Kafka Producer Internals

In this video , the internals of Kafka Producer is explained.
Architecture :
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github.com/SatadruMukherjee/D...
Prerequisite:
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Install and run Apache Kafka & integration with Python using kafka-python
• Install and run Apache...
Multiple Producer & Multiple Consumer in a Kafka Topic
• Multiple Producer & Mu...
Intuition on Log files in kafka & Kafka Brokers
• Intuition on Log files...
Broker Cluster and Zookeeper in Kafka
• Broker Cluster and Zoo...
Topics, partitions, and offsets in Kafka
• Topics, partitions, an...
Kafka Cluster with Multiple Brokers
• Kafka Cluster with Mul...
Topic with Replication in Multiple Broker Kafka Cluster
• Topic with Replication...
Setting up a single node Kafka Cluster on EC2
• Setting up a single n...
Kafka Log Segments in-depth intuition
• Kafka Log Segments in-...
Kafka Producer Key & Message Acknowledgements
• Kafka Producer Key & M...
Check this playlist for more Data Engineering related videos:
• Demystifying Data Engi...
Snowflake Complete Course from scratch with End-to-End Project with in-depth explanation--
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[@user-or5gv9jt2i]

probably the best playlist for kafka sir. amazing

[@KnowledgeAmplifier1]

Glad to hear that!!

[@kanagarajraj1241]

Thanks Lovely brother 👍

[@KnowledgeAmplifier1]

You are welcome Kanagaraj Raj! Happy Learning :-)

[@prodigit7]

Thanks for all. My resume about the topic. The internal workings of a Kafka producer can be described as follows: 1. The Kafka producer sends messages to a partition using a ProducerRecord object that contains information such as the topic name, the partition to which the message should be sent, and the key and value of the message. hash(key)%num_partition 2. Before sending the message, the producer must serialize it into an appropriate format for storage and transmission. This can be done using a custom serializer or by using one of Kafka's built-in serializers. 3. Once the message is serialized, the producer must determine the partition to which the message should be sent. This can be done using a hashing function that takes the message key and the total number of partitions to determine the appropriate partition. 4. The message is then stored in a buffer waiting to be sent. Multiple messages can be stored in the buffer before being sent as a batch. 5. The producer can specify parameters such as maximum wait time (linger.ms) and maximum batch size (batch.size) to control when messages are sent. 6. If sending the message fails for any reason, the producer can either retry sending the message or retry sending the entire batch of messages. 7. If sending the message succeeds, the producer receives information about the message such as the partition offset, timestamp, and other metadata.

[@devamsanghavi1787]

Thank you for this Course!

[@KnowledgeAmplifier1]

You are welcome Devam Sanghavi! Happy Learning

[@animeshsen5901]

Simply the best!!

[@KnowledgeAmplifier1]

Thank you Animesh ! Happy Learning :-)

[@KLNP-ot6rq]

Very good job buddy !

[@KnowledgeAmplifier1]

Thanks a lot KLNP1978! Happy Learning :-)

[@digitaltechconnect1318]

Please provide us the coding of the video for the execution

[@KnowledgeAmplifier1]

Hello Digital tech connect, this video is explaining the theory part , so no code is shared , for lab experiment related videos , the codes are available in description box or in the comment section...Happy Learning

[@digitaltechconnect1318]

Please send this video coding for the the practice

[@KnowledgeAmplifier1]

Hello Digital tech connect, this video is explaining the theory part , so no code is shared , for lab experiment related videos , the codes are available in description box or in the comment section...Happy Learning