Ans. The most important elements of Kafka:
Topic – It is the bunch of similar kind of messages
Producer – using this one can issue communications to the topic
Consumer – it endures to a variety of topics and takes data from brokers.
Brokers – this is the place where the issued messages are stored
Ans. Duplication assures that issued messages which are available are absorbed in the case of any appliance mistake, plan fault, or recurrent software promotions.
Ans. It is responsible for covering the two producers- kafka.producer.SyncProducer and the kafka.producer.async.AsyncProducer. The main aim is to disclose all the producer performance through a single API to the clients.
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Ans. Kafka being distributed publish-subscribe system has the advantages as below.Fast: Kafka comprises of a broker and a single broker can serve thousands of clients by handling megabytes of reads and writes per second.Scalable: facts are partitioned and streamlined over a cluster of machines to enable large information durable: Messages are persistent and is replicated in the cluster to prevent record loss Distributed by Design: It provides fault tolerance guarantees and robust.
Ans. They are mainly four major components in the Kafka system. They are as follows:
Ans.
Ans. A leader and follower make sure that the system is always online and the information is made available without any downtime.
In this scenario:
So for every partition in the Kafka system, at least one server will act as a Leader. The rest of the servers can be defined as Followers.
The main activity of the leader is to make sure to execute all the requests associated to read and write, for the partition.
The same activities are followed by the Followers in the background and create replicas. In any event, if the Leader is not able to serve the information, one of the followers will be able to provide the relevant information.
Ans. Replication in the Kafka system is mainly needed to make sure the information or the data is always available. In reality, we get to see the systems are down for many reasons, for example:
Ans. The traditional method transfer generally includes two methods, they are listed below:
Ans. The following are the benefits of the Apache Kafka system over traditional technique:
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Ans. The main API's that are available within the Kafka system are listed below:
Ans. The load balancing concept is achieved with the help of Leader and Follower servers. All the information requests will be first sent across to the Leader server, if the request is not fulfilled then the request will be sent to the follower server. So basically, this process is nothing but a load balancing process.
Ans. The highest possible size of a message that can be allowed is near to 1000000 bytes.
Ans. They are three different types of system tools:
Ans. Within the Apache Kafka system, a high rate transmission, and processing rates is a mandatory requirement to make sure the data is available all the time. To support the high processing requests and transmissions requests the usage of Java is required.
More importantly, we have good community support concerning Java usage in Kafka
Ans. Apache Kafka is capable of handling various use cases that are pretty common for a Data Lake implementation.
For example: Handling use cases concerning log aggregations, web activities tracking, and monitoring.
Ans. We know the Apache Kafka system is a distributed system where the information is replicated into multiple servers so that there is no practical downtime. To manage and make sure that these distributed systems are well co-ordinated we need a mechanism, i.e. Zookeeper does the job.
With the use of Zookeeper, it builds perfect collaboration and co-ordination between the available nodes in the clusters.
In the case of recovery, Zookeeper will make sure that to recover the information.
Ans. Firstly, we cannot connect to Kafka servers directly, all the requests would go through Zookeeper only.
So if in any scenario or situation, if Zookeeper is down none of the requests will be fulfilled. So to answer the question, yes we would need Zookeeper to use the Kafka system.
Ans. The concept of a consumer group can be observed in only the Apache Kafka system. They are called the Apache Kafka consumer group.
So Apache Kafka consumer group consists of more than one consumer group. The main activity of this consumer group is to absorb a specific set of topics. Usually, these topics are subscribed to topics.
Ans. The steps that are associated to start a Kafka server is as follows:
Firstly initiative, Kafka server one has to make sure to initiate the request to the Zookeeper server. Because to reach out to the Kafka server, the Zookeeper server is used.
Start a new terminal and type the specific command :
bin/zookeeper-server-start.sh config/zookeeper.properties
To ignite Kafka broker, the following command has to be used:
bin/Kafka-server-start.sh config/server.properties
Ans. Kafka as a streaming/data distribution system, it is mainly used into two areas:
To build real-time streaming data applications. Within these applications, the data is available between the two systems.
To build real-time streaming data applications. Within these applications, the data is transformed.
Ans. Within Apache Kafka, it has an inbuilt framework or process where it is capable of ingesting data into the Kafka system directly or ingesting data into different external systems.
These connectors are maintained separately from the main point source of the codebase.
Ans. With the use of Connect API, the connectors will have an ability either to pull or push functions. When the pull function is used, the data is pulled from various data sources into the Apache Kafka system.
When the push function is used, the data is pushed from the Apache Kafka system to a data system.
It is not mandatory to use the connector API. Also, one can use pre-built connectors where one doesn't need to customize any additional code.
Ans. If the Kafka producer is continuously sending out the messages where the broker is not able to handle all the requests, then we get to see the following error:
QueueFullExecption.
So to handle these error situations and also to handle the message requests that are sent from Producers, we can have multiple brokers. So using multiple brokers, the load will be balanced.
Ans. A streaming platform will have three capabilities.
Ans. The event replication factor is the major difference between Apache Kafka and Apache Flume.
Apache Kafka is capable of replicating the events. Whereas, the Apache Flume is not useful for event replication.
Ans. In the Kafka cluster, a broker is referred to as a server.
Ans. ISR full form is In Sync replicas.
Ans. Yes, it is an open-source platform.
Ans. With the help of Stream API, it allows the application to process all of the requests and the data is transform effectively without any interruption.
Ans. Apache Kafka is written with the use of Java and Scala languages.
Ans. Yes, it is possible to achieve a FIFO format in Kafka.
Ans. SerDes stands for serializer and deserializer.
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