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Systems Engineering 2 - Assignment 1

Organization

  • deadline: 11:59pm AOE, 14th of Dec‘18

  • you will have two opportunities to test your solution before the deadline. We will test all repositories on November 30th, 2018 and December 12th, 2018 and publish the results on the course website.

    • mind that the results of these tests are not graded. Only the final result matters.
    • if your solution fails a test, you will not receive a detailed explanation of the reasons why it failed. Your task is to figure it out on your own.
  • git usage is mandatory (multiple commits with meaningful messages)

  • Go is mandatory

  • you have to work alone

  • don't share code

  • ask questions in the Auditorium

Task description

You are required to develop an online document library. Users are presented with an input form, where they can submit documents (e.g., books, poems, recipes) along with metadata (e.g., author, mime type, ISBN). For the sake of simplicity, they can view all stored documents on a single page.

form output
input form output sample

Hence, create an application with the following architecture. Don't worry, in this repository you can find some Makefiles, Dockerfiles, configuration files and source code to get you started.

./image/architecture.png

Nginx

Nginx is a web server that delivers static content in our architecture. Static content comprises the landing page (index.html), JavaScript, css and font files located in nginx/www.

  1. complete the nginx/Dockerfile
    1. upgrade the system
    2. install nginx
    3. copy nginx/nginx.conf from host to container's /etc/nginx/nginx.conf
    4. use port 80 in the container
    5. run nginx on container startup
  2. in docker-compose
    1. build the image
    2. assign nginx to the se_backend network
    3. mount the host directory nginx/www to /var/www/nginx in the container
  3. verify your setup (it should display the landing page)

HBase

We use HBase, the open source implementation of Bigtable, as database. hbase/hbase_init.txt creates the se2 namespace and a library table with two column families: document and metadata.

  1. build the image for the container description located in hbase/
  2. in docker-compose
    1. add hbase to the se_backend network

The Dockerfile exposes different ports for different APIs. We recommend the JSON REST API, but choose whatever API suits you best.

Note

  1. HBase REST documentation
  2. the client port for REST is 8080
  3. employ curl to explore the API
    1. curl -vi -X PUT -H "Content-Type: application/json" -d '<json row description>' "localhost:8080/se2:library/fakerow"
    2. yes, it's really fakerow
  4. gserve/src/gserve/HbaseJSON.go contains helpers to convert data from frontend JSON via Go types to base64-encoded HBase JSON and back
  5. you might want to use the (Un)marshal functions from the encoding/JSON package

ZooKeeper

Deviating from the architecture image, you don't need to create an extra ZooKeeper container. The HBase image above already contains a ZooKeeper installation.

  1. add an alias to the hbase section in docker-compose such that other containers can connect to it by referring to the name zookeeper

Note

  1. you are allowed to use the go-zookeeper library

grproxy

This is the first service/server you have to write by yourself. Implement a reverse proxy that forwards every request to nginx, except those with a "library" prefix in the path (e.g., http://host/library). Discover running gserve instances with the help of ZooKeeper and forward library requests in circular order among those instances (Round Robin).

  1. complete grproxy/Dockerfile
  2. in docker-compose
    1. build grproxy
    2. add grproxy to both networks: se_frontend and se_backend

Note

  1. you are allowed to use httputil.ReverseProxy
  2. you don't need to handle the case where an instance registered to ZooKeeper doesn't reply

gserve

Gserve is the second service you need to implement, and it serves basically two purposes. Firstly, it receives POST requests from the client (via grproxy) and adds or alters rows in HBase. And secondly, it replies to GET requests with an HTML page displaying the contents of the whole document library. It only receives requests from grproxy after it subscribed to ZooKeeper, and automatically unsubscribes from ZooKeeper if it shuts down or crashes.

  1. gserve shall return all versions of HBase cells (see output sample above)
  2. the returned HTML page must contain the string "proudly served by gserve1" (or gserve2, ...) without HTML tags in between
  3. complete gserve/Dockerfile
  4. in docker-compose
    1. build gserve
    2. start two instances gserve1 and gserve2
    3. add both instances to se_backend
    4. make sure, that both instances start after hbase and grproxy
    5. provide the names of the instances (gserve1, gserve2) via environmental variables

Hints

  • Start small, don't try to solve every problem at once.
  • Test your components against single Docker containers (e.g., gserve with HBase container), and integrate them into docker-compose later on.
  • The developer tools of your browser may help you to capture and analyse requests and responses.

Links

Git

  • push changes to your repo
  • if you find bugs in provided files or the documentation, feel free to open a pull request on Bitbucket

Frequently Asked Questions

  1. How do I use the JSON/Base64-encoding/(Un)Marshaling code?

    package main
    
    import "encoding/json"
    
    func main() {
       // unencoded JSON bytes from landing page
       // note: quotation marks need to be escaped with backslashes within Go strings: " -> \"
       unencodedJSON := []byte("{\"Row\":[{\"key\":\"My first document\",\"Cell\":[{\"column\":\"document:Chapter 1\",\"$\":\"value:Once upon a time...\"},{\"column\":\"metadata:Author\",\"$\":\"value:The incredible me!\"}]}]}")
       // convert JSON to Go objects
       var unencodedRows RowsType
       json.Unmarshal(unencodedJSON, &unencodedRows)
       // encode fields in Go objects
       encodedRows := unencodedRows.encode()
       // convert encoded Go objects to JSON
       encodedJSON, _ := json.Marshal(encodedRows)
    
       println("unencoded:", string(unencodedJSON))
       println("encoded:", string(encodedJSON))
    }
    
    /*
    output:
    
    unencoded: {"Row":[{"key":"My first document","Cell":[{"column":"document:Chapter 1","$":"value:Once upon a time..."},{"column":"metadata:Author","$":"value:The incredible me!"}]}]}
    encoded: {"Row":[{"key":"TXkgZmlyc3QgZG9jdW1lbnQ=","Cell":[{"column":"ZG9jdW1lbnQ6Q2hhcHRlciAx","$":"dmFsdWU6T25jZSB1cG9uIGEgdGltZS4uLg=="},{"column":"bWV0YWRhdGE6QXV0aG9y","$":"dmFsdWU6VGhlIGluY3JlZGlibGUgbWUh"}]}]}
    */
  2. Do I need a library to connect with HBase?

    No, we recommend the REST interface. You might also consider using Thrift, but we haven't tested it.

  3. Could you provide an example for an HBase scanner?

    Yes, for the command line:

    #!/usr/bin/bash
    
    echo "get scanner"
    
    scanner=`curl -si -X PUT \
       -H "Accept: text/plain" \
       -H "Content-Type: text/xml" \
       -d '<Scanner batch="10"/>' \
       "http://127.0.0.1:8080/se2:library/scanner/" | grep Location | sed "s/Location: //" | sed "s/\r//"`
    
    echo $scanner
    
    curl -si -H "Accept: application/json" "${scanner}"
    
    echo "delete scanner"
    
    curl -si -X DELETE -H "Accept: text/plain" "${scanner}"
  4. What is meant by "build gserve"?

    Build the docker image with docker compose, not the gserve binary.

Optional

You had a lot of fun and want more? No problem! Select a topic you're interested in, and enhance any of the components. For instance, query single documents or rows, replace nginx with a web server written by yourself, improve the error handling in Grproxy, write test cases or in the worst case just beautify the HTML/CSS. But keep in mind: your application shall still conform to the task description.

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