, we will create the consumer in specific consumer group.
For now, that's all for this example.
And next, let's make a short summary of it.
See you next.
Bye by.