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December 6th, 2022    

CISC 7510X
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Sample Data
ctsdata.20140211.tar
Stock Ordrs


SQLRunner

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 7510X HW# 1 (due by 2nd class;): Email me your name, prefered email address, IM account (if any), major, and year. (oh, and install PostgreSQL).


CISC 7510X HW# 2 (due by 3rd class;): For the below `store' schema:
product(productid,description,)
customer(customerid,username,fname,lname,street1,street2,city,state,zip)
purchase(purchaseid,purchasetimestamp,customerid,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?

Also, install PostgreSQL.


CISC 7510X HW# 3 (due by 4th class;): Install PostgreSQL.
For the below schema for a company door:
doorlog(eventid,doorid,tim,username,event)

Where doorid represents the door for this event. e.g. Front door may be doorid=1, and bathroom may be doorid=2, etc. tim is timestamp, username is the user who is opening or closing the door. event is "E" for entry, and "X" for exit.

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

  1. How many users entered through doorid=1
  2. If doorid=2 is bathroom, how many people are currently in the bathroom?
  3. If doorid=1 is front entrance door, and doorid=3 is back entrance door, and these are the only doors in the building, how many people are currently in the building?
  4. How many people were in the building on July 4th, at 10PM? (watching fireworks)
  5. If doorid=7 is for floor 42, what's the daily occupancy of floor 42 for entire 2021 (give a number for every day in 2021; not just days that had activity; if nobody entered/left floor, then return 0 for that day)
  6. What is the daily average (and standard deveation) occupancy of floor 42 for 2021? (single number; use above question results)
  7. What percentage of the people work on floor 42 (assume if they entered the floor, they work there).
  8. What's the average number of times per day that people use the bathroom? (bathroom is doorid=2).
  9. What percentage of employees stayed after 5:15PM on July 3rd, 2022?
  10. List all employees who left work before 1PM on July 3rd, 2022 (assume they arrived to work on July 3rd, before 1pm).

CISC 7510X HW# 4 (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# 5 (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 dain/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# 6 (due by Nth class;): Doing something useful with the data from HW5: Background: Pairs trading. Using the percentage returns table you built in HW5: Your task is to identify potential symbol pairs that have HIGH correlation, and are suitable for pairs trading. While everyone agrees that this strategy works, nobody agrees on the best way to identify correlation---especially when considered in relation to the rest of the market.

For this homework, feel free to use whatever you think is appropriate for correlation (if not sure, try Pearson; Take a log of the percentage gain, and apply pearson on top of that. Yes, you can do all this in SQL.).

Submit 10 "best" symbol pairs, each of which trades at least ~$10m a day, suitable for pairs trading in December 2013 (yah, I know it's an old date). Along with the pairs, submit their correlation coefficients for previous year, and the month of December 2013. (assume you were trading $1m worth, and you traded those exact 10 pairs, how much would you have gained/lost during that period?). Also submit the sql code to get those 10 symbols from the dataset.


CISC 7510X HW# 7 (due by Nth class): Your buddy stops over for lunch and tells you about his 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! 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. 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?).

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). Also submit database schema (DDL, create table statements), and query statements/process to find a compatible part.


CISC 7510X HW# 8: Given a database table such as: create table file(id int, parentid int, name varchar(1024), size int, type char(1)); write a single (recursive) database query to list FULL PATH of all files. [assume type is either "F" or "D" for file or directory]. Your query should give you similar output to unix command: "find . -type f".

Submit query in an email; put "CISC 7510X HW8" in email subject.


CISC 7510X HW# 9: Write a program to peform a database backup. Generate a public/private key pair (using GnuPG, or anything else). Your backup program/script must run daily, backup a table in a database into a .csv.gz file (comma delimited, gzip compressed [do not use database specific binary formats]). And encrypt the backup using your PUBLIC key.

Note that you can use any language, database, utility, configuration, etc. (cron script or windows scheduler is ok). The key is that the backup is comma delimited (do not export to database specific formats), gzip compressed, AND encrypted with public key---and is generated daily (without your intervention). Email me the program/script and instructions on how to set it up to run daily (for cron, I want the crontab line, etc., for windows scheduler, I want a batch file to setup to run and instruction on how to set it up in scheduler)


CISC 7510X HW# 10: Part1: It's year 2032, and flying cars are finally here. For safety, each is equipped with a black box that logs (every second): GPS timestamp, GPS latitude, longitude, and altitude.

To keep its flying registration, your flying car transmits this data nightly to the FAA, so your safe flying record can be verified (or appropriate tickets issued if not).

Your job as a contractor for the FAA is to write queries that generate tickets. Your database gets 50 million car records per day (all flying cars in the US, in year 2032), each one logging their position every second for the entire day. Your task is:

1. Write a query that identifies speeders (anyone flying over 500mph). What's the running time of your query, in big-O notation (how will the database execute your SQL?).

2. Airborne flying cars must keep a distance of 50 feet away from any other airborne flying car. Write a query that identifies violators and tickets *both* cars [assume airborne means 50 feet altitude]. Again, what's the running time of your query in big-O notation.

Note, millions of records, you can't just do an inner join and compare distances: you may assume the existance of a "distance" function that takes two sets of coordinates as arguments, e.g.: distance(x1,y1,z1,x2,y2,z2) and returns distance.

Part2: It's year 2022, and the city is strapped for cash. You notice license-plate reading cameras at highway entrances and exits (and all intersections), and get an idea... someone is taking a picture and logging the license plates in a database for every car that goes near those cameras. We get: GPS timestamp, GPS latitude and longitude of camera, and car license plate.

Your job as a DMV contractor: write a query to ticket top 5% of speeders, assuming max speed within the city (including highways) is 50mph.

Hint: If a car is photographed at location X, at 9:00:00am, and is then photographed again at some other random location Y, that is 1 mile away at 9:01:00am, that implies the car drove at 60mph (1-mile in 1-minute) between the two locations. Note that we don't care which road the driver used---unless they can bend space-time and teleport, they *had* to have gone at *least* 60mph between the two locations.

Note that part2 is somewhat different from part1... For both parts, assume your database is *huge* (millions of records---try to come up with solutions that are faster than O(n^2)).

Submit SQL queries to solve both problems.



































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