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Today we are going to run SQL queries against a table containing ten THOUSAND records. {{ Maniacal laughter }} {{ Phone call }} What is it, Im in the middle of a video You dont say? ALL in RAM? Well, alrighty then Today we are going to run SQL queries against a table containing one .. Hundred .. MILLION records. {{ Maniacal laughter }} But dont worry. By using indexes, we can rapidly speed up queries so you do not have to experience the phenomenon known as boredom. We will work with a single table called person containing 100 MILLION randomly generated people. The first row is an auto-generated primary key called personid The other columns are firstname lastname and birthday. To create this table, we randomly generated names using the 1000 most popular female names, male names, and last names in the United States. We did not weight the names by frequency when generating our random sample. The datasets and the Python code used to generate the random names are available
