This document describes a Hadoop project to find adjusted closing stock prices when dividends are not reported. It involves reading data from two CSV files - one with dividend information and one with daily stock prices. The architecture uses a mapper to parse the input data and a reducer to retrieve the adjusted closing price by matching dates when dividends are zero. Pseudocode is provided for the mapper and reducer. The business implication is that adjusted closing prices provide a more accurate reflection of a stock's value over time compared to raw closing prices.

1. HADOOP PROJECT
Submitted By
Ankush Roy
Apuroop Pulabhatla
Ashitha VS
Krishna Bollojula
Srikanth Mallya
Koushik Rakshit
Roma Agrawal

2. CONTENTS
Business Problem
Understanding Data
Architecture
Psuedo code
Business Implication

3. BUSINESS PROBLEM
We need to find the adjusted closing price for
each day a stock has not reported dividend.
We are given two data sets:
1Dividends – A CSV file that gives us information
about the dates a dividend is returned.
2. NYSE_daily_prices – A bunch of CSV files that has
all the information about stock prices.

4. continued…
• We have to retrieve the dates when
dividends have a value 0, from the
dividends data set and match that with
the NYSE daily prices data set and hence
retrieve the corresponding adjusted
closing price.
.

5. UNDERSTANDING DATA
 The NYSE Daily Prices File has the following
columns separated by commas(CSV File):
exchange, stock_symbol, date, stock_price_open,
stock_price_high, stock_price_low, stock_price_close,
stock_volume, stock_price_adj_close
 The NYSE Daily Dividends File has the
following columns separated by commas(CSV
File):
exchange, stock_symbol, date, dividends

6. ARCHITECTURE
Mapper
Reducer
Output
Input Files
<Stock_symbol, Date, X, X, X, X, X
Adjusted_closing_price>
<Stock_symbol | Date, Adjusted_closing_price>
<Stock_symbol | Date, Dividend>
<Stock_symbol | Date, Adjusted_closing_price>

7. PSEUDOCODE - MAPPER
public static class StockAnalysisMapper extends MapReduceBase
implements Mapper<LongWritable, Text, Text, Text>
{
@Override
public void map(LongWritable key, Text
value,OutputCollector<Text, Text> output, Reporter reporter)
throws IOException
{
// switch case to parse the input lines and store the data
// check for null values in the key
// check the header and send the key value to output collector
}
}

8. PSEUDOCODE-REDUCER
public static class StockAnalysisReducer extends MapReduceBase implements
Reducer<Text, Text, Text, Text>
{
@Override
public void reduce(Text key, Iterator<Text> values,OutputCollector<Text, Text> output,
Reporter reporter) throws IOException
{
while (values.hasNext())
{
// Parse the inputs which are count,stock adjusted closing price and check
// Store them as required after parsing
//check for null values of stock adjusted closing price
}
//Increment the sum
// write to output if sum is 1
}
}

9. BUSINESS IMPLICATION
The closing price of a stock is exactly that: the
price of that stock at the close of the trading day.
The adjusted closing price uses the closing price
as a starting point, but it takes into account factors
such as dividends, stock splits and new stock
offerings.
The adjusted closing price represents a more
accurate reflection of a stock's value, since
distributions and new offerings can alter the
closing price.

10. Continued…
The primary use for the adjusted closing
price is as a means to develop an
accurate track record of a stock's
performance.
The comparison of a stock's historical
adjusted closing price to its current price
shows the true rate of return.

11. Thank you