Very well done Tim - Thank you!

finally i found the partition logic in this video. Thanks a lot for the crisp video tim.

Thank you, crystal clear!

Yet again Tim, rock solid short snappy overview.

It's simply a great explanation. Thanks Man

Great video guys, very helpful!

Thanks Tim.. This is best video over internet for those who just jumped in to Kafka....

Thank so much, it is so clearly

man your style of explanation is just awesome..I mean how can you explain things so easily that too without much animation or something...one of the best instructor I must say

incredible visualized video. Thank you so much

Very well explained ..thank you

good explanation, thanks!

Amazing explanation!!

clear explanation, thanks

Best explanation for partition.

hey tim, can you tell me another advantage using partition

Thanks to animation in this video now I better understand partition

awesome .

What is the relation between events and messages? Messages have key-value pairs? or Events have key-value pairs? what exactly ... Events or messages are stored in partitions with key-value pairs? this was a helpful video Take key ------> HASH Function-------> Output mod (Total no. of partitions) ------> Resulting no. is Partitions number where message going to store. I was unaware of this concept. Thank You Tim.

Hi - what do the Fire logo and wheel logo mean? Are these logos of old Kafka versions? I only could find a slideshow "Kafka - Past, present and future" :)

so it is generally correct , if not always, to say that messages in different partitions within same topic are mutually exclusive?

what if we want to store information for each day in the NASDAQ stock market with ~3000 symbols and 1 billon of trades per day. Should we use one topic for each symbol or just one topic with handred of partitions? I want to understand a real case with a hugh amount of data!

Is it possible one message can belongs to multiple partitions ?

What's the name of this song? ps: Kafka is amazing

So if you want a FIFO queue, you are limited to only one partition?

Excellent explanation, but one thing that I see just about all videos lack is explaining WHY partitioning is useful and when it is not.

@ConfluentDevXTeam

3 ай бұрын

Gilles here from Confluent. It's a good point, I was wondering the same thing last week and realised we don't have a video that goes into details of how you should partition your topics and why. The best resource is still this blog post from Jun Rao: www.confluent.io/blog/how-choose-number-topics-partitions-kafka-cluster/. Hope this helps!

When consumer read the topic, how does it know which partition to read the message out?

When I subscribe to a partitioned Topic, I still get all the messages eventually, just not necessarily in the correct order, right?

Why don't use consistent hashing but use hash/ num_partition?

Do we need to mentioned the number of partition while creating the topics? For example if I create the key with CustomerID and create the Kafka topic with 5 Partition then when there is a 6th Customer comes with different Key then which Partition will stored?

@AmitMahto-bf5np

9 ай бұрын

Yes,you have to mention no. of partitions.

If the number of partitions changes, does Kafka re-hash and redistribute events? If not then events with the same ID could end up in different partitions?

@zampogna

Жыл бұрын

It would be great to have a crisp explaination also for that

@gerooq

Жыл бұрын

Why would events have the same ID

What if one partition node goes down, then the order can be messed up?

in my humble opinion it is the case in real world, to have a customer acting as a noisy neighbour.

Since Kafka 2.4 the Default Partitioner is set to Sticky Partitioner, and not Round Robin. Hence, if you wonder why all the messages with the null key land in the same partition this is the reason. If you want to set it to Round Robin to how it was before version 2.4 then set it in the props passed to ProducerFactory: props.put(ProducerConfig.PARTITIONER_CLASS_CONFIG, RoundRobinPartitioner.class);