Thrifting With Marla (Vintage Clothing Store) 2018
hey guys! today's video is another video in my "thrift with me" series! i went to Vantage in SLC, Utah (https://www.instagram.com/vantageslc/) 10/10 recommend, if you're ever in town, or near by, be sure to check them out! let me know if you guys want a haul video on the items I bought!
Intro music - https://soundcloud.com/ashleyhelal/pines
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I'm from England(Leeds) and our charity shops(thrifts stores) are not as nearly as good as the ones in America. And the only vintage thrift store we have in Leeds is not as good as the one in America. If ur British like or reply to my comment
I live in Australia and I love your videos and your clothes. I like the HAWAIIAN shirt and I also like stripey shirts but I'm an XS or a S Depending on sizing in Australia but I love your channel so much!! Can you tell me where I can find good clothes in Australian stores??
Just look up 'op shops around me' and i TELL YOU there are so many! Im an aussie too, brissy, and i have ventured everywhere and there are sooooo many awesome places. I recommend salvos, lifeline, vinnies and the odd ones like foundation ones and little hole in the wall shops. If you seek, you will find.
This article has been motivated by a response I gave to a problem raised on an Oracle developer forum. Our requirement is to produce a report that details customer spending for each month of the year. Our database only records actual spend, so for any given month, data for dormant or idle customers will have to be generated.
First, well create a mock CUSTOMER_ORDERS table with sparse data to represent customer spending. To keep the example simple, well denormalise the customer name onto the orders table.
a sparse report.
With our customer orders data as sparse as it is, a monthly report for purchases by customer would look as follows.
adding the missing months.
We can see from the data that we are missing most months of the year for our two customers. Remember that our requirement is to show a report for every month in 2004 for every customer. First we will build a "time dimension" set (using subquery factoring) and outer join it to our orders table.
We can see that this hasnt quite worked. We have the zero sums and the year-months, but we are missing customer names. This is because we outer joined to CUSTOMER_ORDERS on the year-months, so any customer columns would show as NULL for deficient rows. Until PARTITION OUTER JOIN appeared in Oracle 10g, we couldnt "invent" data easily , though the next section shows that it is possible in prior versions.
data-densification without partition outer join.