代写CS5010作业、代做Basic Concurrency作业、代写Java程序作业、Java语言作业代做
CS5010 Fall 2018
Assignment 6 - Basic Concurrency
Overview
The aim of this assignment is to give you experience designing and implementing a concurrent
program to process a reasonably large amount of data. We’ll start by implementing a serial
version of the problem, and then redesign to create a highly concurrent solution.
The Problem Scenario
Your overworked and underpaid Professor is desperately trying to write a research paper on
performance testing of cloud-based applications. He has generated a tonne of data from tests
that is currently processed partially automatically, and partially manually in a spreadsheet. To
speed up results processing, a fully automated solution is needed.
This is where you come in.
The current tests produce two very simple .csv files.
One records the results of HTTP POST requests sent to a server, and the other records the
results of HTTP GET operations.
In both files, the format is identical, ie:
{time stamp, operation type, latency, HTTP response code}.
● Time stamp is a value returned from System.currentTimeMillis();.It represents the time
the request was sent
● Operation is POST or GET
● Latency is a value in milliseconds - the round trip response time for the request.
● HTTP response code should be self explanatory :) It should be 200.
Here’s a sample extract from the POST file:
154134849941 POST 1814 200
154134850122 POST 246 200
154134850147 POST 112 200
154134850158 POST 160 200
154134850174 POST 107 200
154134850185 POST 174 200
Your task is to process the this raw data from both files and produce performance statistics that
characterize the test.
The processing has several steps:
First, for each file (POST and GET), process the individual request latencies into 1 second
‘buckets’. Take the first time stamp in each file as time 0, and create buckets for each second
that the test runs for, relative to the start time.
Write two new .csv files which contain the output of your processing, with the format:
{1 Second Bucket start ime,
# of requests in that bucket,
mean latency of requests in that bucket)
Here’s an example of this format
1541348499 3 1087
1541348500 11 233
1541348501 12 363
1541348502 11 132
1541348503 16 145
1541348504 16 380
After writing these lines to the files, you need to calculate:
1. Test length: How many second between start of POST/GET and end?
2. Mean latency (in milliseconds, no decimal places)
3. The 99th percentile latency (in milliseconds, no decimal places)
4. Total Throughput = total number of requests processed/test length in seconds
Write these values at the bottom of each csv file after ‘bucketizing’ the results.
Next ….:
Each test sends more POSTs than GETs. So while you should see POST requests continuously
through the whole test time (every bucket), there will be intervals when there are POSTs but no
GETs. Here’s an example, where there are no GET requests in time interval 1538758101
onwards.
POST GET TOTAL
1538758093 575 176 1538758093 34 88 609
1538758094 557 185 1538758094 27 94 584
1538758095 553 181 1538758095 17 88 570
1538758096 570 181 1538758096 12 78 582
1538758097 542 186 1538758097 11 88 553
1538758098 569 181 1538758098 13 78 582
1538758099 568 181 1538758099 10 101 578
1538758100 562 181 1538758100 9 79 571
1538758101 570 180 570
1538758102 579 170 579
1538758103 589 178 589
1538758104 551 182 551
1538758105 575 177 575
You therefore need to read through the two result files and produce a third with the above
format. This file ‘time aligns’ requests so that POSTs and GETs for the same time interval
appear on the same row, and the total number of requests for that interval is in a new column on
the right. Insert a blank column after the POST and GET columns.
Finally, calculate:
1. The overall throughput for the test (combined POST and GET) in requests per second
2. The peak throughput - ie the bucket with the higher total throughput
And write these values at the bottom of the file.
Part 1 - Sequential Solution
Easy - write a sequential version to solve the above problem.
The main class should be called PerformanceDataProcessor() and accept two file names as
command line arguments - the first contains the POST results, the second the GET results.
These files are .csv file, and have a name that ends with the word ‘raw’.
When you write the two new processed files, replace ‘raw’ with ‘results’.
When you write the time-aligned file, replace ‘results’ with ‘combined’.
For testing you are provided with two sets of ‘raw’ files. All have long test names, but the ones
with JavaTest in the title are relatively small in size. The other pair are quite a bit larger :). This
size may influence your solution.
Step 2 - Concurrent Solution
Now, redesign your solution to use threads in a ‘producer-consumer’ design style. Same inputs.
Same outputs. But the code now contains multiple threads.
For example, every time you read a file, you can think of this as a producer that simply knows
how to read this given file type and write each line ‘somewhere’ for another thread, the
consumer, to process. Consumers could read the contents and transform the file contents into
the results required, and write these ‘somewhere’ for maybe another thread to write the output.
This is called a ‘pipe-and-filter’ architecture.
Your solution must have producer and consumer threads running concurrently, and
communicating via some suitable shared data structure. Producers and consumers should be
loosely coupled and communicate only through some queue or channel.
Step 3: Identify the Peak phase
Modify your concurrent solution to take an additional integer value on the command line.
Let’s call this ‘threshold’. The threshold is a value that the user wants to use to identify the
PEAK test load period, when the client load is at its highest.
You should use it as follows:
1. Process the {testname}POST-results.csv file to find the first interval with throughput >=
to the threshold value. This interval marks the start of the peak phase.
2. Now find the end of the peak phase by finding the last interval with throughput >= to the
threshold value.
3. Create a new file called .{testname}POST-peak.csv that contains all the rows from the
peak phase
4. Calculate for the peak phase data the following, and write the results at the bottom of the
file:
a. The duration of the peak phase in seconds
b. The mean throughput
c. The highest interval requests/sec
d. The 5th percentile value for the peak phase throughput
e. The mean response timehttp://www.6daixie.com/contents/9/2139.html
f. The 99th percentile response time
And that’s it!!
Submission Requirements
As per previous assignments, use the maven archetype. Write great code or you will lose
points. Deadline Monday 12th November 6pm PST
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