Interview Questions.

Question 1. Mention What Is Apache Kafka?

Answer :

Apache Kafka is a post-subscribe messaging gadget developed through Apache written in Scala. It is a disbursed, partitioned and replicated log service.

Question 2. Mention What Is The Traditional Method Of Message Transfer?

Answer :

The traditional method of message transfer includes two methods

Queuing: In a queuing, a pool of consumers may also read message from the server and each message goes to one among them
Publish-Subscribe: In this model, messages are broadcasted to all consumers
Kafka caters single customer abstraction that generalized each of the above- the patron organization.

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Question three. Mention What Is The Benefits Of Apache Kafka Over The Traditional Technique?

Answer :

Apache Kafka has following blessings above traditional messaging technique

Fast: A unmarried Kafka dealer can serve thousands of customers by means of dealing with megabytes of reads and writes in line with 2nd
Scalable: Data are partitioned and streamlined over a cluster of machines to allow large information
Durable: Messages are persistent and is replicated within the cluster to prevent information loss
Distributed by Design: It presents fault tolerance guarantees and durability
Question 4. Mention What Is The Meaning Of Broker In Kafka?

Answer :

In Kafka cluster, broker time period is used to refer Server.

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Question 5. Mention What Is The Maximum Size Of The Message Does Kafka Server Can Receive?

Answer :

The maximum size of the message that Kafka server can get hold of is a million bytes.

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Question 6. Explain What Is Zookeeper In Kafka? Can We Use Kafka Without Zookeeper?

Answer :

Zookeeper is an open supply, excessive-overall performance co-ordination provider used for disbursed packages adapted by using Kafka.

No, it is not possible to bye-skip Zookeeper and join immediately to the Kafka dealer. Once the Zookeeper is down, it can not serve patron request.

Zookeeper is essentially used to communicate among distinct nodes in a cluster
In Kafka, it's far used to devote offset, so if node fails anyhow it can be retrieved from the formerly devoted offset
Apart from this it also does other activities like leader detection, allotted synchronization, configuration management, identifies when a new node leaves or joins, the cluster, node status in actual time, etc.
Question 7. Explain How Message Is Consumed By Consumer In Kafka?

Answer :

Transfer of messages in Kafka is completed by using sendfile API. It permits the transfer of bytes from the socket to disk thru kernel space saving copies and phone among kernel person lower back to the kernel.

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Question eight. Explain How You Can Improve The Throughput Of A Remote Consumer?

Answer :

If the customer is placed in a unique data middle from the broking, you can require to song the socket buffer size to amortize the lengthy network latency.

Question 9. Explain How You Can Get Exactly Once Messaging From Kafka During Data Production?

Answer :

During statistics, manufacturing to get precisely once messaging from Kafka you need to comply with  things keeping off duplicates throughout statistics intake and heading off duplication at some stage in facts manufacturing.

Here are the two methods to get precisely one semantics even as statistics production:

Avail a single creator consistent with partition, each time you get a network mistakes assessments the ultimate message in that partition to see in case your ultimate write succeeded
In the message include a primary key (UUID or some thing) and de-reproduction on the customer
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Question 10. Explain How You Can Reduce Churn In Isr? When Does Broker Leave The Isr?

Answer :

ISR is a fixed of message replicas which are absolutely synced up with the leaders, in other phrase ISR has all messages which might be committed. ISR ought to usually encompass all replicas till there's a real failure. A duplicate can be dropped out of ISR if it deviates from the leader.

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Question 11. Why Replication Is Required In Kafka?

Answer :

Replication of message in Kafka ensures that any published message does not lose and may be fed on in case of system errors, program blunders or more common software program enhancements.

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Question 12. What Does It Indicate If Replica Stays Out Of Isr For A Long Time?

Answer :

If a replica stays out of ISR for an prolonged time, it suggests that the follower is not able to fetch records as speedy as records accrued on the leader.

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Question 13. Mention What Happens If The Preferred Replica Is Not In The Isr?

Answer :

If the favored reproduction isn't always within the ISR, the controller will fail to transport leadership to the preferred duplicate.

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Question 14. Is It Possible To Get The Message Offset After Producing?

Answer :

You can not do this from a class that behaves as a producer like in most queue structures, its function is to hearth and neglect the messages. The broker will do the relaxation of the work like appropriate metadata coping with with identification’s, offsets, and many others.

As a purchaser of the message, you can get the offset from a Kafka broker. If you gaze in the SimpleConsumer elegance, you'll note it fetches MultiFetchResponse items that include offsets as a list. In addition to that, when you iterate the Kafka Message, you will have MessageAndOffset gadgets that include each, the offset and the message sent.

Question 15. Which Components Are Used For Stream Flow Of Data?

Answer :

Bolt:- Bolts constitute the processing common sense unit in Storm. One can utilize bolts to do any sort of processing such as filtering, aggregating, joining, interacting with statistics stores, speakme to external structures and so forth. Bolts also can emit tuples (records messages) for the subsequent bolts to process. Additionally, bolts are responsible to renowned the processing of tuples after they are completed processing.

Spout:- Spouts constitute the source of facts in Storm. You can write spouts to read statistics from information resources which includes database, disbursed file structures, messaging frameworks and so forth. Spouts can widely be categorized into following –

Reliable:- These spouts have the capability to replay the tuples (a unit of records in facts movement). This enables packages attain ‘at least once message processing’ semantic as in case of disasters, tuples may be replayed and processed once more. Spouts for fetching the statistics from messaging frameworks are normally reliable as these frameworks provide the mechanism to replay the messages.

Unreliable:- These spouts don’t have the capability to replay the tuples. Once a tuple is emitted, it cannot be replayed regardless of whether or not it was processed efficiently or now not. This kind of spouts observe ‘at most as soon as message processing’ semantic.

Tuple:- The tuple is the main statistics structure in Storm. A tuple is a named list of values, where every value can be any type. Tuples are dynamically typed — the varieties of the fields do not need to be declared. Tuples have helper techniques like getInteger and getString to get discipline values without having to solid the result. Storm desires to realize a way to serialize all of the values in a tuple. By default, Storm knows how to serialize the primitive kinds, strings, and byte arrays. If you want to use any other kind, you’ll need to put in force and sign in a serializer for that kind.

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Question sixteen. What Are The Key Benefits Of Using Storm For Real Time Processing?

Answer :

Easy to function: Operating storm is quiet clean

Real fast: It can manner a hundred messages in step with 2nd in line with node

Fault Tolerant: It detects the fault automatically and re-starts offevolved the purposeful attributes

Reliable: It guarantees that every unit of facts may be finished at the least once or precisely as soon as

Scalable: It runs throughout a cluster of device.

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Question 17. Does Apache Act As A Proxy Server?

Answer :

Yes, It acts as proxy additionally by way of the usage of the mod_proxy module. This module implements a proxy, gateway or cache for Apache. It implements proxying functionality for AJP13 (Apache JServ Protocol model 1.3), FTP, CONNECT (for SSL),HTTP/0.9, HTTP/1.Zero, and (because Apache 1.3.23) HTTP/1.1. The module can be configured to connect to other proxy modules for those and other protocols.

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Question 18. While Installing, Why Does Apache Have Three Config Files - Srm.Conf, Access.Conf And Httpd.Conf?

Answer :

The first  are remnants from the NCSA instances, and typically you must be ok in case you delete the first two, and stick with httpd.Conf.

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Question 19. What Is Zeromq?

Answer :

ZeroMQ is “a library which extends the standard socket interfaces with functions traditionally supplied via specialised messaging middleware merchandise”. Storm is predicated on ZeroMQ primarily for venture-to-assignment verbal exchange in running Storm topologies.

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Question 20. How Many Distinct Layers Are Of Storm’s Codebase?

Answer :

There are three wonderful layers to Storm’s codebase.

First, Storm become designed from the very starting to be well matched with a couple of languages. Nimbus is a Thrift carrier and topologies are described as Thrift structures. The utilization of Thrift allows Storm for use from any language.
Second, all of Storm’s interfaces are special as Java interfaces. So despite the fact that there’s a variety of Clojure in Storm’s implementation, all usage must undergo the Java API. This manner that each feature of Storm is constantly available via Java.
Third, Storm’s implementation is essentially in Clojure. Line-smart, Storm is ready 1/2 Java code, 1/2 Clojure code. But Clojure is much more expressive, so in truth the wonderful majority of the implementation common sense is in Clojure.
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Question 21. When Do You Call The Cleanup Method?

Answer :

The cleanup method is called when a Bolt is being shutdown and have to cleanup any resources that had been opened. There’s no guarantee that this technique could be called at the cluster: For example, if the system the task is going for walks on blows up, there’s no manner to invoke the technique. The cleanup technique is intended when you run topologies in local mode (wherein a Storm cluster is simulated in manner), and you want with the intention to run and kill many topologies with out suffering any aid leaks.

Question 22. How Can We Kill A Topology?

Answer :

To kill a topology, surely run:

storm kill stormname

Give the equal name to storm kill as you used when submitting the topology. Storm won’t kill the topology right now. Instead, it deactivates all of the spouts so that they don’t emit any greater tuples, after which Storm waits Config.TOPOLOGY_MESSAGE_TIMEOUT_SECS seconds before destroying all of the people. This offers the topology enough time to finish any tuples it become processing whilst it got killed.

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Question 23. What Is Combiner Aggregator?

Answer :

A Combiner Aggregator is used to combine a set of tuples right into a single field. It has the subsequent signature:

public interface CombinerAggregator 
 T init (TridentTuple tuple);
 T integrate(T val1, T val2);
 T 0();
 

Storm calls the init() technique with every tuple, and then again and again calls the combine()technique until the partition is processed. The values surpassed into the combine() approach are partial aggregations, the end result of combining the values returned through calls to init().

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Question 24. Is It Necessary To Kill The Topology While Updating The Running Topology?

Answer :

Yes, to replace a walking topology, the handiest alternative currently is to kill the current topology and resubmit a new one. A deliberate feature is to put in force a Storm change command that swaps a strolling topology with a brand new one, making sure minimal downtime and no risk of each topologies processing tuples at the identical time.

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Question 25. Explain How To Write The Output Into A File Using Storm?

Answer :

In Spout, while you are reading record, make FileReader object in Open() technique, as such that point it initializes the reader item for employee node. And use that item in nextTuple() technique.

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Question 26. Mention What Is The Difference Between Apache Kafka And Apache Storm?

Answer :

Apach Kafeka: It is a dispensed and strong messaging device which can cope with big amount of information and allows passage of messages from one stop-factor to every other.

Apache Storm: It is a actual time message processing device, and you could edit or manipulate information in actual time. Apache hurricane pulls the facts from Kafka and applies some required manipulation.

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Question 27. Explain When Using Field Grouping In Storm, Is There Any Time-out Or Limit To Known Field Values?

Answer :

Field grouping in hurricane makes use of a mod hash function to decide which venture to send a tuple, making sure which assignment could be processed in the proper order. For that, you don’t require any cache. So, there is no time-out or restriction to regarded field values.

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Question 28. In Which Folder Are Java Applications Stored In Apache?

Answer :

Java packages are not stored in Apache, it is able to be handiest connected to a different Java webapp web hosting webserver using the mod_jk connector.

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Question 29. What Is Mod_vhost_alias?

Answer :

This module creates dynamically configured virtual hosts, by way of allowing the IP cope with and/or the Host: header of the HTTP request for use as a part of the pathname to decide what files to serve. This lets in for easy use of a big variety of virtual hosts with comparable configurations.

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Question 30. What Is Struct And Explain Its Purpose?

Answer :

A struts is a open source framework for developing a Java net packages.

Question 31. List The Various Components In Kafka?

Answer :

The four important additives of Kafka are:

Topic – a circulate of messages belonging to the identical kind
Producer – that could put up messages to a topic
Brokers – a set of servers where the publishes messages are stored
Consumer – that subscribes to diverse topics and pulls facts from the brokers.
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Question 32. Explain The Role Of The Offset?

Answer :

Messages contained within the walls are assigned a completely unique ID wide variety that is known as the offset. The role of the offset is to uniquely discover every message within the partition.

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Question 33. Explain The Concept Of Leader And Follower?

Answer :

Every partition in Kafka has one server which performs the position of a Leader, and none or greater servers that act as Followers. The Leader plays the assignment of all read and write requests for the partition, whilst the role of the Followers is to passively reflect the chief. In the occasion of the Leader failing, one of the Followers will take at the role of the Leader. This guarantees load balancing of the server.

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Question 34. How Do You Define A Partitioning Key?

Answer :

Within the Producer, the function of a Partitioning Key is to signify the destination partition of the message. By default, a hashing-based Partitioner is used to decide the partition ID given the key. Alternatively, users can also use customized Partitions.

Question 35. In The Producer, When Does Queuefullexception Occur?

Answer :

QueueFullException generally occurs whilst the Producer attempts to send messages at a tempo that the Broker can't deal with. Since the Producer doesn’t block, users will need to add sufficient agents to collaboratively deal with the accelerated load.

Question 36. Explain The Role Of The Kafka Producer Api.

Answer :

The function of Kafka’s Producer API is to wrap the two producers – kafka.Manufacturer.SyncProducer and the kafka.Producer.Async.AsyncProducer. The purpose is to show all the manufacturer capability via a single API to the client.

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