I recently completed my presentation on Impostor Syndrome, I'm Just Here For The T-Shirt, at Adobe ColdFusion Summit 2024. Several people asked me for the link, so here it is: https://slides.com/codefumonkey/hfts-cfs24
Wise(ish) Words of a CodeFuMonkey
My place to run off at the mouth. Mostly about geek stuff. Sometimes.
Wednesday, October 2, 2024
My Presentation At ColdFusion Summit 2024
I recently completed my presentation on Impostor Syndrome, I'm Just Here For The T-Shirt, at Adobe ColdFusion Summit 2024. Several people asked me for the link, so here it is: https://slides.com/codefumonkey/hfts-cfs24
Saturday, January 13, 2024
Another Holiday Puzzle - Hanukkah of Data - Speed Run
Hanakkuh of Data
A database puzzle** WARNING: SPOILERS AHEAD **
** SPEEDRUN **
The SpeedRun wasn't a whole lot different than the original run through. There was a new, slightly more complex dataset, but the problems were almost exactly the same.
** PART 0 **
The code to unlock the files was the same as the previous set.
** PART 1 **
This one was also the same, but with the new data, it returned a different person to seed the rest of the problems with.
** PART 2 **
This one was also very similar, but the initials of the Contractor were different. There was also a slight change in the product SKUs that neded to be applied.
** PART 3 **
Since the person from the previous query changed, we had to change that value in the speedrun query. It also changed the birthdate of the Neighbor, so that required a couple of seconds of Google-fu to find dates for Libras in The Year of the Goat.
** PART 4 **
This one didn't require any changes. It pulled up different results, but otherwise was the same as the regular queries.
** PART 5 **
I had to run this one twice. This was the only one that I missed on the first try. I didn't catch that the Cat Lady was no longer in "Staten Island". My initial try gave me the wrong person, but when I removed that condition, I got the correct answer.
** PART 6 **
This one required no changes. I just returned a different person who was used in Part 7.
** PART 7 **
This one took me the longest of all of these. The data changes required me to make a few additions to the query. I changed the customer.id in the WHERE filters and added two new SKUs (HOM and TOY). There was an issue with my JOIN condition where I spit out the colors, but removing that condition gave me the right answer. Since color was such an important part of the original query, I'm guessing that this condition was probably intended, but I got lucky with my query. I'll take another look at this one, but for now, I've got the right answer.
** PART 8 **
The final question once again didn't require any changes.
The Speed Run was also pretty fun, but since the questions were essentially the same, not a lot of figuring was required for the queries. I don't know if that just means the data wasn't that much different or that I just wrote the queries originally that caught issues that were introduced in the speed run.
It took me 31 minutes to complete, and I only had one wrong answer in Part 5.
BACK TO PART 1
BACK TO PART 2
BACK TO PART 3
BACK TO PART 4
BACK TO PART 5
BACK TO PART 6
BACK TO PART 7
BACK TO PART 8
Thursday, January 4, 2024
Another Holiday Puzzle - Hanukkah of Data - Part 8
Hanakkuh of Data
A database puzzle** WARNING: SPOILERS AHEAD **
** DAY 8 - THE COLLECTOR **
"Oh that damned woman! She moved in, clogged my bathtub, left her coupons all over the kitchen, and then just vanished one night without leaving so much as a note.
Except she did leave behind that nasty carpet. I spent months cleaning one corner, only to discover a snake hiding in the branches! I knew then that she was never coming back, and I had to get it out of my sight.
"Well, I don't have any storage here, and it didn't seem right to sell it, so I gave it to my sister. She wound up getting a newer and more expensive carpet, so she gave it to an acquaintance of hers who collects all sorts of junk. Apparently he owns an entire set of Noah's collectibles! He probably still has the carpet, even.
"My sister is away for the holidays, but I can have her call you in a few weeks."
The family dinner is tonight! Can you find the collector's phone number in time?
This is the final day, and it seems way too easy. The only things that look like clues are the statement about the acquaintance who collects all sorts of junk and that he owns an "entire set of Noah's collectibles". This seems like I'm looking for someone who purchased a lot of the items that are labeled '
What we know:
- The Collector has an entire set of Noah's collectibles.
So first, I need to look at the products to verify which ones are Noah's Collectibles.
SELECT * FROM products WHERE descr LIKE 'Noah%' OR sku LIKE 'COL%'
This shows that I won't be able to use products.sku, because some of the items are listed under 'COL%' and some under 'TOY%'. All of the 'COL' items are Noah's Collectibles, but the 'TOY' items aren't. But it does look like I can grab all of the collectibles if I just use product.descr LIKE 'Noah%`. Of course, this is another assumption on my part. Are the 'TOY's also Collectibles, or is it just items listed with 'COL'?
SELECT c.customerid, c.name, c.phone
FROM customers c
INNER JOIN (
SELECT TOP 1 o.customerid, count(*) AS cnt
FROM orders o
INNER JOIN orders_items oi ON o.orderid = oi.orderid
INNER JOIN products p ON oi.sku = p.sku
AND p.descr LIKE 'Noah%'
GROUP BY o.customerid
ORDER BY cnt DESC
) s1 ON c.customerid = s1.customerid
Entering the phone number shows this is correct, too.
All days have been completed.
"Oh yes, that magnificent Persian carpet! An absolute masterpiece, with a variety of interesting animals congregating around a Tree of Life. As a collector, I couldn't believe when it fell into my lap.
"A friend of mine had taken it off her brother's hands, and she didn't know what to do with it. I saw her one day, and she was about to put an old rug out at the curb. It looked like it had been through a lot, but it was remarkably not that dirty. It still took quite a bit of effort and no small amount of rug cleaner, but ultimately, I managed to get the last bits of grime out of it.
"I actually live right down the street from Noah's Market - I'm a huge fan and I shop there all the time! I even have a one-of-a-kind scale model of Noah's Ark that makes a complete set of Noah's collectibles.
"I would love for Noah to have his rug once again to enjoy."
** CONCLUSION **
These were interesting puzzles. The querying part wasn't that difficult, but just figuring out what was being asked was extremely difficult for some of these. I'm not sure that this really tested my SQL skills as much as it tested my ability to determine what it was that the customer was actually asking for.
Overall, it was pretty fun. Now that we've completed the first batch, I think I'll try to see what the speed run is like.
BACK TO PART 1
BACK TO PART 2
BACK TO PART 3
BACK TO PART 4
BACK TO PART 5
BACK TO PART 6
BACK TO PART 7
BACK TO PART 8
Another Holiday Puzzle - Hanukkah of Data - Part 7
Hanakkuh of Data
A database puzzle** WARNING: SPOILERS AHEAD **
** DAY 7 - THE MEET CUTE **
"Oh that tapestry, with the colorful toucan on it! I'll tell you what happened to it.
"One day, I was at Noah's Market, and I was just about to leave when someone behind me said 'Miss! You dropped something!'
"Well I turned around to see this cute guy holding an item I had bought. He said, 'I got the same thing!' We laughed about it and wound up swapping items because I wanted the color he got. We had a moment when our eyes met and my heart stopped for a second. I asked him to get some food with me and we spent the rest of the day together.
"Before long I moved into his place, but the romance faded quickly, as he wasn't the prince I imagined. I left abruptly one night, forgetting the tapestry on his wall. But by then, it symbolized our love, and I wanted nothing more to do with it. For all I know, he still has it."
Can you figure out her ex-boyfriend's phone number?
This is another one where we'll need info from the previous query. We need to know the customerid of The Bargain Hunter, since the Ex-boyfriend bought the same item at the same time. But the item was a different color, so we'll also need to look at Products with a color description. I think that's all the actual clues in the text.
What we know:
- The Ex-boyfriend bought an item at Noah's Market the same day as The Bargain Hunter.
- The Bargain Hunter's customerid is 4167
- Colored items are designated in product.sku as 'COL%'
So first, let's find the orders that were placed on the same day as The Bargain Hunter.
SELECT o1.customerid, o1.orderid, o2.customerid, o2.orderid
FROM orders o1
INNER JOIN orders o2 ON o1.customerid <> o2.customerid
AND YEAR(o1.ordered) = YEAR(o2.ordered)
AND MONTH(o1.ordered) = MONTH(o2.ordered)
AND DAY(o1.ordered) = DAY(o2.ordered)
WHERE o1.customerid = 4167
This gives us over 3000 orders. This also shows that we probably need to simplify date searching a little bit. orders.ordered is a datetime datatype. We want to truncate that date to just `YYYY-MM-DD`, and we can do this by simply using CAST(orders.ordered AS date). That will trim off the time part. That way we aren't pulling out each part. We can go back to that if we need to later.
We also need to narrow these orders down to just those items with a color listed. Looking at the data shows us that it's part of products.descr.
/* Get Sherri's orders */
SELECT o.ordered, oi.sku, p.descr, CAST(o.ordered AS date) AS truncDate
FROM orders o
INNER JOIN orders_items oi ON o.orderid = oi.orderid
INNER JOIN products p ON oi.sku = p.sku
AND p.sku LIKE 'COL%'
WHERE o.customerid = 4167
This drops it down to just 4 orders. That should be easy to work with. Now we just need to find other orders placed on that date.
/* Find Orders from same time as Sherri's */
; WITH sherriOrders AS (
SELECT o.ordered, oi.sku, p.descr, CAST(o.ordered AS date) AS truncDate
FROM orders o
INNER JOIN orders_items oi ON o.orderid = oi.orderid
INNER JOIN products p ON oi.sku = p.sku
AND p.sku LIKE 'COL%'
WHERE o.customerid = 4167
)
SELECT c.customerid, c.name, c.phone, o.*, so.*, ABS(DATEDIFF(hour,o.ordered,so.ordered)) AS diffHrs
FROM orders o
INNER JOIN orders_items oi ON o.orderid = oi.orderid
INNER JOIN products p ON oi.sku = p.sku
--AND p.sku LIKE 'COL%'
INNER JOIN sherriOrders so ON oi.sku = so.sku
AND CAST(o.ordered AS date) = so.truncDate
AND o.ordered <= so.ordered
--AND DATEDIFF(hour,o.ordered,so.ordered) < 1 /* Orders less than 1 hour apart. */
INNER JOIN customers c ON o.customerid = c.customerid
WHERE o.customerid <> 4167 /* Exclude Sherri */
/* NO RESULTS */
That's not good. That shouldn't have eliminated everything. There should be other orders that happened at the same time.
After digging at the data, I realized that I was eliminating the data that I actually needed. I was comparing Product SKUs from both orders, but the text says that these items were different colors. They'll have different SKUs, so I need to compare the item name without the colors.
/* Find Orders from same time as Sherri's */
; WITH sherriOrders AS (
SELECT o.ordered, oi.sku, p.descr
, SUBSTRING(p.descr,1,CHARINDEX('(',p.descr)-2) AS prodName
, CAST(o.ordered AS date) AS truncDate
FROM orders o
INNER JOIN orders_items oi ON o.orderid = oi.orderid
INNER JOIN products p ON oi.sku = p.sku
AND p.sku LIKE 'COL%'
WHERE o.customerid = 4167 /* Sherri */
)
SELECT c.customerid, c.name, c.phone --, o.*, oi.*,p.*, so.*
FROM orders o
INNER JOIN customers c ON o.customerid = c.customerid
INNER JOIN orders_items oi ON o.orderid = oi.orderid
INNER JOIN products p ON oi.sku = p.sku
AND p.sku LIKE 'COL%'
INNER JOIN sherriOrders so ON
SUBSTRING(p.descr,1, CASE WHEN CHARINDEX('(',p.descr) IS NULL THEN LEN(p.descr) ELSE CHARINDEX('(',p.descr)-2 END ) = so.prodName /* THIS IS AN INSANE SPLITTING */
AND CAST(o.ordered AS date) = so.truncDate
AND ABS(DATEDIFF( minute, o.ordered,so.ordered )) < 1 /* USE ABS TO ELIMINATE NEGATIVES */
WHERE o.customerid <> 4167
/*
customerid name phone
5783 Carlos Myers 838-335-7157
*/
That one gets us down to just one result. Entering that phone number gives us another right answer.
GO TO DAY 8
BACK TO PART 1
BACK TO PART 2
BACK TO PART 3
BACK TO PART 4
BACK TO PART 5
BACK TO PART 6
Another Holiday Puzzle - Hanukkah of Data - Part 6
Hanakkuh of Data
A database puzzle** WARNING: SPOILERS AHEAD **
** DAY 6 - THE BARGAIN HUNTER **
"Why yes, I did have that rug for a little while in my living room! My cats can't see a thing but they sure chased after the squirrel on it like it was dancing in front of their noses.
"It was a nice rug and they were surely going to ruin it, so I gave it to my cousin, who was moving into a new place that had wood floors.
"She refused to buy a new rug for herself - she said they were way too expensive. She's always been very frugal, and she clips every coupon and shops every sale at Noah's Market. In fact I like to tease her that Noah actually loses money whenever she comes in the store.
"I think she's been taking it too far lately though. Once the subway fare increased, she stopped coming to visit me. And she's really slow to respond to my texts. I hope she remembers to invite me to the family reunion next year."
Can you find her cousin's phone number?
Hmmm.... seems like there's some misdirection language in here. The Cat Lady talks about her cousin with wood floors. That's not really tracked in our data, so that can't really be a clue. The only thing she really says though is that her cousin is very cheap and shops only sales at Noah's Market. I think this one took sparse clues to a whole new level.
What we know:
- Cousin is very cheap.
- Cousin shops every sale at Noah's Market. She mentions Noah loses money when she comes in, but is that a clue?
These "clues" are getting very vague. They require a significant amount of interpretation of what the text even says. I'm not even sure exactly what clues this one is giving me.
The only clue I really see is that this Cousin shops all sales at Noah's. There doesn't seem to be any direct indicator of what a sale is, but there is a product.wholesale_cost column and an orders_items.unit_price columns. Hopefully, if I compare these numbers and something will pop out.
/* Look for sales orders that were less than normal Product price. */
SELECT *
FROM orders_items oi
INNER JOIN products p ON oi.sku = p.sku
WHERE oi.unit_price < p.wholesale_cost
Good. I got back over 2000 rows, so this should be a way I can figure out what was on sale.
/* Who made those Orders */
; WITH salesOrders AS (
SELECT TOP 1 o.customerid, count(*) AS cnt
FROM orders_items oi
INNER JOIN products p ON oi.sku = p.sku
INNER JOIN orders o ON oi.orderid = o.orderid
WHERE oi.unit_price < p.wholesale_cost
GROUP BY o.customerid
ORDER BY cnt DESC
)
SELECT c.customerid, c.name, c.phone
FROM customers c
INNER JOIN salesOrders so ON c.customerid = so.customerid
/*
customerid name phone
4167 Sherri Long 585-838-9161
*/
After GROUPing, JOINing and ORDERing those records to find who had the most orders on sale, I came back with only one record. Entering her phone number shows her as the correct answer again.
This one was mind-bogglingly difficult just to get what the clue was. It required a little bit of looking at the words in the problem and then checking the data to realize there were differences in pricing between sale and wholesale. These clues make you think about more than just data.
GO TO DAY 7
BACK TO PART 1
BACK TO PART 2
BACK TO PART 3
BACK TO PART 4
BACK TO PART 5
Another Holiday Puzzle - Hanukkah of Data - Part 5
Hanakkuh of Data
A database puzzle** WARNING: SPOILERS AHEAD **
** DAY 5 - THE CAT LADY **
"Yes, I did have that tapestry for a little bit. I even cleaned a blotchy section that turned out to be a friendly koala.
"But it was still really dirty, so when I was going through a Marie Kondo phase, I decided it wasn't sparking joy anymore.
"I listed it on Freecycle, and a woman in Staten Island came to pick it up. She was wearing a "Noah's Market" sweatshirt, and it was just covered in cat hair. When I suggested that a clowder of cats might ruin such a fine tapestry, she looked at me funny. She said "I only have ten or eleven cats, and anyway they are getting quite old now, so I doubt they'd care about some old rug."
"It took her 20 minutes to stuff the tapestry into some plastic bags she brought because it was raining. I spent the evening cleaning my apartment."
What's the phone number of the woman from Freecycle?
Each of these puzzles did a good job of tying these people back to Noah's Market. Little clues like a "Noah's Market sweatshirt" were good.
This one seems extremely sparse on clues.
What we know:
- This woman lives in Staten Island
- She has a lot of older cats - 10-11
First, let's look for people from Staten Island.
SELECT *
FROM customers c
WHERE city = 'Staten Island'
This comes back with over 300 rows.
To narrow this down, it's probably a fair assumption that she buys cat supplies from Noah's Market. But querying shows there are over 700 cat products. She also has older cats, and if it was mentioned in the text, it's probably a clue. Looking at the data, we need to look for items for "Senior Cats. That brings us down to 257 products. Let's build a query to see if we can identify somebody from "Staten Island" with a lot of orders for "senior cat" products.
SELECT c.customerid, c.name, c.phone, count(o.orderid) AS cnt
FROM customers c
INNER JOIN orders o ON c.customerid = o.customerid
INNER JOIN (
SELECT oi.orderid
FROM orders_items oi
INNER JOIN products p ON oi.sku = p.sku
AND p.descr LIKE '%cat%'
AND p.descr LIKE '%senior%'
) s1 ON o.orderid = s1.orderid
WHERE c.city = 'Staten Island'
GROUP BY c.customerid, c.name, c.phone
ORDER BY cnt DESC
This gives us 76 rows, but there is an outlier. Entering her phone number shows she's the right answer. We found the Cat Lady.
GO TO DAY 6
BACK TO PART 1
BACK TO PART 2
BACK TO PART 3
BACK TO PART 4
Another Holiday Puzzle - Hanukkah of Data - Part 4
Hanakkuh of Data
A database puzzle** WARNING: SPOILERS AHEAD **
** DAY 4 - THE EARLY BIRD **
The investigator called the phone number you found and left a message, and a man soon called back:
"Wow, that was years ago! It was quite an elegant tapestry.
"It took a lot of patience, but I did manage to get the dirt out of one section, which uncovered a superb owl. I put it up on my wall, and sometimes at night I swear I could hear the owl hooting.
"A few weeks later my bike chain broke on the way home, and I needed to get it fixed before work the next day. Thankfully, this woman I met on Tinder came over at 5am with her bike chain repair kit and some pastries from Noah's. Apparently she liked to get up before dawn and claim the first pastries that came out of the oven.
"I didn't have any money or I would've paid her for her trouble. She really liked the tapestry, though, so I wound up giving it to her.
"I don't remember her name or anything else about her."
Can you find the bicycle fixer's phone number?
This seems to be very light on the clues.
What we know:
- This is a woman who likes to get the first pastries from Noah's.
- She brought her Bike Chain Repair Kit over at 5am.
This one will be tough. Let's see what we've got.
/* Find chain repair kit */
SELECT *
FROM products p
WHERE descr LIKE '%chain%'
/* No results found, so look for first orders of the day. */
Well that was a dead end. It looks like the Bike Chain Repair Kit was a big red herring. All Bakery orders have a product.sku that starts with "BKY". I'll also check only orders before 5am.
Let's find the first orders of the day.
; WITH firstOrders AS (
SELECT s1.orderid, ordered, customerid
FROM (
SELECT orderid, ordered, customerid
, ROW_NUMBER() OVER ( PARTITION BY YEAR(ordered), MONTH(ordered), DAY(ordered) ORDER BY ordered ) AS rn
FROM orders o
WHERE DATEPART(hour,o.ordered) <=5
) s1
WHERE s1.rn = 1
)
, ordersFromBakery AS (
SELECT fo.orderid, fo.customerid
FROM orders_items oi
INNER JOIN firstOrders fo ON oi.orderid = fo.orderid
WHERE oi.sku LIKE 'BKY%'
)
SELECT c.name, count(*) AS cnt
FROM customers c
INNER JOIN ordersFromBakery ofb ON c.customerid = ofb.customerid
GROUP BY c.name
That came back with 59 rows with no standouts. Let's simplify this query.
SELECT TOP 1 c.name, c.phone, COUNT(oi.sku) AS cnt
FROM customers c
INNER JOIN orders o ON c.customerid = o.customerid
INNER JOIN orders_items oi ON o.orderid = oi.orderid
WHERE oi.sku LIKE 'BKY%'
AND DATEPART(hour,o.ordered) < 5
GROUP BY c.name, c.phone
ORDER BY cnt DESC
/*
name phone cnt
Renee Harmon 607-231-3605 5
*/
That one came back with 177 rows, but sorting by the count leaves only 1 outlier. She wasn't a very big outlier.
Checking her phone number shows that she is the right one. I'll want to look at this one again to see if I missed something.
GO TO DAY 5
BACK TO PART 1
BACK TO PART 2
BACK TO PART 3