Its common knowledge to duck hunters that chest wading is dangerous but will they actually pull you under when they fill with water causing you to drown? In this video I fall into a marsh wearing my neoprene waders and put that myth to the test. Watch to the end for a few good laughs.
Connect with us on Social media!
Faceboook: The Quack Addicts
Gator-Tail Outboards: http://gator-tail.com/
• ShotKam: “QUACK50” https://shotkam.com/
• HTR Gun Stand: “Quack” is https://www.htrinnovations.com/
Nikon D7500 with 18-300mm Nikkor lens
Go Pro Hero 5 Black
Go Pro Hero 6 Black
2 ShotKam 2018 models
Adobe Premiere Pro CC 2018
Duck Hunting Gear:
Gator-Tail Savage Series Boat
Gator-Tail GTR 40 XD Surface Drive Motor
Benelli M2 12ga
Browning A-5 12ga
Drake Waterfowl lst eqwader 2.0
Mud River Lanyard Co Custom Lanyards
Rob Roberts T2 and T3 chokes
Hevi Metal 3 inch 3 shot
My go to call: Critter Done timber double reed
How's your duck season going? Hopefully its been better than ours has been thus far. We've been holding onto this video for hard times so we figured it'd be a good time to put it up. Hope you guys enjoy it!
However I feel like the drowning or getting sucked under would be more so if you were say fishing in a river and there was current added to the equation . However it's good to know that there is no real risk in the situation you just showed! . Which is great for me and my buddies who go out wheeling and get in some deep holes .
We actually have a new hunting video that's going up tomorrow! But yeah man its been the worst start to a season that we have seen in a long time here in KY. Hopefully January will be better, its usually the best part of the year for us.
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.