Searching in a sorted and rotated array

This can be done in O(logN) using a slightly modified binary search.

The interesting property of a sorted + rotated array is that when you divide it into two halves, atleast one of the two halves will always be sorted.

Let input array arr = [4,5,6,7,8,9,1,2,3]
number of elements  = 9
mid index = (0+8)/2 = 4

[4,5,6,7,8,9,1,2,3]
         ^
 left   mid  right

as seem right sub-array is not sorted while left sub-array is sorted.

If mid happens to be the point of rotation them both left and right sub-arrays will be sorted.

[6,7,8,9,1,2,3,4,5]
         ^

But in any case one half(sub-array) must be sorted.

We can easily know which half is sorted by comparing start and end element of each half.

Once we find which half is sorted we can see if the key is present in that half - simple comparison with the extremes.

If the key is present in that half we recursively call the function on that half
else we recursively call our search on the other half.

We are discarding one half of the array in each call which makes this algorithm O(logN).

Pseudo code:

function search( arr[], key, low, high)

        mid = (low + high) / 2

        // key not present
        if(low > high)
                return -1

        // key found
        if(arr[mid] == key)
                return mid

        // if left half is sorted.
        if(arr[low] <= arr[mid])

                // if key is present in left half.
                if (arr[low] <= key && arr[mid] >= key) 
                        return search(arr,key,low,mid-1)

                // if key is not present in left half..search right half.
                else                 
                        return search(arr,key,mid+1,high)
                end-if

        // if right half is sorted. 
        else    
                // if key is present in right half.
                if(arr[mid] <= key && arr[high] >= key) 
                        return search(arr,key,mid+1,high)

                // if key is not present in right half..search in left half.
                else
                        return search(arr,key,low,mid-1)
                end-if
        end-if  

end-function

The key here is that one sub-array will always be sorted, using which we can discard one half of the array.

The accepted answer has a bug when there are duplicate elements in the array. For example, arr = {2,3,2,2,2} and 3 is what we are looking for. Then the program in the accepted answer will return -1 instead of 1.

This interview question is discussed in detail in the book 'Cracking the Coding Interview'. The condition of duplicate elements is specially discussed in that book. Since the op said in a comment that array elements can be anything, I am giving my solution as pseudo code in below:

function search( arr[], key, low, high)

    if(low > high)
        return -1
    
    mid = (low + high) / 2
    
    if(arr[mid] == key)
        return mid

    // if the left half is sorted.
    if(arr[low] < arr[mid]) {

        // if key is in the left half
        if (arr[low] <= key && key <= arr[mid]) 
            // search the left half
            return search(arr,key,low,mid-1)
        else
            // search the right half                 
            return search(arr,key,mid+1,high)
        end-if

    // if the right half is sorted. 
    else if(arr[mid] < arr[high])    
        // if the key is in the right half.
        if(arr[mid] <= key && arr[high] >= key) 
            return search(arr,key,mid+1,high)
        else
            return search(arr,key,low,mid-1)
        end-if
   
    else if(arr[mid] == arr[low])
       
        if(arr[mid] != arr[high])
            // Then elements in left half must be identical. 
            // Because if not, then it's impossible to have either arr[mid] < arr[high] or arr[mid] > arr[high]
            // Then we only need to search the right half.
            return search(arr, mid+1, high, key)
        else 
            // arr[low] = arr[mid] = arr[high], we have to search both halves.
            result = search(arr, low, mid-1, key)
            if(result == -1)
                return search(arr, mid+1, high, key)
            else
                return result
   end-if
end-function

You can do 2 binary searches: first to find the index i such that arr[i] > arr[i+1].

Apparently, (arr\[1], arr[2], ..., arr[i]) and (arr[i+1], arr[i+2], ..., arr[n]) are both sorted arrays.

Then if arr[1] <= x <= arr[i], you do binary search at the first array, else at the second.

The complexity O(logN)

EDIT: the code.