C Program To Re-arrange Even and Odd Elements of An Array

Lets write a C program to re-arrange even and odd elements of an array.

Note: We need to arrange EVEN numbers at the top and ODD numbers to the bottom of the same array.

Example: Expected Input/Output

Enter 5 integer numbers
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15

After re-arranging even and odd elements …
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11
15

Visual Representation

Rearranging even and odd elements of an array

Video Tutorial: C Program To Re-arrange Even and Odd Elements of An Array


[youtube https://www.youtube.com/watch?v=RfAdoYetz3M]

YouTube Link: https://www.youtube.com/watch?v=RfAdoYetz3M [Watch the Video In Full Screen.]

Source Code: C Program To Re-arrange Even and Odd Elements of An Array

#include<stdio.h>

#define N 10

int main()
{
    int a[N], i, j = N, temp;

    printf("Enter %d integer numbers\n", N);
    for(i = 0; i < N; i++)
        scanf("%d", &a[i]);

    for(i = 0; i <= j; i++)
    {
        if(a[i] % 2 != 0)
        {
            while(j > i)
            {
                j--;
                if(a[j] % 2 == 0)
                {
                    temp = a[i];
                    a[i] = a[j];
                    a[j] = temp;
                    break;
                }
            }
        }
    }

    printf("\nAfter re-arranging even and odd elements ...\n");
    for(i = 0; i < N; i++)
        printf("%d\n", a[i]);

    return 0;
}

Output:
Enter 10 integer numbers
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10

After re-arranging even and odd elements …
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1

Logic To Re-arrange Even and Odd Elements of An Array

First we accept N integer numbers from the user and store it inside a[N]. Using “for loop” we iterate through the array elements one by one.

Inside For Loop
We initialize i to 0, which is the first index of any array. We iterate through this “for loop” until i is less than or equal to j. j represents the number of elements already sorted from bottom(N – 1) of the array. i.e., from index j to (N – 1) all the elements are already odd numbers. For each iteration of the for loop we increment the value of i by 1.

First if condition – inside for loop
Aim of our C program is to move all the even elements to top and odd elements to the bottom. So if the “for loop” selected element, which is present in a[i] already has a even number then we let that number stay there itself, and increment the value of i by one. If the “for loop” selected number, which is present in a[i] has odd number, then we start searching for a even number from the bottom of the same array to swap it with a[i].

Inside While loop
Assume that a[i] has a odd number. Now lets initialize j to the size of array, which is N. “While loop” executes until j is greater than i. Here i represents the number of elements already sorted from the top. i.e., from index 0 to i all the elements are already even numbers.

This “while loop” executes until j is greater than i. The value of i is set by “for loop”. It’s the index of the element which is selected by the “for loop”, which has ODD number. i.e., if the control has entered “while loop” that means a[i] has ODD number. “While Loop” checks for EVEN element from the bottom of the array to swap it with the ODD number present at a[i].

Second if condition – inside while loop
As soon as control enters the while loop we reduce the value of j by 1. So now j is (N – 1), which is the last element of any array. Next, if the “while loop” selected element, which is present at a[j] has EVEN number, then we swap that number with the ODD number present in a[i], and break out of the while loop.

For each iteration of “while loop” we decrement the value of j by 1. And we do not reset the value of j for each iteration of “for loop”.

Printing re-arranged array elements
Once control exits “for loop” we print the array elements from 0 to N -1 and it’ll have all EVEN numbers at the top and ODD numbers at the bottom.

Explanation With Example

If int a[5] = {11, 10, 13, 12, 15};
ODD: a[i] % 2 != 0
EVEN: a[j] % 2 == 0

    j = N;
    for(i = 0; i <= j; i++)
    {
        if(a[i] % 2 != 0)
        {
            while(j > i)
            {
                j--;
                if(a[j] % 2 == 0)
                {
                    temp = a[i];
                    a[i] = a[j];
                    a[j] = temp;
                    break;
                }
            }
        }
    }
ia[i]ODDja[j]EVENSwap
011TRUE415FALSENO
011TRUE312TRUEYES
110FALSE213FALSENO

As you can see from above table swapping occurs at a[0] and a[3]. a[0] has integer number 11 and a[3] has integer number 12. So after swapping these numbers a[5] will be: {12, 10, 13, 11, 15}; So a[0], a[1] has EVEN numbers and a[2], a[3], a[4] has ODD numbers.

Important Note: i always represents the number of elements sorted from top(EVEN numbers), and j represents the index from (N – 1) which are sorted from bottom(ODD numbers).

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Sparse Index: MongoDB

All sparse indexes are unique index, but not all unique indexes are sparse! There are situations where we want to create unique index on key/field which is not present in all documents. Wherever the key is not present, it’s value will be treated as NULL. If more than 1 document has NULL value to the key we want to make as unique, then it violates unique key rule. In such situations we can make use of Sparse index and create unique key on only those documents which has the key in it.

sparse-index-unique-key-mongodb

example: database name
company: collection name

Insert documents

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MongoDB shell version: 2.6.1
connecting to: test
> use example
switched to db example
 
> db.company.insert({name: "Apple", product: "iPhone"});
WriteResult({ "nInserted" : 1 })
 
> db.company.insert({name: "Motorola", product: "Smart Watch"});
WriteResult({ "nInserted" : 1 })
 
> db.company.insert({name: "Technotip"});
WriteResult({ "nInserted" : 1 })
 
> db.company.insert({name: "Google"});
WriteResult({ "nInserted" : 1 })
 
 
> db.company.find().pretty()
{
        "_id" : ObjectId("53d9f5125d1942042b4e092b"),
        "name" : "Apple",
        "product" : "iPhone"
}
{
        "_id" : ObjectId("53d9f52d5d1942042b4e092c"),
        "name" : "Motorola",
        "product" : "Smart Watch"
}
{ "_id" : ObjectId("53d9f5385d1942042b4e092d"), "name" : "Technotip" }
{ "_id" : ObjectId("53d9f53f5d1942042b4e092e"), "name" : "Google" }

We have 4 documents in “company” collection. First 2 documents has “name” and “product” keys. Last 2 documents has only “name” key.

Sparse Index – Unique Key: MongoDB


[youtube https://www.youtube.com/watch?v=6pxI5j6TZRU]

YouTube Link: https://www.youtube.com/watch?v=6pxI5j6TZRU [Watch the Video In Full Screen.]



Duplicate key error

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> db.company.ensureIndex({product: 1}, {unique: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "ok" : 0,
        "errmsg" : "E11000 duplicate key error index: example.company.$product_1
  dup key: { : null }",
        "code" : 11000
}

Since last 2 documents do not have “product” key, its value will be treated as “NULL”. Since both these documents have value of “product” as “NULL”, trying to create unique key on “product” throws duplicate key error.

Sparse Index

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> db.company.ensureIndex({product: 1}, {unique: true, sparse: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

This creates a sparse index on “product” key/field.

system.indexes collection

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> db.system.indexes.find().pretty()
{
        "v" : 1,
        "key" : {
                "_id" : 1
        },
        "name" : "_id_",
        "ns" : "example.company"
}
{
        "v" : 1,
        "unique" : true,
        "key" : {
                "product" : 1
        },
        "name" : "product_1",
        "ns" : "example.company",
        "sparse" : true
}

The “system.indexes” collection shows that the key “product” is a unique key and is a sparse index.

sort() method

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> db.company.find().sort({product: 1}).pretty();
{ "_id" : ObjectId("53d9f5385d1942042b4e092d"), "name" : "Technotip" }
{ "_id" : ObjectId("53d9f53f5d1942042b4e092e"), "name" : "Google" }
{
        "_id" : ObjectId("53d9f52d5d1942042b4e092c"),
        "name" : "Motorola",
        "product" : "Smart Watch"
}
{
        "_id" : ObjectId("53d9f5125d1942042b4e092b"),
        "name" : "Apple",
        "product" : "iPhone"
}

This command sorts all the documents in lexicographical order. The output includes all the documents. Those documents which do not have “product” key in them are listed first.

Basic Cursor

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> db.company.find().sort({product: 1}).explain()
{
        "cursor" : "BasicCursor",
        "isMultiKey" : false,
        "n" : 4,
        "nscannedObjects" : 4,
        "nscanned" : 4,
        "nscannedObjectsAllPlans" : 4,
        "nscannedAllPlans" : 4,
        "scanAndOrder" : true,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

Since the command is even listing/sorting the documents which do not have “product” key in them, it’s simply making use of Basic Cursor – which do not help in optimizing the command/query performance.

hint() method

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> db.company.find().sort({product: 1}).hint({product: 1}).pretty();
{
        "_id" : ObjectId("53d9f52d5d1942042b4e092c"),
        "name" : "Motorola",
        "product" : "Smart Watch"
}
{
        "_id" : ObjectId("53d9f5125d1942042b4e092b"),
        "name" : "Apple",
        "product" : "iPhone"
}

hint() method tells the mongoDB server to operate only on the sparse key.. hence only retrieving and operating on the documents which has the sparse key in them.

Btree Cursor

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> db.company.find().sort({product: 1}).hint({product: 1}).explain()
{
        "cursor" : "BtreeCursor product_1",
        "isMultiKey" : false,
        "n" : 2,
        "nscannedObjects" : 2,
        "nscanned" : 2,
        "nscannedObjectsAllPlans" : 2,
        "nscannedAllPlans" : 2,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "indexBounds" : {
                "product" : [
                        [
                                {
                                        "$minElement" : 1
                                },
                                {
                                        "$maxElement" : 1
                                }
                        ]
                ]
        },
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

After using hint() method, mongoDB server is only looking for documents which has the sparse index key in them, so it can directly look for the sparse index key inside “system.indexes” collection, hence it’s using Btree Cursor – and is efficient.

Cursor Object: MongoDB

Lets have a deeper look into the MongoDB cursor object.

cursor-object-mongodb

Documents in our collection
test database, names collection.

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> use test
switched to db test
> show collections
names
system.indexes
> db.names.find();
{ "_id" : ObjectId("53be5d4604cc1cb0a7bfc3c0"), "name" : "Alia" }
{ "_id" : ObjectId("53be5d5204cc1cb0a7bfc3c1"), "name" : "Bebo" }
{ "_id" : ObjectId("53be5d5904cc1cb0a7bfc3c2"), "name" : "Chameli" }
{ "_id" : ObjectId("53be5d6104cc1cb0a7bfc3c3"), "name" : "Dev D" }
{ "_id" : ObjectId("53be5d6804cc1cb0a7bfc3c4"), "name" : "Emli" }
{ "_id" : ObjectId("53be5d8604cc1cb0a7bfc3c5"), "name" : "Farhan" }
{ "_id" : ObjectId("53be5d9204cc1cb0a7bfc3c6"), "name" : "Gangs" }
{ "_id" : ObjectId("53be5d9904cc1cb0a7bfc3c7"), "name" : "Hum" }
{ "_id" : ObjectId("53be5e3704cc1cb0a7bfc3c8"), "name" : 25 }

We have 8 documents with name in alphabetical order, and 1 document with name as 25. So in total we have 9 documents in our names collection.

Establishing Cursor

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> var cur = db.names.find();
 
> cur
{ "_id" : ObjectId("53be5d4604cc1cb0a7bfc3c0"), "name" : "Alia" }
{ "_id" : ObjectId("53be5d5204cc1cb0a7bfc3c1"), "name" : "Bebo" }
{ "_id" : ObjectId("53be5d5904cc1cb0a7bfc3c2"), "name" : "Chameli" }
{ "_id" : ObjectId("53be5d6104cc1cb0a7bfc3c3"), "name" : "Dev D" }
{ "_id" : ObjectId("53be5d6804cc1cb0a7bfc3c4"), "name" : "Emli" }
{ "_id" : ObjectId("53be5d8604cc1cb0a7bfc3c5"), "name" : "Farhan" }
{ "_id" : ObjectId("53be5d9204cc1cb0a7bfc3c6"), "name" : "Gangs" }
{ "_id" : ObjectId("53be5d9904cc1cb0a7bfc3c7"), "name" : "Hum" }
{ "_id" : ObjectId("53be5e3704cc1cb0a7bfc3c8"), "name" : 25 }

Look at the contents of our cursor object cur.

hasNext() and next() methods on Cursor

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> var cur = db.names.find();
> cur.hasNext();
true
> cur.next()
{ "_id" : ObjectId("53be5d4604cc1cb0a7bfc3c0"), "name" : "Alia" }
> cur.next()
{ "_id" : ObjectId("53be5d5204cc1cb0a7bfc3c1"), "name" : "Bebo" }
> cur.next()
{ "_id" : ObjectId("53be5d5904cc1cb0a7bfc3c2"), "name" : "Chameli" }

If there are any documents to iterate inside cursor object, then hasNext() will return true orelse it’ll return false. If hasNext() returns true, then we can iterate through the documents using next() method on the cursor object.

sort() method on Cursor Object

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> var cur = db.names.find();
 
> cur.sort({"name": -1});
{ "_id" : ObjectId("53be5d9904cc1cb0a7bfc3c7"), "name" : "Hum" }
{ "_id" : ObjectId("53be5d9204cc1cb0a7bfc3c6"), "name" : "Gangs" }
{ "_id" : ObjectId("53be5d8604cc1cb0a7bfc3c5"), "name" : "Farhan" }
{ "_id" : ObjectId("53be5d6804cc1cb0a7bfc3c4"), "name" : "Emli" }
{ "_id" : ObjectId("53be5d6104cc1cb0a7bfc3c3"), "name" : "Dev D" }
{ "_id" : ObjectId("53be5d5904cc1cb0a7bfc3c2"), "name" : "Chameli" }
{ "_id" : ObjectId("53be5d5204cc1cb0a7bfc3c1"), "name" : "Bebo" }
{ "_id" : ObjectId("53be5d4604cc1cb0a7bfc3c0"), "name" : "Alia" }
{ "_id" : ObjectId("53be5e3704cc1cb0a7bfc3c8"), "name" : 25 }

We could modify the cursor object using methods like sort(), limit() and skip(). In above example, we are modifying cursor object using sort() method, and we are sorting it in reverse lexicographical order on the name field.

limit() method on Cursor Object

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> var cur = db.names.find();
> cur.limit(3);
{ "_id" : ObjectId("53be5d4604cc1cb0a7bfc3c0"), "name" : "Alia" }
{ "_id" : ObjectId("53be5d5204cc1cb0a7bfc3c1"), "name" : "Bebo" }
{ "_id" : ObjectId("53be5d5904cc1cb0a7bfc3c2"), "name" : "Chameli" }

We could limit the output/result using limit() method.

Chaining method on Cursor Object

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> var cur = db.names.find();
 
> cur.sort({"name": -1}).limit(5).skip(2);
{ "_id" : ObjectId("53be5d8604cc1cb0a7bfc3c5"), "name" : "Farhan" }
{ "_id" : ObjectId("53be5d6804cc1cb0a7bfc3c4"), "name" : "Emli" }
{ "_id" : ObjectId("53be5d6104cc1cb0a7bfc3c3"), "name" : "Dev D" }
{ "_id" : ObjectId("53be5d5904cc1cb0a7bfc3c2"), "name" : "Chameli" }
{ "_id" : ObjectId("53be5d5204cc1cb0a7bfc3c1"), "name" : "Bebo" }

Here we chain the methods sort(), limit() and skip(). We are sorting in reverse lexicographical order on the name field, then skipping the first 2 documents and then limiting the result/output to 5 documents.

The order in which these 3 methods are applied are: First sort, then skip and then limit.
Also note that, these methods modify cursor object at the server side and not on client site.

Cursor Object: MongoDB


[youtube https://www.youtube.com/watch?v=_LexQW0vSlQ]

YouTube Link: https://www.youtube.com/watch?v=_LexQW0vSlQ [Watch the Video In Full Screen.]



explain() method on Cursor Object

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> db.names.find().explain();
{
        "cursor" : "BasicCursor",
        "isMultiKey" : false,
        "n" : 9,
        "nscannedObjects" : 9,
        "nscanned" : 9,
        "nscannedObjectsAllPlans" : 9,
        "nscannedAllPlans" : 9,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "server" : "PC:27017",
        "filterSet" : false
}

explain() method shows that find() returns a basic cursor. More on explain() method in coming videos.

Programmatic way of printing Cursor Object content

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> var cur = db.names.find();
 
> while(cur.hasNext()) printjson(cur.next());
{ "_id" : ObjectId("53be5d4604cc1cb0a7bfc3c0"), "name" : "Alia" }
{ "_id" : ObjectId("53be5d5204cc1cb0a7bfc3c1"), "name" : "Bebo" }
{ "_id" : ObjectId("53be5d5904cc1cb0a7bfc3c2"), "name" : "Chameli" }
{ "_id" : ObjectId("53be5d6104cc1cb0a7bfc3c3"), "name" : "Dev D" }
{ "_id" : ObjectId("53be5d6804cc1cb0a7bfc3c4"), "name" : "Emli" }
{ "_id" : ObjectId("53be5d8604cc1cb0a7bfc3c5"), "name" : "Farhan" }
{ "_id" : ObjectId("53be5d9204cc1cb0a7bfc3c6"), "name" : "Gangs" }
{ "_id" : ObjectId("53be5d9904cc1cb0a7bfc3c7"), "name" : "Hum" }
{ "_id" : ObjectId("53be5e3704cc1cb0a7bfc3c8"), "name" : 25 }

While loop executes until cur.hasNext() returns true. Until cur.hasNext() is true, cur.next() keeps printing next document in the cursor cur.