Hadoop Administrator Interview Questions Part 1

Following are some questions and answers to ask a Hadoop Administrator Interviewee


Q1. What are the default configuration files that are used in Hadoop 
As of 0.20 release, Hadoop supported the following read-only default configurations
- src/core/core-default.xml
- src/hdfs/hdfs-default.xml
- src/mapred/mapred-default.xml

Q2. How will you make changes to the default configuration files 
Hadoop does not recommends changing the default configuration files, instead it recommends making all site specific changes in the following files
- conf/core-site.xml
- conf/hdfs-site.xml
- conf/mapred-site.xml

Unless explicitly turned off, Hadoop by default specifies two resources, loaded in-order from the classpath:
- core-default.xml : Read-only defaults for hadoop.
- core-site.xml: Site-specific configuration for a given hadoop installation.

Hence if same configuration is defined in file core-default.xml and src/core/core-default.xml then the values in file core-default.xml (same is true for other 2 file pairs) is used.

Q3. Consider case scenario where you have set property mapred.output.compress to true to ensure that all output files are compressed for efficient space usage on the cluster.  If a cluster user does not want to compress data for a specific job then what will you recommend him to do ? 
Ask him to create his own configuration file and specify configuration mapred.output.compress to false and load this file as a resource in his job.

Q4. In the above case scenario, how can ensure that user cannot override the configuration mapred.output.compress to false in any of his jobs
This can be done by setting the property final to true in the core-site.xml file

Q5. What of the following is the only required variable that needs to be set in file conf/hadoop-env.sh for hadoop to work 

- HADOOP_LOG_DIR

- JAVA_HOME

- HADOOP_CLASSPATH
The only required variable to set is JAVA_HOME that needs to point to <java installation> directory


Q6. List all the daemons required to run the Hadoop cluster 
- NameNode
- SecondaryNameNode
- DataNode
- JobTracker
- TaskTracker



Q7. Whats the default port that jobtrackers listens to
50030


Q8. Whats the default  port where the dfs namenode web ui will listen on
50070

Java interview questions for Hadoop developer Part 3

 Q21. Explain difference of Class Variable and Instance Variable and how are they declared in Java 
Class Variable is a variable which is declared with static modifier.
Instance variable is a variable in a class without static modifier.
The main difference between the class variable and Instance variable is, that first time, when class is loaded in to memory, then only memory is allocated for all class variables. That means, class variables do not depend on the Objets of that classes. What ever number of objects are there, only one copy is created at the time of class loding.

Q22. Since an Abstract class in Java cannot be instantiated then how can you use its non static methods 
By extending it

Q23. How would you make a copy of an entire Java object with its state? 
Have this class implement Cloneable interface and call its method clone().

Q24. Explain Encapsulation,Inheritance and Polymorphism 
Encapsulation is a process of binding or wrapping the data and the codes that operates on the data into a single entity. This keeps the data safe from outside interface and misuse. One way to think about encapsulation is as a protective wrapper that prevents code and data from being arbitrarily accessed by other code defined outside the wrapper.
Inheritance is the process by which one object acquires the properties of another object.
The meaning of Polymorphism is something like one name many forms. Polymorphism enables one entity to be used as as general category for different types of actions. The specific action is determined by the exact nature of the situation. The concept of polymorphism can be explained as "one interface, multiple methods".

Q25. Explain garbage collection? 
Garbage collection is one of the most important feature of Java.
Garbage collection is also called automatic memory management as JVM automatically removes the unused variables/objects (value is null) from the memory. User program cann't directly free the object from memory, instead it is the job of the garbage collector to automatically free the objects that are no longer referenced by a program. Every class inherits finalize() method from java.lang.Object, the finalize() method is called by garbage collector when it determines no more references to the object exists. In Java, it is good idea to explicitly assign null into a variable when no more in us

Q26. What is similarities/difference between an Abstract class and Interface? 
Differences- Interfaces provide a form of multiple inheritance. A class can extend only one other class.
- Interfaces are limited to public methods and constants with no implementation. Abstract classes can have a partial implementation, protected parts, static methods, etc.
- A Class may implement several interfaces. But in case of abstract class, a class may extend only one abstract class.
- Interfaces are slow as it requires extra indirection to find corresponding method in in the actual class. Abstract classes are fast.
Similarities
- Neither Abstract classes or Interface can be instantiated

Q27. What are different ways to make your class multithreaded in Java 
There are two ways to create new kinds of threads:
- Define a new class that extends the Thread class
- Define a new class that implements the Runnable interface, and pass an object of that class to a Thread's constructor.

Q28. What do you understand by Synchronization? How do synchronize a method call in Java? How do you synchonize a block of code in java ?
Synchronization is a process of controlling the access of shared resources by the multiple threads in such a manner that only one thread can access one resource at a time. In non synchronized multithreaded application, it is possible for one thread to modify a shared object while another thread is in the process of using or updating the object's value. Synchronization prevents such type of data corruption.
- Synchronizing a method: Put keyword synchronized as part of the method declaration
- Synchronizing a block of code inside a method: Put block of code in synchronized (this) { Some Code }

Q29. What is transient variable? 
Transient variable can't be serialize. For example if a variable is declared as transient in a Serializable class and the class is written to an ObjectStream, the value of the variable can't be written to the stream instead when the class is retrieved from the ObjectStreamthe value of the variable becomes null.

Q30. What is Properties class in Java. Which class does it extends? 
The Properties class represents a persistent set of properties. The Properties can be saved to a stream or loaded from a stream. Each key and its corresponding value in the property list is a string

Q31. Explain the concept of shallow copy vs deep copy in Java 
In case of shallow copy, the cloned object also refers to the same object to which the original object refers as only the object references gets copied and not the referred objects themselves.
In case deep copy, a clone of the class and all all objects referred by that class is made.

Q32. How can you make a shallow copy of an object in Java 
Use clone() method inherited by Object class

Q33. How would you make a copy of an entire Java object (deep copy) with its state? 
Have this class implement Cloneable interface and call its method clone().

Java interview questions for Hadoop developer Part 2

Q11. Which of the following object oriented principal is met with method overloading in java
- Inheritance
- Polymorphism
- Inheritance 
Polymorphism

Q12. Which of the following object oriented principal is met with method overriding in java
- Inheritance
- Polymorphism
- Inheritance 
Polymorphism

Q13. What is the name of collection interface used to maintain unique elements 
Map

Q14. What access level do you need to specify in the class declaration to ensure that only classes from the same directory can access it? What keyword is used to define this specifier? It has to have default specifier.
You do not need to specify any access level, and Java will use a default package access level

Q15. What's the difference between a queue and a stack? 
Stacks works by last-in-first-out rule (LIFO), while queues use the FIFO rule

Q16. How can you write user defined exceptions in Java 
Make your class extend Exception Class

Q17. What is the difference between checked and Unchecked Exceptions in Java ? Give an example of each type 
All predefined exceptions in Java are either a checked exception or an unchecked exception. Checked exceptions must be caught using try .. catch() block or we should throw the exception using throws clause. If you dont, compilation of program will fail.
- Example checked Exception: ParseTextException
- Example unchecked exception: ArrayIndexOutOfBounds

Q18. We know that FileNotFoundExceptionis inherited from IOExceptionthen does it matter in what order catch statements for FileNotFoundExceptionand IOExceptipon are written? 
Yes, it does. The FileNoFoundExceptionis inherited from the IOException. Exception's subclasses have to be caught first.

Q19. How do we find if two string are same or not in Java. If answer is equals() then why do we have to use equals, why cant we compare string like integers 
We use method equals() to compare the values of the Strings. We can't use == like we do for primitive types like int because == checks if two variables point at the same instance of a String object.

Q20. What is "package" keyword 
This is a way to organize files when a project consists of multiple modules. It also helps resolve naming conflicts when different packages have classes with the same names. Packages access level also allows you to protect data from being used by the non-authorized classes

Java interview questions for Hadoop developer Part 1

Since Hadoop and all its eco-system is built in java hence when hiring for a hadoop developer it makes sense to test the core java skills of the interviewee as well. Following are some questions that I have compiled that test the basic java understanding of the candidate. I would expect any decent candidate to answer 90% of these questions

Q1. What is mutable object and immutable object
If a object value is changeable then we can call it as Mutable object. (Ex., StringBuffer) If you are not allowed to change the value of an object, it is immutable object. (Ex., String, Integer, Float)

Q2. What are wrapped classes in Java. Why do they exist. Give examples 
Wrapped classes are classes that allow primitive types to be accessed as objects, e.g. Integer, Float etc

Q3. Even though garbage collection cleans memory, why can't it guarantee that a program will run out of memory? Give an example of a case when garbage collection will run out ot memory 
Because it is possible for programs to use up memory resources faster than they are garbage collected. It is also possible for programs to create objects that are not subject to garbage collection. Once example can be if yuo try to load a very big file into an array.

Q4. What is the difference between Process and Thread? 
A process can contain multiple threads. In most multithreading operating systems, a process gets its own memory address space; a thread doesn't. Threads typically share the heap belonging to their parent process. For instance, a JVM runs in a single process in the host O/S. Threads in the JVM share the heap belonging to that process; that's why several threads may access the same object. Typically, even though they share a common heap, threads have their own stack space. This is how one thread's invocation of a method is kept separate from another's

Q5. How can you write a indefinate loop in java 
while(true) {
}
OR
for ( ; ; ){
}

Q6. How can you create singleton class in Java 
Make the constructor of the class private and provide a static method to get instance of the class

Q7. What do keywords "this" and "super" do in Java 
"this" is used to refer to current object. "super" is used to refer to the class extended by the current class

Q8. What are access specifiers in java. List all of them. Access specifiers are used to define score of variables in Java. There are four levels of access specifiers in java- public
- private
- protected
- default

Q9. Which of the following 3 object oriented principals does access specifiers implement in java
- Encapsulation
- Polymorphism
- Intheritance 
Encapsulation

Q10. What is method overriding and method overloading 
With overriding, you change the method behavior for a subclass class. Overloading involves having a method with the same name within the class with different signature

Hadoop Distributed File Systems (HDFS) Interview Questions

Q1. What is HDFS  HDFS, the Hadoop Distributed File System, is a distributed file system designed to hold very large amounts of data (terabytes or even petabytes), and provide high-throughput access to this information. Files are stored in a redundant fashion across multiple machines to ensure their durability to failure and high availability to very parallel applications

Q2. What does the statement "HDFS is block structured file system" means  It means that in HDFS individual files are broken into blocks of a fixed size. These blocks are stored across a cluster of one or more machines with data storage capacity

Q3. What does the term "Replication factor" mean  Replication factor is the number of times a file needs to be replicated in HDFS

Q4. What is the default replication factor in HDFS  3

Q5. What is the typical block size of an HDFS block  64Mb to 128Mb

Q6. What is the benefit of having such big block size (when compared to block size of linux file system like ext)  It allows HDFS to decrease the amount of metadata storage required per file (the list of blocks per file will be smaller as the size of individual blocks increases). Furthermore, it allows for fast streaming reads of data, by keeping large amounts of data sequentially laid out on the disk

Q7. Why is it recommended to have few very large files instead of a lot of small files in HDFS  This is because the Name node contains the meta data of each and every file in HDFS and more files means more metadata and since namenode loads all the metadata in memory for speed hence having a lot of files may make the metadata information big enough to exceed the size of the memory on the Name node

Q8. True/false question. What is the lowest granularity at which you can apply replication factor in HDSF
- You can choose replication factor per directory
- You can choose replication factor per file in a directory
- You can choose replication factor per block of a file
- True
- True
- False

Q9. What is a datanode in HDFS  ndividual machines in the HDFS cluster that hold blocks of data are called datanodes

Q10. What is a Namenode in HDSF  The Namenode stores all the metadata for the file system

Q11. What alternate way does HDFS provides to recover data in case a Namenode, without backup, fails and cannot be recovered  There is no way. If Namenode dies and there is no backup then there is no way to recover data

Q12. Describe how a HDFS client will read a file in HDFS, like will it talk to data node or namenode ... how will data flow etc  To open a file, a client contacts the Name Node and retrieves a list of locations for the blocks that comprise the file. These locations identify the Data Nodes which hold each block. Clients then read file data directly from the Data Node servers, possibly in parallel. The Name Node is not directly involved in this bulk data transfer, keeping its overhead to a minimum.

Q13. Using linux command line. how will you
- List the the number of files in a HDFS directory
- Create a directory in HDFS
- Copy file from your local directory to HDSF

hadoop fs -ls 
hadoop fs -mkdir 
hadoop fs -put localfile hdfsfile 

Hadoop Interview Questions Part 4

Q31. How will you write a custom partitioner for a Hadoop job  
To have hadoop use a custom partitioner you will have to do minimum the following three
- Create a new class that extends Partitioner class
- Override method getPartition
- In the wrapper that runs the Map Reducer, either
  - add the custom partitioner to the job programtically using method setPartitionerClass or
  - add the custom partitioner to the job as a config file (if your wrapper reads from config file or oozie)

Q32. How did you debug your Hadoop code  
There can be several ways of doing this but most common ways are
- By using counters
- The web interface provided by Hadoop framework

Q33. Did you ever built a production process in Hadoop ? If yes then what was the process when your hadoop job fails due to any reason
Its an open ended question but most candidates, if they have written a production job, should talk about some type of alert mechanisn like email is sent or there monitoring system sends an alert. Since Hadoop works on unstructured data, its very important to have a good alerting system for errors since unexpected data can very easily break the job.

Q34. Did you ever ran into a lop sided job that resulted in out of memory error, if yes then how did you handled it
This is an open ended question but a candidate who claims to be an intermediate developer and has worked on large data set (10-20GB min) should have run into this problem. There can be many ways to handle this problem but most common way is to alter your algorithm and break down the job into more map reduce phase or use a combiner if possible.

Hadoop Interview Questions Part 3

Q22. Whats is Distributed Cache in Hadoop
Distributed Cache is a facility provided by the Map/Reduce framework to cache files (text, archives, jars and so on) needed by applications during execution of the job. The framework will copy the necessary files to the slave node before any tasks for the job are executed on that node.

Q23. What is the benifit of Distributed cache, why can we just have the file in HDFS and have the application read it  
This is because distributed cache is much faster. It copies the file to all trackers at the start of the job. Now if the task tracker runs 10 or 100 mappers or reducer, it will use the same copy of distributed cache. On the other hand, if you put code in file to read it from HDFS in the MR job then every mapper will try to access it from HDFS hence if a task tracker run 100 map jobs then it will try to read this file 100 times from HDFS. Also HDFS is not very efficient when used like this.

Q.24 What mechanism does Hadoop framework provides to synchronize changes made in Distribution Cache during runtime of the application  
This is a trick questions. There is no such mechanism. Distributed Cache by design is read only during the time of Job execution

Q25. Have you ever used Counters in Hadoop. Give us an example scenario
Anybody who claims to have worked on a Hadoop project is expected to use counters

Q26. Is it possible to provide multiple input to Hadoop? If yes then how can you give multiple directories as input to the Hadoop job  
Yes, The input format class provides methods to add multiple directories as input to a Hadoop job

Q27. Is it possible to have Hadoop job output in multiple directories. If yes then how  
Yes, by using Multiple Outputs class

Q28. What will a hadoop job do if you try to run it with an output directory that is already present? Will it
- overwrite it
- warn you and continue
- throw an exception and exit
The hadoop job will throw an exception and exit.

Q29. How can you set an arbitary number of mappers to be created for a job in Hadoop  
This is a trick question. You cannot set it

Q30. How can you set an arbitary number of reducers to be created for a job in Hadoop  
You can either do it progamatically by using method setNumReduceTasksin the JobConfclass or set it up as a configuration setting

Hadoop Interview Questions Part 2

Q11. Give an example scenario where a cobiner can be used and where it cannot be used

There can be several examples following are the most common ones

- Scenario where you can use combiner

  Getting list of distinct words in a file

- Scenario where you cannot use a combiner

  Calculating mean of a list of numbers 

Q12. What is job tracker

Job Tracker is the service within Hadoop that runs Map Reduce jobs on the cluster

Q13. What are some typical functions of Job Tracker

The following are some typical tasks of Job Tracker

- Accepts jobs from clients

- It talks to the NameNode to determine the location of the data

- It locates TaskTracker nodes with available slots at or near the data

- It submits the work to the chosen Task Tracker nodes and monitors progress of each task by receiving heartbeat signals from Task tracker 

Q14. What is task tracker

Task Tracker is a node in the cluster that accepts tasks like Map, Reduce and Shuffle operations - from a JobTracker 

Q15. Whats the relationship between Jobs and Tasks in Hadoop

One job is broken down into one or many tasks in Hadoop. 

Q16. Suppose Hadoop spawned 100 tasks for a job and one of the task failed. What will hadoop do ?

It will restart the task again on some other task tracker and only if the task fails more than 4 (default setting and can be changed) times will it kill the job

Q17. Hadoop achieves parallelism by dividing the tasks across many nodes, it is possible for a few slow nodes to rate-limit the rest of the program and slow down the program. What mechanism Hadoop provides to combat this  

Speculative Execution 

Q18. How does speculative execution works in Hadoop  

Job tracker makes different task trackers process same input. When tasks complete, they announce this fact to the Job Tracker. Whichever copy of a task finishes first becomes the definitive copy. If other copies were executing speculatively, Hadoop tells the Task Trackers to abandon the tasks and discard their outputs. The Reducers then receive their inputs from whichever Mapper completed successfully, first. 

Q19. Using command line in Linux, how will you 

- see all jobs running in the hadoop cluster

- kill a job

- hadoop job -list

- hadoop job -kill jobid 

Q20. What is Hadoop Streaming  

Streaming is a generic API that allows programs written in virtually any language to be used as Hadoop Mapper and Reducer implementations 

Q21. What is the characteristic of streaming API that makes it flexible run map reduce jobs in languages like perl, ruby, awk etc.  

Hadoop Streaming allows to use arbitrary programs for the Mapper and Reducer phases of a Map Reduce job by having both Mappers and Reducers receive their input on stdin and emit output (key, value) pairs on stdout.

Hadoop Interview Questions Part 1

Q1. Name the most common InputFormats defined in Hadoop? Which one is default ?
Following 2 are most common InputFormats defined in Hadoop
- TextInputFormat
- KeyValueInputFormat
- SequenceFileInputFormat

TextInputFormatis the hadoop default

Q2. What is the difference between TextInputFormatand KeyValueInputFormat class
TextInputFormat: It reads lines of text files and provides the offset of the line as key to the Mapper and actual line as Value to the mapper
KeyValueInputFormat: Reads text file and parses lines into key, val pairs. Everything up to the first tab character is sent as key to the Mapper and the remainder of the line is sent as value to the mapper.

Q3. What is InputSplit in Hadoop

When a hadoop job is run, it splits input files into chunks and assign each split to a mapper to process. This is called Input Split 

Q4. How is the splitting of file invoked in Hadoop Framework  

It is invoked by the Hadoop framework by running getInputSplit()method of the Input format class (like FileInputFormat) defined by the user 

Q5. Consider case scenario: In M/R system,

    - HDFS block size is 64 MB

    - Input format is FileInputFormat

    - We have 3 files of size 64K, 65Mb and 127Mb 

then how many input splits will be made by Hadoop framework?

Hadoop will make 5 splits as follows 

- 1 split for 64K files 

- 2  splits for 65Mb files 

- 2 splits for 127Mb file 

Q6. What is the purpose of RecordReader in Hadoop

The InputSplithas defined a slice of work, but does not describe how to access it. The RecordReaderclass actually loads the data from its source and converts it into (key, value) pairs suitable for reading by the Mapper. The RecordReader instance is defined by the InputFormat 

Q7. After the Map phase finishes, the hadoop framework does "Partitioning, Shuffle and sort". Explain what happens in this phase?

- Partitioning

Partitioning is the process of determining which reducer instance will receive which intermediate keys and values. Each mapper must determine for all of its output (key, value) pairs which reducer will receive them. It is necessary that for any key, regardless of which mapper instance generated it, the destination partition is the same

- Shuffle

After the first map tasks have completed, the nodes may still be performing several more map tasks each. But they also begin exchanging the intermediate outputs from the map tasks to where they are required by the reducers. This process of moving map outputs to the reducers is known as shuffling.

- Sort

Each reduce task is responsible for reducing the values associated with several intermediate keys. The set of intermediate keys on a single node is automatically sorted by Hadoop before they are presented to the Reducer 

Q9. If no custom partitioner is defined in the hadoop then how is data partitioned before its sent to the reducer  

The default partitioner computes a hash value for the key and assigns the partition based on this result 

Q10. What is a Combiner 

The Combiner is a "mini-reduce" process which operates only on data generated by a mapper. The Combiner will receive as input all data emitted by the Mapper instances on a given node. The output from the Combiner is then sent to the Reducers, instead of the output from the Mappers.