Interface Java Interview Questions – Set 10

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Performance of Set interface implementations

HashSet

The HashSet class offers constant-time [ Big O Notation is O(1) ] performance for the basic operations (add, remove, contains and size), assuming the hash function disperses the elements properly among the buckets. Iterating over this set requires time proportional to the sum of the HashSet instance’s size (the number of elements) plus the “capacity” of the backing HashMap instance (the number of buckets). Thus, it’s very important not to set the initial capacity too high (or the load factor too low) if iteration performance is important.

TreeSet

The TreeSet implementation provides guaranteed log(n) time cost for the basic operations (add, remove and contains).

LinkedHashSet

A linked hash set has two parameters that affect its performance: initial capacity and load factor. They are defined precisely as for HashSet. Note, however, that the penalty for choosing an excessively high value for initial capacity is less severe for this class than for HashSet, as iteration times for this class are unaffected by capacity.

Set & List interface extend Collection, so Why doesn’t Map interface extend Collection

Though the Map interface is part of collections framework, it does not extend collection interface. This is by design, and the answer to this questions is best described in Sun’s FAQ Page: This was by design. We feel that mappings are not collections and collections are not mappings. Thus, it makes little sense for Map to extend the Collection interface (or vice versa). If a Map is a Collection, what are the elements? The only reasonable answer is “Key-value pairs”, but this provides a very limited (and not particularly useful) Map abstraction. You can’t ask what value a given key maps to, nor can you delete the entry for a given key without knowing what value it maps to. Collection could be made to extend Map, but this raises the question: what are the keys? There’s no really satisfactory answer, and forcing one leads to an unnatural interface. Maps can be viewed as Collections (of keys, values, or pairs), and this fact is reflected in the three “Collection view operations” on Maps (keySet, entrySet, and values). While it is, in principle, possible to view a List as a Map mapping indices to elements, this has the nasty property that deleting an element from the List changes the Key associated with every element before the deleted element. That’s why we don’t have a map view operation on Lists.

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What is the difference between Input Split and HDFS Block?

The Logical division of data is called Input Split and physical division of data is called HDFS Block

Give the use of the bootstrap panel.

We use panels in bootstrap from the boxing of DOM components.

How JobTracker assign tasks to the TaskTracker?

The TaskTracker periodically sends heartbeat messages to the JobTracker to assure that it is alive. This messages also inform the JobTracker about the number of available slots. This return message updates JobTracker to know about where to schedule task.

What is heartbeat in HDFS?

Heartbeat is a signal which is used between a data node and name node, and between task tracker and job tracker. If the name node or job tracker doesn’t respond to the signal then it is considered that there is some issue with data node or task tracker.

What is the SequenceFileInputFormat in Hadoop?

In Hadoop, SequenceFileInputFormat is used to read files in sequence. It is a specific compressed binary file format which passes data between the output of one MapReduce job to the input of some other MapReduce job.

What are the network requirements for using Hadoop?

Following are the network requirement for using Hadoop:

  • Password-less SSH connection.
  • Secure Shell (SSH) for launching server processes

What is Hadoop?

Hadoop is a distributed computing platform. It is written in Java. It consists of the features like Google File System and MapReduce.

What are the functionalities of JobTracker?

These are the main tasks of JobTracker:

  • To accept jobs from the client.
  • To communicate with the NameNode to determine the location of the data.
  • To locate TaskTracker Nodes with available slots.
  • To submit the work to the chosen TaskTracker node and monitors the progress of each task.