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Apache Flume Interview Questions

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by Ravindra Savaram
Last modified: July 16th 2021

If you're looking for Apache Flume Interview Questions & Answers for Experienced or Freshers, you are at the right place. There are a lot of opportunities from many reputed companies in the world. According to research Apache Flume has a market share of about 70.37%. So, You still have the opportunity to move ahead in your career in Apache Flume Development. Mindmajix offers Advanced Apache Flume Interview Questions 2021 that helps you in cracking your interview & acquire a dream career as an Apache Flume Developer.

Best Apache Flume Interview Questions And Answers

1. What is Flume?

Flume is a reliable distributed service for the collection and aggregation of a 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?

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

3. What is Flume Agent?

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 a destination like HDFS. The agent is the heart of the Apache Flume.

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4. What is a Flume event?

A unit of data with the set of string attributes called Flume event. The external source like the webserver 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 an event. Each event has header and value sectors, which have header information and appropriate value that assign to the particular header.

5. What are Flume Core components?

The following are the core components:

  • Source, Channels, and Sink are core components in Apache Flume.
  • When Flume source receives events from external sources, it stores the event in one or multiple channels.
  • The flume channel is temporarily stored & keeps the event until it’s consumed by the Flume sink. It acts as a Flume repository.
  • Flume Sink removes the event from the channel and puts it into an external repository like HDFS or Move to the next Flume agent.

6. Can Flume provides 100% reliability to the data flow?

Yes, it provides end-to-end reliability of the flow. By default, Flume uses a transactional approach in the data flow. Sources and sinks are encapsulated in a transactional repository provided by the channels. These channels are responsible to pass reliably from end to end in the flow. So it provides 100% reliability to the data flow.

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7. Can you explain about configuration files?

The agent configuration is stored in the local configuration file. It comprises each agent’s source, sinks, and channel information. Each core component such as source, sink, and channel has properties such as name, type, and set of properties. For example, Avro source needs a hostname, the port number to receive data from an external client. The memory channel should have a maximum queue size in the form of capacity. The sink should have File System URI, Path to create files, frequency of file rotation, and more configurations.

8. What are the complicated steps in Flume configuration?

Flume can process 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 are connected to load data. So the configuration is a trigger to load streaming data. For example consumer key, consumer secret, accessToken, and access token secret are key factors to download data from Twitter.

9. What are the important steps in the configuration?

The following are the steps in the configuration:

  • The configuration file is the heart of Apache Flume’s agent.
  • Every Source must have at least one channel.
  • Every Sink must have only one channel.
  • Every Component must have a specific type.

10. Apache Flume supports third-party plugins also?

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 big data analysts use this tool for streaming data.

11. Can you explain Consolidation in Flume?

The beauty of Flume is Consolidation, it collects data from different sources even its different flume Agents. Flume sources can collect all data flow from different sources and flows through channels and sinks. Finally, send this data to HDFS or the target destination. Flume consolidation

12. Can Flume can distribute data to multiple destinations?

Yes, it supports multiplexing flow. The event flows from one source to multiple channels and multiple destinations. It’s achieved by defining a flow multiplexer.
In the above example, data flows and replicated to HDFS and another sink to destination and another destination is input to another agent.

13. Agent communicate with other Agents?

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

14. What are interceptors?

It’s one of the most frequently asked Flume interview questions. Interceptors are used to filter the events between source and channel, channel and sink. These channels can filter unnecessary or targeted log files. Depends on the requirements you can use n number of interceptors.

15. What are Channel selectors?

Channel selectors control and separating the events and allocate them to a particular channel. There are default/ replicated channel selectors. Replicated channel selectors can replicate the data in multiple/all channels. Multiplexing channel selectors used to separate and aggregate the data based on the event’s header information. It means based on the Sink’s destination, the event aggregate into the particular sink.
Leg example: One sink connected with Hadoop, another with S3 another with Hbase, at that time, Multiplexing channel selectors can separate the events and flow to the particular sink.

16. What are sink processors?

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

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NameRavindra Savaram
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Ravindra Savaram is a Content Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.