Real-time Cryptocurrency Price Updates

Static website to visit UI (GitHub repository)

Follow installation instructions and visit dynamic website for integrated app

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Technologies

• Cryptocurrency prices are fetched in real-time from Coinranking API

• JSON response is parsed, necessary fields extracted, and sent through to a Kafka topic via a Kafka Producer in Python

• Spark Structured Streaming application in Scala consumes the messages from the Kafka topic, transforms into required data types via a schema, and calculates aggregates on real-time messages

• Aggregates are calculated using window functions to calculate rolling average for each currency over a timespan. Currently supported aggregates are -

  • Moving Arithmetic Mean
  • Moving Geometric Mean
  • Moving Harmonic Mean

• Cassandra sink is used to persist both real-time prices as well as calculated aggregates from Spark

• Node.js and Express is used to create REST Endpoints to fetch and serve the latest data from Cassandra

• Server-side components are containerized with Docker Compose.

• React, Chart.js, and Material-UI is used to render responsive UI consisting of cryptocurrency cards and real-time dashboard. Updated prices and aggregates are fetched from REST Endpoint.

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UI Snapshots

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Docker Installation

• Download and install Docker Engine for your operating system. (Linux recommended)

• Download and install Docker Compose

• Navigate to the directory where the project is cloned

• In your terminal, run

docker-compose up

• Check the logs on the terminal and wait till cryptocurrency messages are being published

• In another terminal, from the project home directory run

bash start-services.sh

• To monitor Spark jobs, visit localhost:8080 in your browser

• Wait a few minutes for the job to execute as it is downloading packages, Spark UI will be updated with master and worker when the job begins

• Visit localhost:5000 to get the data as JSON. REST Endpoints are -

  • /latestPrice fetches the latest price of every coin
  • /latestPrice/symbol_coin fetches the latest price of the selected coin.
  • Eg. /latestPrice/BTC fetches -

  {
  "symbol_coin": "BTC",
  "timestamp": "2020-10-02T15:31:56.000Z",
  "id": "1",
  "market_cap": "195148831212",
  "name_coin": "Bitcoin",
  "number_of_markets": "19526",
  "percent_change_24hr": "-3.12",
  "price": "10545.2298078033",
  "total_supply": "18505887",
  "uuid": "Qwsogvtv82FCd",
  "volume": "18990315583"
  }
  

  • /latestAggregate fetches the latest calculated aggregates of every coin
  • /latestAggregate/symbol_coin fetches the latest calculated aggregate of the selected coin in the most recent sliding window
  • Eg. /latestAggregate/ETH fetches -

  {
    "symbol_coin": "ETH",
    "end_time": "2020-09-23T07:58:30.000Z",
    "arithmetic_mean": "336.0199798016828",
    "geometric_mean": "336.01994915594116",
    "harmonic_mean": "336.0199185102891",
    "start_time": "2020-09-23T07:53:30.000Z"
  }
  

• Visit dynamic website

• To shut services down, run

docker-compose down

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Manual Installation

Kafka Producer

Uses

• Python 3.8.2
• Apache Kafka 2.6.0

Zookeeper

• Navigate to Kafka installation directory and start Zookeeper in your shell

cd $KAFKA_HOME
bin/zookeeper-server-start.sh config/zookeeper.properties 

Kafka Server

• Navigate to Kafka installation directory and start Kafka server in your shell

cd $KAFKA_HOME
bin/kafka-server-start.sh config/server.properties

Kafka Topic

• Navigate to Kafka installation directory and create a Kafka topic "crypto_topic"

cd $KAFKA_HOME
bin/kafka-topics.sh --bootstrap-server localhost:9092 --topic crypto_topic \
--create --partitions 3 --replication-factor 1

• Check if the topic is created.

kafka-topics --bootstrap-server localhost:9092 --list

Python Producer

• Navigate to /kafkaProducer
• In config.ini change

[kafka]
bootstrap_servers=kafka:9092

to

[kafka]
bootstrap_servers=localhost:9092

• Create and activate your virtual environment

python3 -m venv cryptoEnv
source cryptoEnv/bin/activate

• Install dependencies.

pip install -r requirements.txt

• Start the producer service.

python3 kafkaProducerService.py

Cassandra Sink

Uses

• Apache Cassandra 3.11.8
• Java 1.8.0_265 OpenJDK

Create Tables

• Start Cassandra service.

sudo service cassandra start

• Check status of nodes.

nodetool status

• Open Cassandra Query Language shell

cqlsh

• Create the necessary tables.
• DDL is found in cassandraData/cqlqueries.cql

Spark Consumer

Uses

• Apache Spark 2.4.5
• SBT 1.3.13
• Java 1.8.0_265 OpenJDK

Package and Submit

• Navigate to /sparkConsumer
• In src/main/resources/config.properties change

kafka.bootstrap.servers=kafka:9092
spark.cassandra.connection.host=cassandra

to

kafka.bootstrap.servers=localhost:9092
spark.cassandra.connection.host=localhost

• Run the following in your shell, where $SPARK_HOME is the Spark installation directory

sbt package && \
$SPARK_HOME/bin/spark-submit --master local[*] --class processing.SparkRealTimePriceUpdates \
--packages com.datastax.spark:spark-cassandra-connector_2.11:2.4.3,org.apache.spark:spark-sql-kafka-0-10_2.11:2.4.5 \
target/scala-2.11/sparkconsumer_2.11-1.0-RELEASE.jar

• Monitor Spark from localhost:8080 on your browser

Node.js Backend

Uses

• Node.js 14.11.0

Start Server

• Navigate to /nodeRESTBackend
• In src/config.json change

"cassandraContactPoint" : "cassandra:9042",

to

"cassandraContactPoint" : "localhost:9042",

• Install packages

npm install

• Start the server

node src/server.js

React Frontend

Uses

• React
• Chart.js
• Material-UI

• Visit dynamic site, alternatively

Start Server

• Navigate to /reactUI

• Install packages

npm install

• Start the server

npm start

• Visit UI from localhost:3000 on your browser