Visiting British Columbia Day 4: Sailing to Bowen Island

Yer. There is a Bowen Island. Bowen says, "It is a giant island!". Believe it or not, go to check out by yourself. It is a pretty island. If Bowen wants to visit it again, I will do.

Be Cautious about the Storage used by Backup

The files on my PC is massive and unorganized. It takes some effort to manage it. To do some cleanup, I wrote a simple program to find all the duplicate files and tested it with the camera roll folder at One Drive/pictures. I thought it should be a dummy test. What surprised me is the following result:
total number of files: 33347, space occupied: 15.56GB
total number of duplicates: 613, space occupied: 1.62GB

About 20% of files are duplicates even under the backup for the camera roll! My camera could not take pictures that could be exactly same. I inspect both the album on my phone and the camera roll folder on One Drive. The duplicates don't exist at the album on my phone at all, but the camera roll backup on One Drive does show a lot of duplicates. It must be something wrong with One Drive's backup protocol or a bug in the code. These duplicates are only picture files. I don't have an enterprise account. People need to be careful about the backup for the enterprise storage too.

Due to curiosity, I run the program for gdrive photo folder too. Gdrive photo folder doesn't have the duplicates. But I could not open/read gdocs and gsheets at all from the PC. If one day, you don't have internet access, the local gdrive does nothing useful at all!

The duplicate picture files on Camera Roll have the similar names like:
one is DSC06220 1, the other is DSC06220_1.  I guess it is caused by the intermittent network connection for my case as those files are random. It doesn't happen to all the pictures taken at the same time or same day.

It has a reason to keep the files accidentally with the same names. Like one changes the SD card of the phone and start to take new pictures, the names will be reused again. However the things can be worse if someone just get out the SD card, plug it back again, then one ends up all the duplicate files on One Drive.  It should have done something smarter to inspect the contents or do a checksum to avoid to store exact same files/pictures.

If you are paying money for the backup storage, watch out for the space occupied by the duplicates. You can download my code to check duplicates on windows from github.

Revisiting Quicksort for Big Data

Quicksort is one of the most used subroutines in applications.While browsing its implementations online, one thing troubles me. As the following example from Rosettacode,  it has the neat implementation. But how about all the numbers are same! It doesn't do anything wrong, but it just runs your CPU all the time by doing useless things :P.

#include 
 
void quick_sort (int *a, int n) {
    int i, j, p, t;
    if (n < 2)
        return;
    p = a[n / 2];
    for (i = 0, j = n - 1;; i++, j--) {
        while (a[i] < p)
            i++;
        while (p < a[j])
            j--;
        if (i >= j)
            break;
        t = a[i];
        a[i] = a[j];
        a[j] = t;
    }
    quick_sort(a, i);
    quick_sort(a + i, n - i);
}

It is not hard to fix the problem by counting the number of the pivot value.  Just return when observing all the numbers are same.

While the data set is huge and the partitions are getting smaller with a few call of quick_sort, it has high probability that all the values in one small partition are the same. For some situations even worse, like sorting all the people in USA according to the age. If the input is an array of records in database systems, it is really costly by doing useless memory access/copies in nlog(n) scope!!!

Human's age are values from 1 to 100 something. If blindly using the quick_sort algorithms, it just eats the CPU and memory for no good. In many cases the keys to be sorted have just a few unique values like the age. In these cases, instead of using a nlog(n) quicksort algorithm,  a hybrid hash/count sort can do a much better job by one or a few scans. First extract the unique keys from the input, sort/hash them, do a final scan by counting or rearranging inputs. One can do optimization by just doing one scan depending the situations.

Visiting British Columbia Day 3: Getting on the Boat at Vancouver

After a long day on bus, ferry, water taxi, finally got on the boat.

Having fun on the ferry.


Vancouver harbor view from the water taxi.


Giant Cargo ship

Getting on the boat finally.

Visiting British Columbia Day 2: Exploring Victoria

We started off from the place we stayed and walked to Beacon Hill Park close by. 

At the south side of Beacon Hill Park, we continued to explore the trail along the cost called Dallas Road Waterfront trail. The vista points on the trail have stunning views. 

Starting from south point of Dallas Road Waterfront trail, we walked to the harbor and piers. Around harbor there are a lot of beautiful classic Victorian mansions.  

Tour De Victoria was happening on the day we were visiting. It looks a fun event. 

 Stroking around the downtown area.

At the late afternoon we had high tea at Empress hotel. It is worthwhile trying! The pier looks grand too at night. Don't miss it. 

Visiting British Columbia Day 1: Taking seaplane to Victoria

Flew from San Jose to Seattle.
Flew from Seattle to Victoria by Sea plane. It was a great experience.  Overlook of islands, mountains, harbor, and the ocean from the seaplane is grand.

We arrived Victoria at late afternoon. When we visited Butchart gardens, it was turning dark. I wish we had more day time to explore it as it is really pretty. The fireworks that only happens during summer season is great and beautiful too. Don't miss it if you come during summer and check out the time at the website.