The project is split into several services:
- Cassandra persists the data: blocks, transactions, and visualisations (analysed data).
- Bitcoin is used to connect to the Bitcoin blockchain. It's a simple Bitcoin Core node whose role is to index all the blocks and transactions and make them consumable through a HTTP JSON RPC interface.
- Scanner connects to the bitcoin service through its APIs and stores all the blocks and transactions in the Cassandra database.
- Spark analyses the Bitcoin blockchain data stored in Cassandra.
- API is a REST interface that allows clients to consume the data stored in Cassandra.
- Frontend is the web app used to explore the blockchain and visualise analysed data.
Each service contains 1 or more containers and can be scaled independently from each other.
All docker images are hosted: https://hub.docker.com/u/openblockchaininfo/
The following instructions will walk you through installing the entire openblockchain application including all system dependencies and requirements allowing you to run openblockchain from most base systems (Linux, OSX, Windows).
The instructions will start by guiding you through installing Ubuntu on VirtualBox.
Due to the computing power and disk space requirements, the data storage and processing for the project was designed to be run on several machines, preferably in a cloud with local management from a host machine.
The following instructions guide you through setting up your host machine with Ubuntu and docker-engine, docker-machine and docker-compose.
First you need to install VirtualBox by following these instructions
You then need to download Ubuntu 16.04.1 LTS - 64 bit by following these instructions
You need to create a new virtual machine using VirtualBox. The virtual machine (hereafter referred to as 'the host machine') will be used to deploy the application. The host machine requires:
- Ubuntu 64 bit
- RAM: 2GB
- CPU: Any
- Disk: 20GB
When you start the host machine for the first time select Ubuntu 16.04.1 LTS - 64 bit (which you downloaded in the previous step) as the start-up disk (it is possible to run the project on other versions of Ubuntu and even other operating systems such as Windows and OS X, but instructions for those have not been included here).
The host machine will only be used to send commands to the cluster.
The cluster machines (where the services will be deployed) require (each):
- RAM: 4GB+
- CPU: 4+ cores
- Disk: 150GB+
Once you set up the host machine (see the following "Prerequisites" section), the "Cluster Setup" instructions will guide you through the steps required to create 3 machines on Scaleway.
These must be installed on the host machine only. Make sure that your host machine has Ubuntu installed (which you will have if you have followed the previous steps).
1. Install Docker Engine
Docker Engine includes the docker client. docker will be used to communicate with the docker daemons which run on every machine in the cluster.
Update package information. Ensure that APT works with the https method, and that CA certificates are installed:
$ sudo apt-get update
$ sudo apt-get install apt-transport-https ca-certificates
Add the official GPG key and APT repository:
$ sudo apt-key adv --keyserver hkp://p80.pool.sks-keyservers.net:80 --recv-keys 58118E89F3A912897C070ADBF76221572C52609D
$ sudo echo "deb https://apt.dockerproject.org/repo ubuntu-wily main" > /etc/apt/sources.list.d/docker.list
Update the APT package index and install Docker:
$ sudo apt-get update
$ sudo apt-get install docker-engine
Start the docker daemon and verify it's installed correctly:
$ sudo service docker start
$ sudo docker run hello-world
Always up-to-date instructions are available at docker.com.
2. Install Docker Machine
docker-machine is used to provision machines for the cluster.
Download the Docker Machine 0.8 binary and extract it to your PATH:
$ sudo curl -L https://github.com/docker/machine/releases/download/v0.8.0/docker-machine-`uname -s`-`uname -m` > /usr/local/bin/docker-machine
$ sudo chmod +x /usr/local/bin/docker-machine
Check the installation by displaying the Machine version:
$ docker-machine version
Always up-to-date instructions are available at docker.com.
3. Install Docker Compose
Docker Compose is used to manage the services.
$ sudo curl -L https://github.com/docker/compose/releases/download/1.8.0/docker-compose-`uname -s`-`uname -m` > /usr/local/bin/docker-compose
$ sudo chmod +x /usr/local/bin/docker-compose
Check the installation by displaying the Compose version:
$ docker-compose --version
Always up-to-date instructions are available at docker.com.
You have now configured your host machine. You have:
- installed VirtualBox
- installed Ubuntu 16.04.1 LTS 64-bit on a virtual machine (the host machine)
- installed Docker Engine
- installed Docker Machine
- installed Docker Compose
This will allow you to manage all the microservices which constitue the openblockchain application from within the host machine.
The following instructions guide you through deploying the cluster in the cloud, using Scaleway. The cluster will contain the following services:
- 3 instances of Cassandra
- 1 Bitcoin node
- 1 Spark master
- 2 Spark workers
- 1 Spark job submitter
- 1 scanner container
- 1 api container
- 1 frontend container
The microservices are managed via docker-* on your host machine.
1. Create the discovery service
Using Scaleway
In order to use Scaleway, you'll first need to install the Scaleway driver for Docker Machine:
$ wget https://github.com/scaleway/docker-machine-driver-scaleway/releases/download/v1.2.1/docker-machine-driver-scaleway_1.2.1_linux_amd64.tar.gz
$ tar -xvf docker-machine-driver-scaleway_1.2.1_linux_amd64.tar.gz
$ sudo cp docker-machine-driver-scaleway_1.2.1_linux_amd64/docker-machine-driver-scaleway /usr/local/bin/
$ sudo chmod +x /usr/local/bin/docker-machine-driver-scaleway
Create a machine to host a Consul discovery service:
$ docker-machine create -d scaleway \
--scaleway-commercial-type=C2S --scaleway-name=obc-consul \
--scaleway-organization=<SCALEWAY-ACCESS-KEY> --scaleway-token=<SCALEWAY-SECRET-KEY> \
obc-consul
Point your docker client to the new machine:
$ eval $(docker-machine env obc-consul)
Create and start the service:
$ docker run --name consul --restart=always -p 8400:8400 -p 8500:8500 \
-p 53:53/udp -d progrium/consul -server -bootstrap-expect 1 -ui-dir /ui
2. Launch the Docker Swarm (cluster)
Using Scaleway
You can provision the machines from Scaleway, which provides affordable high-end servers that are perfect for this project.
Get your Scaleway credentials (access key and secret key) from this page, then deploy 3 machines:
$ docker-machine create -d scaleway \
--scaleway-commercial-type=C2L --scaleway-name=obc \
--scaleway-organization=<SCALEWAY-ACCESS-KEY> --scaleway-token=<SCALEWAY-SECRET-KEY> \
--swarm --swarm-master \
--swarm-discovery consul://`docker-machine ip obc-consul`:8500 \
--engine-opt cluster-store=consul://`docker-machine ip obc-consul`:8500 \
--engine-opt cluster-advertise=eth0:2376 \
obc
$ docker-machine create -d scaleway \
--scaleway-commercial-type=C2L --scaleway-name=obc-01 \
--scaleway-organization=<SCALEWAY-ACCESS-KEY> --scaleway-token=<SCALEWAY-SECRET-KEY> \
--swarm \
--swarm-discovery consul://`docker-machine ip obc-consul`:8500 \
--engine-opt cluster-store=consul://`docker-machine ip obc-consul`:8500 \
--engine-opt cluster-advertise=eth0:2376 \
obc-01
$ docker-machine create -d scaleway \
--scaleway-commercial-type=C2L --scaleway-name=obc-02 \
--scaleway-organization=<SCALEWAY-ACCESS-KEY> --scaleway-token=<SCALEWAY-SECRET-KEY> \
--swarm \
--swarm-discovery consul://`docker-machine ip obc-consul`:8500 \
--engine-opt cluster-store=consul://`docker-machine ip obc-consul`:8500 \
--engine-opt cluster-advertise=eth0:2376 \
obc-02
By default the Scaleway machines have a 50GB disk. However, Scaleway also attaches a 250GB SSD, which needs to be mounted manually:
$ printf "obc\nobc-01\nobc-02" | \
xargs -n 1 -I CONT_NAME docker-machine ssh CONT_NAME \
"echo ; echo ; echo CONT_NAME ;"`
`"echo 'Formatting...' ;"`
`"yes | mkfs -t ext4 /dev/sda ;"`
`"echo 'Mounting...' ;"`
`"mkdir -p /openblockchain ;"`
`"mount /dev/sda /openblockchain ;"`
`"echo 'Adding to fstab...' ;"`
`"echo '/dev/sda /openblockchain auto defaults,nobootwait,errors=remount-ro 0 2' >> /etc/fstab ;"`
`"echo 'Done' ;"
This additional storage will not be visible within the UI of your Scaleway account. You can manually check to verify the additional storage has been mounted (in this case checking obc):
$ docker-machine ssh obc
$ cat /etc/fstab
$ ls -al /openblockchain
3. Verify the swarm
Point your Docker environment to the machine running the swarm master:
$ eval $(docker-machine env --swarm obc)
Print cluster info:
$ docker info
You can also list the IPs that Consul has "discovered":
$ docker run --rm swarm list consul://`docker-machine ip obc-consul`:8500
1. Create the default network
Create an overlay network that allows containers to "see" each other no matter what node they are on:
$ docker network create --driver overlay --subnet 10.0.9.0/24 obcnet
List all networks, obcnet should be shown as overlay:
$ docker network ls
openblockchain has been designed with multiple microservices which are linked in the main Docker engine as git submodules.
The following command clones the project and all required gitmodules.
$ git clone --recursive https://github.com/open-blockchain/openblockchain.git
Once you have cloned the repo make sure to go into the directory.
$ cd openblockchain
2. Up!
From the root folder (which contains docker-compose.yml), run:
$ docker-compose up -d --build
Docker will deploy all the services. By default, it'll launch:
- 3 instances of Cassandra
- 1 Bitcoin node
- 1 Spark master
- 2 Spark workers
- 1 Spark job submitter
- 1 scanner container
- 1 api container
- 1 frontend container
3. Check the services
Show all containers and their status (they should all be "Up"):
$ docker-compose ps
Show the Cassandra cluster status (you should see 3 nodes):
$ docker-compose exec cassandra-seed nodetool status
In the mean time, the bitcoin server should've already scanned a few hundred blocks. Let's see it working live:
$ docker-compose logs -f --tail 100 bitcoin
You should see something like this, which means that it downloaded all the blocks from 0 to 187591 (in this example):
bitcoin_1 | 2016-08-25 15:03:16 UpdateTip: new best=00000000000006edbd5920f77c4aeced0b8d84e25bb5123547bc6125bffcc830 height=187589 log2_work=68.352088 tx=4696226 date=2012-07-05 03:45:13 progress=0.015804 cache=48.7MiB(122719tx)
bitcoin_1 | 2016-08-25 15:03:16 UpdateTip: new best=00000000000003f07c1227f986f4687d291af311a346f66247c504b332510931 height=187590 log2_work=68.352117 tx=4696509 date=2012-07-05 03:52:33 progress=0.015805 cache=48.7MiB(122815tx)
bitcoin_1 | 2016-08-25 15:03:16 UpdateTip: new best=00000000000002b34a755d25a5fee4c0ad0c018cf94f4b0afef6aabe823d304a height=187591 log2_work=68.352146 tx=4696593 date=2012-07-05 04:01:11 progress=0.015805 cache=48.7MiB(122839tx)
Now let's see the Spark dashboards, which should be empty right now. Run the following command to get the dashboard URL of each Spark master and worker:
$ echo "master: "`docker-machine ip obc`":8080"
$ echo "worker 1: "`docker-machine ip obc-01`":8081"
$ echo "worker 2: "`docker-machine ip obc-02`":8081"
1. Scan the blockchain
Show the scanners' logs:
$ docker-compose logs -f --tail 100 scanner-01
$ docker-compose logs -f --tail 100 scanner-02
The scanners were configured (in docker-compose.yml) so that they index a fixed range of blocks. However, in the beginning, when the bitcoin node hasn't yet reached block 330,000, scanner-02 (which is configured to scan blocks from 330,000 to 400,000) will not be able to scan anything. Therefore, it'll wait 10 minutes then try again until those blocks are available.
2. Spark analysis
The spark-submit service runs multiple Spark scripts every hour. These scripts generate visualizations (i.e. data points) that the API will provide to the frontend. You can see its progress by looking at the logs:
$ docker-compose logs -f --tail 100 spark-submit
Let's run a custom script which counts all the blocks and transactions in Cassandra:
$ docker-compose exec spark-submit sbt submit-Counter
When the script finishes, you should see something like this (ignore the logs that begin with a timestamp):
Blocks: 239699
Transactions: 18941698
3. Access the API
Find the name of the machine the api container is running on:
$ docker ps --filter "name=node-api" --format "{{.Names}}"
This will output something like obc-02/api, where the part before the slash is the machine name.
Now get the URL of the api, replacing <machine-name-from-above> accordingly:
$ echo "http://"`docker-machine ip <machine-name-from-above>`":10010"
4. Access the web app frontend
Find the name of the machine the frontend container is running on:
$ docker ps --filter "name=frontend" --format "{{.Names}}"
This will output something like obc-01/frontend, where the part before the slash is the machine name.
Now get the URL of the frontend, replacing <machine-name-from-above> accordingly:
$ echo "http://"`docker-machine ip <machine-name-from-above>`":80"
5. Visualizations
Depending on whether the spark-submit service had time to finish the Spark scripts or not, you might see visualizations in the frontend, at http://<frontend-ip>:80/blocks.
If visualizations are not yet available, check the progress of spark-submit:
$ docker-compose logs -f --tail 100 spark-submit
If it's idling, restart the service (docker-compose restart spark-submit). Otherwise, it's probably processing data from Cassandra. Let it finish the job and refresh the page (go away and make a cup of tea - in 60 mins it will certainly have crunched some numbers).
Copyright (C) 2016 Dan Hassan
Designed, developed and maintained by Dan Hassan [email protected]
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
API Service dependencies
https://github.com/scalatra/scalatra
Copyright (c) Alan Dipert [email protected]. All rights reserved.
Frontend Service dependencies
https://github.com/gaearon/react-redux-universal-hot-example
The MIT License (MIT), Copyright (c) 2015 Erik Rasmussen
node-api dependencies
https://github.com/nodejs/node/blob/master/LICENSE
Copyright Node.js contributors. All rights reserved.
openblockchain Service dependencies
https://github.com/docker/docker
Apache License, Version 2.0, January 2004, http://www.apache.org/licenses/
Scanner Service dependencies
https://github.com/outworkers/phantom
Copyright 2013-2016 Websudos, Limited. , All rights reserved.
Spark Service dependencies
https://github.com/apache/spark
Apache License, Version 2.0, January 2004, http://www.apache.org/licenses/