project related to how the live count works.
Budget: $30 – $250 USD
Let us think about an example of updating two different types of databases. The first example involves an online ticket purchase at Ticketmaster. In this case, each ticket is unique. One person, one seat. Ticketmaster is not just one computer, but many. These computers must work together and not sell the same ticket twice. When you wish to purchase a concert ticket, you first use your mobile device or use your browser to access the Ticketmaster website. At the website, you determine which seat location you can afford. You decide on the seat and go through the process of typing in your payment information. At this point, the seats you wish to purchase will be locked in the Ticketmaster database for a short time until you finish your transaction. If you do not finish in time, the lock will be released for another person to purchase the seat. No one else can buy those seats until the time expires or the seats are purchased.
On to the second example. What is the difference between reserving a specific seat at a concert and calculating the number of likes on YouTube? We are not reserving one specific seat but incrementing a counter. Each "like" on YouTube is just as valuable as another. We are not purchasing anything unique. It is more like voting for a candidate. With huge website such as Twitter and YouTube, there are many computers. Thus, when we see a video with the number of likes at the bottom of the app, we see the sum of several likes from different computers. Thus, the problem, the networked computers must communicate with some other server that is keeping track of the total number of likes.
On to the second example. What is the difference between reserving a specific seat at a concert and calculating the number of likes on YouTube? We are not reserving one specific seat but incrementing a counter. Each "like" on YouTube is just as valuable as another. We are not purchasing anything unique. It is more like voting for a candidate. With huge website such as Twitter and YouTube, there are many computers. Thus, when we see a video with the number of likes at the bottom of the app, we see the sum of several likes from different computers. Thus, the problem, the networked computers must communicate with some other server that is keeping track of the total number of likes.