Apache Flume Interview Questions And Answers 2020

Apache Flume Interview Questions And Answers prepared from Codingcompiler experts. These Apache FlumeInterview Questions were asked in various interviews conducted by top multinational companies across the globe. We hope that these interview questions on Apache Flume will help you in cracking your next job interview. All the best and happy learning.

In this article, you’ll learn

Apache Flume Interview Questions
Apache Flume Interview Questions And Answers
Advanced Apache Flume interview Questions And Answers
The Best Apache Flume Interview Questions And Answers

Apache Flume Interview Questions

  1. What is Apache Flume?
  2. Why we are using Flume?
  3. What is Flume Agent?
  4.  Explain the core components of Flume.
  5.  What is Flume event?
  6. What is a channel?
  7. Explain about the different channel types in Flume. Which channel type is faster?
  8. Explain about the replication and multiplexing selectors in Flume.
  9. Does Apache Flume provide support for third party plug-ins?
  10. What is sink processors?

Apache Flume Interview Questions And Answers


1. What is Apache Flume?

Answer: As we know, while it comes to efficiently and reliably collect, aggregate and transfer massive amounts of data from one or more sources to a centralized data source we use Apache Flume. However, it can ingest any kind of data including log data, event data, network data, social-media generated data, email messages, message queues etc since data sources are customizable in Flume. Flume is a reliable distributed service for collection and aggregation of large amount of streaming data into HDFS. Most of the Bigdata analysts use Apache Flume to push data from different sources like Twitter, Facebook, & LinkedIn into Hadoop, Strom, Solr, Kafka & Spark.

2. Why we are using Flume?

Answer: Most often Hadoop developer use this tool to get log data from social media sites. It’s developed by Cloudera for aggregating and moving very large amount of data. The primary use is gather log files from different sources and asynchronously persists in the Hadoop cluster.

3. What is Flume Agent?

Answer: A Flume agent is a JVM process that holds the Flume core components (Source, Channel, Sink) through which events flow from an external source like web-servers to destination like HDFS. Agent is heart of the Apache Flume.

4. Explain the core components of Flume.

Answer: There are various core components of Flume available. They are –

  • Event-  Event is the single log entry or unit of data which we transport further.
  • Source-  Source is the component by which data enters Flume workflows.
  • Sink- For transporting data to the desired destination sink is responsible.
  • Channel-Channel is nothing but a  duct between the Sink and Source.
  • Agent- Agent is what we have known as any JVM that runs Flume.
  • Client- Client transmits the event to the source that operates with the agent.

5. What is Flume event?

Answer: A unit of data with set of string attributes called Flume event. The external source like web-server sends events to the source. Internally Flume has inbuilt functionality to understand the source format. For example Avro sends events from Avro sources to the Flume.

Each log file is considered as an event. Each event has header and value sectors, which has header information and appropriate value that assign to the particular header.

6. What is a channel?

Answer: A transient store that receives the events from the source also buffers them till they are consumed by sinks is what we call a Flume channel. To be very specific it acts as a bridge between the sources and the sinks in Flume.

Basically, these channels can work with any number of sources and sinks are they are fully transactional.

Like − JDBC channel, File system channel, Memory channel, etc.

7. Explain about the different channel types in Flume. Which channel type is faster?

Answer: The 3 different built in channel types available in Flume are-

MEMORY Channel – Events are read from the source into memory and passed to the sink.

JDBC Channel – JDBC Channel stores the events in an embedded Derby database.

FILE Channel –File Channel writes the contents to a file on the file system after reading the event from a source. The file is deleted only after the contents are successfully delivered to the sink.

MEMORY Channel is the fastest channel among the three however has the risk of data loss. The channel that you choose completely depends on the nature of the big data application and the value of each event.

8. Explain about the replication and multiplexing selectors in Flume.

Answer: Channel Selectors are used to handle multiple channels. Based on the Flume header value, an event can be written just to a single channel or to multiple channels. If a channel selector is not specified to the source then by default it is the Replicating selector. Using the replicating selector, the same event is written to all the channels in the source’s channels list. Multiplexing channel selector is used when the application has to send different events to different channels.

9. Does Apache Flume provide support for third party plug-ins?

Answrer: Most of the data analysts use Apache Flume has plug-in based architecture as it can load data from external sources and transfer it to external destinations.

10. What is sink processors?

Answer: Sink processors is a mechanism by which you can create a fail-over task and load balancing.

Advanced Apache Flume interview Questions And Answers

11. What are the complicated steps in Flume configurations?

Answer: Flume can processing streaming data. so if started once, there is no stop/end to the process. asynchronously it can flows data from source to HDFS via agent. First of all agent should know individual components how they are connected to load data. so configuration is trigger to load streaming data. for example consumerkey, consumersecret accessToken and accessTokenSecret are key factor to download data from twitter.

12. Does Apache Flume provide support for third-party plug-ins?

Answer: Most of the data analysts use Apache Flume has plug-in based architecture as it can load data from external sources and transfer it to external destinations.

13. Does Apache Flume support third-party plugins?

Answer: Yes, Flume has 100% plugin-based architecture, it can load and ships data from external sources to external destinations which separately from Flume. SO that most of the big data analysis uses this tool for streaming data.

14: What’s FlumeNG?

Answer: FlumeNG is nothing however a period loader for streaming your knowledge into Hadoop. Basically, it stores knowledge in HDFS and HBase. Thus, if we wish to urge started with FlumeNG, it improves on the first flume.

15. Can Flume can distribute data to multiple destinations?

Answer:  Yes. It supports multiplexing flow. The event flows from one source to multiple channels and multiple destinations, It is achieved by defining a flow multiplexer.

16. Is it possible to leverage real-time analysis on the big data collected by Flume directly? If yes, then explain how?

Answer: Data from Flume can be extracted, transformed and loaded in real-time into Apache Solr servers using MorphlineSolrSink.

17. Differentiate between FileSink and FileRollSink

Answer: The major difference between HDFS FileSink and FileRollSink is that HDFS File Sink writes the events into the Hadoop Distributed File System (HDFS) whereas File Roll Sink stores the events into the local file system.

18. Agent communicates with other Agents?

Answer: NO each agent runs independently. Flume can easily horizontally. As a result, there is no single point of failure.

19: What are the Data extraction tools in Hadoop?

Answer: Sqoop can be used to transfer data between RDBMS and HDFS. Flume can be used to extract the streaming data from social media, weblog, etc. and store it on HDFS.

20. How do you handle agent failures?

Answer: If the Flume agent goes down, then all flows hosted on that agent are aborted. Once the agent is restarted then the flow will resume. If the channel is set up as an in-memory channel, then all events that are stored in the channel when the agent went down are lost. But channel set up as a file or other stable channels will continue to process events where it left off.

The Best Apache Flume Interview Questions And Answers

21. Explain What Are The Tools Used In Big Data?

Answer :

Tools used in Big Data includes

  • Hadoop
  • Hive
  • Pig
  • Flume
  • Mahout
  • Sqoop

22. Tell Any Two Features Of Flume?

Answer :

Fume collects data efficiently, aggregate and moves large amount of log data from many different sources to centralized data store.

Flume is not restricted to log data aggregation and it can transport massive quantity of event data including but not limited to network traffic data, social-media generated data , email message na pretty much any data storage.

23. Explain Reliability And Failure Handling In Apache Flume?

Answer :

Flume NG uses channel-based transactions to guarantee reliable message delivery. When a message moves from one agent to another, two transactions are started, one on the agent that delivers the event and the other on the agent that receives the event. In order for the sending agent to commit it’s transaction, it must receive success indication from the receiving agent.

The receiving agent only returns a success indication if it’s own transaction commits properly first. This ensures guaranteed delivery semantics between the hops that the flow makes. Figure  below shows a sequence diagram that illustrates the relative scope and duration of the transactions operating within the two interacting agents.

24. How do you install third-party plugins into Flume? OR Why do you need third-party plugins in Flume? OR What are the different ways you can install plugins into flume?

Answer: Flume is a plugin-based architecture. It ships with many out-of-the-box sources, channels and sinks. Many other customized components exist seperately from Flume which can be pluged into Flume and used for you applications. Or you can write your own custom components and plug them into Flume.

There are two ways to add plugins to Flume.

Add the plugin jar files to FLUME_CLASSPATH variable in the flume-env.sh file.

25. What do you mean by consolidation in Flume? Or How do you injest data from multiple sources into a single terminal destination?

Answer: Flume can be setup to have multiple agents process data from multiple sources and send to a single or a few intermiate destimations. Separate agents consume messages from the intermediate data source and write to a central data source.

26.  Will flume give 100 percent responsibleness to the information flow?

Answer: Flume usually offers the end-to-end responsibleness of the flow. Also, it uses a transactional approach to the information flow, by default.

In addition, supply and sink encapsulate in a very transactional repository provides the channels. Moreover, to pass dependably from finish to finish flow these channels area unit accountable. Hence, it offers 100 percent responsibleness to the information flow.

27. Differentiate between FileSink and FileRollSink?

Answer: The major difference between HDFS FileSink and FileRollSink is that HDFS File Sink writes the events into the Hadoop Distributed File System (HDFS) whereas File Roll Sink stores the events into the local file system.

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