Kafka tutorials covers Introducing Kafka, Definition, Installation of Kafka, Use cases, Ecosystem, Version Updating, Application Programming Interface, Configuration, Operation, Basic Kafka operations, Datacenters, Import configuration, Java version, Hardware and operating system, Monitoring, Conclusion
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Read below to find out why Kafka has gained impetus in such a short span of time since its inception:
Kafka versus Storm
Despite both these technologies work together, however their operations are slightly different in nature.
Let’s compare Kafka and Storm:
|Apache Kafka||Apache Storm|
|distributed pub-sub real-time messaging system||distributed real-time computation engine|
|processes messages at scale||processes unbounded streams of data|
|Useful when processing and analyzing data in real-time||Useful in transforming data in multiple stages|
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An apache project initially developed at Linkedin. Distributed publish-subscribe messaging system. Mostly the real time actions are operated using it such as metrics collections, logs etc Written in Scala. Supports both queue and Topic semantics. Watch this Kafka video [videothumb class="col-md-12" id="2z6scTH_C4c" alt="Kafka Spark Streaming" title="Kafka Spark Streaming"] Kafka is a technology used for massage services, but Read More
Download the link for Kafka source – https://archive.apache.org/dist/Kafka/0.8.0/Kafka-0.8.0-src.tgz and then: tar xzf Kafka-0.8.0-src.tgz Enter the directory and run the commands: sudo ./sbt update sudo ./sbt package To start the Zookeeper server, run (in the directory) bin/zookeeper-server-start.sh config.zookeeper.properties Now start the Kafka server, run (in the directory) bin/Kafka-server-start.sh config/server.properties Create a Topic of publishing messages, bin/Kafka-create-Topic.sh –zookeeper Read More
The Kafka system is run by different components and all the components performs their individual tasks which are then communicated using the Simple binary Application Programming Interface. The complete whole procedure of running the Kafka needs different servers to operate and each server is called as the broker The messages in Kafka are needed to be Read More
Messaging: Kafka works best on messaging . Since it is the primary work of Kafka. The servers of Kafka known as brokers are best in buffering the messages which are yet to be published and also to start the processing at the consumers by ending it in the producers. It is proficient in transferring the message of Read More
The Kafka system works integrating other tools like Hadoop, Spark, etc. Creating a complete filled Eco system. Read these Top Trending kafka Interview Q's now that helps you grab high-paying jobs !Read More
Updating from 0.7 Release 0.7 is incompatible with newer releases. Most important changes were made to the API and ZooKeeper to add replication.The update from 0.7 to later versions requires a special tool for relocation. This relocation can be done without downtime. Read these Top Trending Kafka Interview Q's now that helps you grab high-paying jobs ! Updating from Read More
Software applications are best assembled by the APIs. The communication of the software commodities happens on this platform. Few Examples Google Maps API, Programmable Web, YouTube APIs,Amazon Product Advertising APIs are some examples of APIs.Read More
By using the property file the Kafka makes its configuration. It can be supplied either from a file or programmatically. It is either taken from a default file or else also can be self-programmed. Read these Top Trending Kafka Interview Q's now that helps you grab high-paying jobs ! Some configurations have both a default global setting as well as Read More
In this section, we will be providing discussions about the basic operations of Kafka as follows: The Addition and Deletion of Topics We can add and delete Topics both automatically and manually. For the addition, the command will be > bin/Kafka-Topics.sh --zookeeper zk_host:port/chroot --create --Topic my_Topic_name --partitions 20 --replication-factor 3 --config x=y The messages that are Read More
Kafka uses 24 Giga bytes memory for dual quad-core machines.Memory need can be calculated using the command write_throughput*30. We need a lot of memory for buffering active readers and writers. So keeping a backup of every bit of memory is very much essential. This tool runs on Unix, Linux as well as in Solaris. Since Kafka Read More
Yammer Metrics is used for reporting purposes between the brokers and the clients. Description Value No of under replicated partitions 0 It means that the server is on active control Only one server is 1 Leader election rate (LER) Server failure not 0 Unclean LER 0 Partition counts Mostly even near servers Leader replica counts Mostly Read More
The final result of the performance of this Kafka system totally depends on how much accuracy occurs in data delivery. The performance depends on the delivery of every message to its consumer correctly, on time without more lag of time. The message delivery has to be done at a perfect time and if not received within Read More
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