You have just moved into a new residential society with 5 huge towers. Each tower has 50 floors and each floor has 2 apartments. That is a total of 500 families. You want to host a new year bash at your home and want to invite your neighbors spread across all the towers. But you are not sure what kind of cuisine they may prefer. You decide to go to each tower and randomly ask around their preferences. Each tower has 100 families/homes, so with your randomness, you land up talking to 30 families in each tower. Of course, talking to all the 500 families would have been a lot of work. Well, you did a great job in surveying 150 families. And now you have some data – people love all sorts of cuisines but what stands out is the Indian food 😉 followed by Italian and then Mexican. OK, you have some idea what to do. And you start your party preparations. On the day when all your neighbors are coming in, you are extremely pleased to see that the survey worked out so well and the food choices were just right. Lucky you. SQL Server does the same. When you want the data out of a table with a predicate (WHERE clause), it estimates the number of records that may be returned and generates a “possibly good” execution plan. This estimation is based on statistics the optimizer generated by surveying the column data on which you have the predicate. Exactly like you surveyed the families. Sounds interesting? Watch the video below.

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