CISC 7510X (DB1) Homeworks

You should EMAIL me homeworks, alex at theparticle dot com. Start email subject with "CISC 7510X HW#". Homeworks without the subject line risk being deleted and not counted.

CISC 7510 HW# 1 (due by 3rd class;): For the below `store' schema:
product(productid,description,listprice)
customer(customerid,username,fname,lname,street1,street2,city,state,zip)
purchase(purchaseid,purchasetimestamp,customerid)
purchase_items(itemid,purchaseid,productid,quantity,price)

Using SQL, answer these questions (write a SQL query that answers these questions):

1. What is the description of productid=42?
2. What's the name and address of customerid=42?
3. What products did customerid=42 purchase?
4. List customers who bought productid=24?
5. List customer names who have never puchased anything.
6. List product descriptions who have never been purchased by anyone.
7. What products were purchased by customers with zip code 10001?
8. What percentage of customers have ever purchased productid=42?
9. Of customers who purchased productid=42, what percentage also purchased productid=24?
10. What is the most popular (purchased most often) product in NY state?
11. What is the most popular (purchased most often) product in Tri-state Area? (NJ, NY, CT)
12. Who purchased productid=24 prior to July 4th, 2020?
13. For each customer, find all products from their last purchase.
14. For each customer, find all products from their last 10 purchases.
15. Names of customers who have purchased product 42 in the last 3 months.

Also, install PostgreSQL.

CISC 7510 HW# 2 (due by 4th class;): Install PostgreSQL
As a `simple' review of SQL, do `Sample Questions' at the end of: sql2.pdf; For the same database, also answer the following questions:

1. Find the company with most employees.
2. Find employees who make more than the average salary within their company.
3. Find employees who make more than the median salary within their company.
4. Find employees whose salary is an outlier (above 2 standard deviations) within their comapny.
5. Find employees whose salary is an outlier (above 95th percentile) within their comapny.
6. Find the company with the highest number of outlying salaries (your choice which outlier to use).
7. Find the company with most non-managing employees.
8. Find the company with highest average difference between manager salary and non-manager employee salary.
9. Assume that each non-managing employee genererates around 2x their salary in revenue. Managing employees don't directly contribute to revenue. Estimate revenue and ``profit'' for each company (assume profit = revenue - all_salaries).
10. Calculate salary skew for profitable (profit > 0) companies from question 9.

Email the query text.

CISC 7510X HW# 3 (due by Nth class;): Write a command line program to "join" .csv files. Use any programming language you're comfortable with (Python suggested). Your program should work similarly to the unix "join" utility (google for it). Unlike the unix join, your program will not require files to be sorted on the key. Your program must also accept the "type" of join to use---merge join, inner loop join, or hash join, etc. Assume that first column is the join key---or you can accept the column number as paramater (like unix join command).

Do not use libraries with join-capabilities (e.g. Pandas, Dataset, or pass your files to unix "join" command, etc. that defeats the purpose of this homework.). Use lists, hashes, your own data-structures, etc., not a library that's essentially a mini-database. Test your program on "large" files (e.g. make sure it wouldn't blow up on one-million-records [e.g. do not store everything in memory], etc.)

Submit source code for the program.

Also... load all files in ctsdata.20140211.tar (link on the left) into Oracle or Postgres (or whichever works for you). The format of these files is: cts(tdate,symbol,open,high,low,close,volume), splits(tdate,symbol,post,pre), dividend(tdate,symbol,dividend). Submit (email) whatever commands/files you used to load the data into whatever database you're using, as well as the raw space usage of the tables in your database.

CISC 7510X HW# 4 (due by Nth class): If you haven't done so already, load all files in ctsdata.20140211.tar (link on the left) into Oracle or PostgreSQL (or whichever works for you; postgresql recommended!). The format of these files is: cts(date,symbol,open,high,low,close,volume), splits(date,symbol,post,pre), dividend(date,symbol,dividend). Submit (email) whatever commands/files you used to load the data into whatever database you're using, as well as the raw space usage of the tables in your database. (this was part of previous homework).

After loading the data, using a create-table-as SQL statement, create another table DAILY_PRCNT, with fields: TDATE,SYMBOL,PRCNT which will have the daily percentage gain/loss adjusted for dividends and splits.

Do NOT write procedural code (Java, C#, C/C++, etc.) for this homework (all code must be SQL, etc.).

HINT: MSFT (Microsoft) on 2004-11-12 closed at 29.97.
They issued a dividend of 3.08, with ex-dividend date of 2004-11-15. Meaning anyone who buys the stock on-or-after 2004-11-15 is NOT entitled to the dividned.
On 2004-11-12 it was $29.97 equity, by morning 2004-11-15 it turned into (26.89 equity + 3.08 cash). When markets closed on 2004-11-15 at 27.39, the gain was from 26.89 to 27.39.
(preclose - dividend) * (1+r) = close
(29.97 - 3.08)*(1+r) = 27.39
r = (27.39/(29.97 - 3.08))-1 = 0.018594
or 1.8594% daily gain.
Can test: (29.97 - 3.08) * (1+0.018594) = 27.390, which matches closing price on 2004-11-15.

HINT: splits, MSFT did a 1 to 2 split on 2003-02-18. During a split, each share of a company gets turned into several shares of lower value each. The total value held by investors is not changed.
Closing price on 2003-02-14 is 48.30
Closing price on 2003-02-18 is 24.96
On 2003-02-14 it was 48.30 stock, by morning 2003-02-18 it turned into 2 * 24.150 equity (total value still 48.30).
(prevclose * pre/post) * (1+r) = close
(48.30 * 1/2) * (1+r) = 24.96
The gain/loss is caluclated from 24.15 (value after split) to 24.96 (closing price on 2003-02-18).
r = (24.96 / (48.30 * 1/2))-1 = 0.033540
or 3.3540% daily gain.
Can test: (48.30 * 1/2) * (1+ 0.033540) = 24.96
Loss is just a negative percentage.

Submit query used to construct the DAILY_PRCNT table (e.g. "create table DAILY_PRCNT as select ..."). We'll do more stuff with this DAILY_PRCNT dataset in subsequent homeworks---so don't put it off and get it done on time.

CISC 7510X HW# 5: Your buddy stops over for lunch and tells you about their wonderful idea of building software for junk yards. Junk yards are places that aquire cheap old cars and sell individual parts---a $1k old junky car may have 100 parts in it that each can be sold for $20-$50, etc. A typical junk yard may have dozens to hundreds of old cars, and if you need a part, you drive by and ask... the attendant would know what car/part you're looking for and would know whether they have anything compatible in the inventory. (e.g. a "left side mirror from a white 2013 Ford Mustang" may be repainted to be compatible with a red 2014 Ford Mustang, etc.).

Now, the attendant would likely know these things (they have enormous domain knowledge). But it's still a major inventory hassle to find compatible parts... Your buddy has an idea of building such an `inventory management system' for junk yards... so anyone can start a junk yard, and junk yards can get much bigger. Maybe even hookup with ebay/amazon for used-parts! (You can't sell used car parts on ebay unless you know what parts you have!).

The idea is that the customer would drive in, type in the car/part they're looking for, and the system would tell them if there's a compatible car/part available (and where it is), or can be made compatible with minor tweaks (such as repainting, etc.). If part is not available locally, the software should be internet enabled to find the compatible parts in other junk yards running the same software. Your buddy estimates license per junk yard, $20k, with $2k/year maintenance, and your buddy thinks he can immediately sell it to at least 10 junk yards near major city centers, and perhaps a few hundred over the next few years. So now you have a case for a lucrative business... your task is to build it.

Go through the process of designing this inventory system. What are objects? What are events? Create a database schema, etc. How would the search process work? (e.g. go through the motions of: new junky car arrives, how is it inventoried? new customer arrives looking for a part, how does the system find a compatible part? where can humans be eliminated from this process?).

Sprinkle AI over the use case: the customer will ask the system in English what they want, and the system will answer (and reason about compatibility / repainting / adjustments, etc.). How would that work? (e.g. the AI bot needs access to the database---what would they query on---and how would they know about compatibility of parts? this has to come from your database.).

Submit writeup of the design (nothing too complicated, just a 1 page description---something that would convince me that you're the right contractor for this project---that you know what you're doing). While you can use chatgpt for this, it is almost certain that chatgpt will take your job if you do---the easiest jobs to eliminate are those that chatgpt can already do easily! Submit database schema (DDL, create table statements), and query statements/process to find a compatible part.