Recipes

Low-Fat Top Secret Recipes by Todd Wilbur

By Todd Wilbur

Dozens of tremendous new fat-conscious recipes are right here from the grasp of most sensible mystery kitchen concoctions.

Todd Wilbur, the irrepressible eating place recipe knockoff artist, is again. because of Wilbur's most up-to-date best mystery mission--to re-create a few of America's most well liked foodstuff items with out the fat--readers can now banquet guilt-free on their favourite snacks. The easy-to-follow recipes, besides Wilbur's patented blueprint illustrations, are bound to produce more healthy do-it-yourself treats that style just like the genuine thing--like Nabisco(r) Reduced-Fat Oreo(r) Cookies or Entenmann's Light(r) Low-Fat Cinnamon Rolls. Wilbur additionally tackles a few generic eating place delights, together with Bennigan's(r) Buffalo bird Sandwich, McDonald's(r) Arch Deluxe(r) and Egg McMuffin(r), and Wendy's(r) fowl Caesar clean crammed Pita(r)--concocting all of them at a fragment of the energy and at a fragment of the price. once more, the intrepid Todd Wilbur is going the place no nutrients author has long past before--and proves that once it involves delivering recipes for foodstuff that diners really need to consume, he's the peoples' choice.

Praise for Todd Wilbur
"The project: Decode the key recipes for America's favourite junk meals. apparatus: normal kitchen home equipment. objective: Leak the implications to a starving public." --USA Today

"There's whatever nearly magically compelling in regards to the thought of creating such meals at domestic . . . The attract is indisputable . . . full of tidbits and lore you're not going to discover at any place else." --Boston Herald

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Then, for each row in your stream, PDI binds the values of the row to the variables in the prepared statement. Let's see it by example. In the transformation you built a stream where each row had a single category and the value for the price. If you run the transformation with log level Detailed and look at the log, you will see the statement that is executed: DELETE FROM products WHERE price < ? AND id_category = ? The WHERE clause is built based on the conditions you entered in the Delete configuration window.

Drop to the canvas a Text file input step and use the step to read the books_news. txt file. As separator, type |. 00 as the Format. 3. Do a preview to verify you have read the file properly. You should see this: 4. Use a Split Fields step to split the name field into two: firstname and lastname. 5. Use a Database lookup step to look up in the authors table for an author that matches the firstname and lastname fields. As Values to return from the lookup table: add the id_author. 6. Check the option Do not pass the row if the lookup fails and close the window.

As the ID for the category tents is 4, the execution of the prepared statement with the values in this row has the same effect as the execution of the following SQL statement: DELETE FROM products WHERE price < 50 AND id_category = 4 See also f Looking for a value in a database table (Chapter 5, Looking for Data). Refer to this recipe if you need to understand how the Database lookup step works. 00 sec) How to do it... 1. Create a new transformation, and create a connection to the book's database.

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