Hadoop Interview Questions and Answers
Question - 41 : - What is the significance of Sqoop’s eval tool?
Answer - 41 : -
The eval tool in Sqoop enables users to carry out user-defined queries on the corresponding database servers and check the outcome in the console.
Question - 42 : - Can you name the default file formats for importing data using Apache Sqoop?
Answer - 42 : -
Commonly, there are two file formats in Sqoop to import data. They are:
- Delimited Text File Format
- Sequence File Format
Question - 43 : - What is the jps command used for?
Answer - 43 : -
The jps command is used to know or check whether the Hadoop daemons are running or not. The active or running status of all Hadoop daemons, which are namenode, datanode, resourcemanager, nodemanager, are displayed by this command.
Question - 44 : - What are the core methods of a reducer?
Answer - 44 : -
The three core methods of a reducer are as follows:
- setup(): This method is used for configuring various parameters such as input data size and distributed cache.
- public void setup (context)
- reduce(): This method is the heart of the reducer and is always called once per key with the associated reduced task.
- public void reduce(Key, Value, context)
- cleanup(): This method is called to clean the temporary files, only once at the end of the task.
public void cleanup (context)
Question - 45 : - What is Apache Flume? List the components of Apache Flume
Answer - 45 : -
Apache Flume is a tool or system, in Hadoop, that is used for assembling, aggregating, and carrying large amounts of streaming data. This can include data such as record files, events, etc. The main function of Apache Flume is to carry this streaming data from various web servers to HDFS.
The components of Apache Flume are as below:
- Flume Channel
- Flume Source
- Flume Agent
- Flume Sink
- Flume Event
Question - 46 : - List the configuration parameters in a MapReduce program
Answer - 46 : -
The configuration parameters in MapReduce are given below:
- Input locations of Jobs in the distributed file system
- Output location of Jobs in the distributed file system
- The input format of data
- The output format of data
- The class containing the map function
- The class containing the reduce function
- JAR file containing the classes—mapper, reducer, and driver
Question - 47 : - What is the default file size of an HDFS data block?
Answer - 47 : -
Hadoop keeps the default file size of an HDFS data block as 128 mb.
Question - 48 : - Why are the data blocks in HDFS so huge?
Answer - 48 : -
The reason behind the large size of the data blocks in HDFS is that the transfer happens at the disk transfer rate in the presence of large-sized blocks. On the other hand, if the size is kept small, there will be a large number of blocks to be transferred, which will force the HDFS to store too much metadata, thus increasing traffic.
Question - 49 : - What is a SequenceFile in Hadoop?
Answer - 49 : -
Extensively used in MapReduce I/O formats, SequenceFile is a flat-file containing binary key-value pairs. The map outputs are stored as SequenceFile internally. It provides reader, writer, and sorter classes. The three SequenceFile formats are as follows:
- Uncompressed key-value records
- Record compressed key-value records—only values are compressed here
- Block compressed key-value records—both keys and values are collected in blocks separately and compressed. The size of the block is configurable
Question - 50 : - What do you mean by WAL in HBase?
Answer - 50 : -
WAL is otherwise referred to as a write ahead log. This file is attached to each Region Server present inside the distributed environment. WAL stores the new data, which is yet to be kept in permanent storage. WAL is often used to recover datasets in case of any failure.