Data Cloud (IT) Role

BFS can be used to solve this question.
Steps :
1. Traverse the whole tree in level order fashion using BFS along with storing the last processed node (curr).
2. Keep a tag at the end of each level to know that a particular level has ended.
3. Whenever a level ends store the last processed node value to the resultant list.
Time Complexity : O(n) [ Since, each node is traversed exactly once ]
Space Complexity : O(w) [ 'w' is the maximum width of the tree ]

Concept of indexing can be used to solve this question.
Traverse the array. For every element at index i,visit a[i]. If a[i] is positive, then change it to negative. If a[i] is negative, it means the element has already been visited and thus it is repeated. Print that element.
Pseudocode :
findRepeating(arr[], n)
{
missingElement = 0

for (i = 0; i < n; i++){
element = arr[abs(arr[i])]

if(element < 0){
missingElement = arr[i]
break
}

arr[abs(arr[i])] = -arr[abs(arr[i])]
}

return abs(missingElement)

}

A hash table is the simplest index structure that a database can implement. The major components of a hash index is the "hash function" and the "buckets". Effectively the DBMS constructs an index for every table you create that has a primary key attribute, like:
CREATE TABLE test (
id INTEGER PRIMARY KEY
,name varchar(100)
);
In table test, if we have decided to store 4 rows then the algorithm splits the places which the rows are to be stored into areas. These areas are called buckets. If a row's primary key matches the requirements to be stored in that bucket, then that is where it will be stored. The algorithm to decide which bucket to use is called the hash function.
In DBMS systems we can usually ask for a hash index for a table, and also say how many buckets we thing we will need.
B and B+ trees are also currently used for providing indexes.

1. MongoDB has the potential for ACID (atomicity, consistency, isolation, durability) compliance, while Postgres has ACID compliance built-in.
2. MongoDB uses collections for the same purpose that Postgres uses tables. These collections include options for setting validation rules and setting maximum sizes. Postgres describes tables in a very specific language and structures the data in such a way that the database or an ETL tool can process it. 
3. Another example of the difference in terminology and syntax between the two is that MongoDB uses documents to obtain data while Postgres uses rows for the same purpose. 
4. While MongoDB does not support FOREIGN KEY constraints, PostgreSQL does. 
5. MongoDB aggregation pipelines are made up of multiple stages to transform data. Postgres uses GROUP_BY to run queries while MongoDB uses the aggregation pipeline.

A Binary Heap is a Binary Tree with following properties.
1) It’s a complete tree (All levels are completely filled except possibly the last level and the last level has all keys as left as possible). 
2) A Binary Heap is either Min Heap or Max Heap. In a Min Binary Heap, the key at root must be minimum among all keys present in Binary Heap. The same property must be recursively true for all nodes in Binary Tree. Max Heap is similar to MinHeap.

Representation of Min Heap :
So basically Min Heap is a complete binary tree. A Min heap is typically represented as an array. The root element will be at Arr[0]. For any ith node, i.e., Arr[i] : 
Arr[(i -1) / 2] returns its parent node.
Arr[(2 * i) + 1] returns its left child node.
Arr[(2 * i) + 2] returns its right child node.

Operations on Heap :
1. Insertion
Add the node to the bottom of the tree.
Look at the parent node. If the parent is greater than the node, swap them.
Continue comparing and swapping to allow the node to move upwards until it finds a parent node that is smaller than it.

insert(int element) {
Heap[++size] = element; 
int current = size;
heapify(current);
}

2. Deletion
Take the bottom level’s right most node and move it to top, replacing the deleted node.
Compare the new root to its children. If it is larger than either child, swap the item with the smaller of the two children.
Continue comparing and swapping, move downward the node until it is smaller than both of its children.
extractMin() {
int min = Heap[0];
Heap[0] = Heap[size--];
heapify(0);
return min;
}

Tip 1 : Be sure to do your homework on the organization and its culture before the interview.
Tip 2 : Employers want to understand how you use your time and energy to stay productive and efficient. Be sure to emphasize that you adhere to deadlines and take them seriously.
Tip 3 : Talk about a relevant incident that made you keen on the profession you are pursuing and follow up by discussing your education.