/vagrant-hadoop-hive-spark

Vagrant project to spin up a single node VM running current versions of Hadoop, Hive and Spark

Primary LanguageShellApache License 2.0Apache-2.0

Vagrant Docker for Hadoop, Spark and Hive

Introduction

Vagrant project to spin up a single virtual machine running:

  • Hadoop
  • Hive
  • HBase
  • Spark
  • Tez

Version Information

The versions of the above components that the VM is provisioned with are defined in the file scripts/versions.sh

The following version combinations are known to work: -

  1. Spark-2.1.1 based on: -

    • Hadoop 2.7.3
    • Hive 1.2.2
    • Spark 2.1.1
    • Tez 0.8.5
    • Sqoop 1.4.6
    • Pig 0.17.0
    • flume 1.7.0
    • Zeppelin 0.8.0 (with Spark/scala, md, file and JDBC interpreters)

  2. Spark-2.3.0 based on: -

    • Hadoop 2.7.6
    • Hive 2.3.3
    • Spark 2.3.0
    • Tez 0.9.1
    • Sqoop 1.4.6
    • Pig 0.17.0
    • flume 1.7.0
    • Zeppelin 0.8.0 (with Spark/scala, md, file and JDBC interpreters)

Services

The virtual machine will be running the following services:

  • HDFS NameNode + DataNode
  • YARN ResourceManager/NodeManager + JobHistoryServer + ProxyServer
  • Hive metastore and server2
  • Spark history server
  • Hbase server

Getting Started

  1. Download and install VirtualBox and/or Docker
  2. Download and install Vagrant.
  3. Clone this repo.
  4. Check the Vagrentfile and comment/uncomment the optional components as required (Pig/Sqoop/HBase/Zeppelin/flume).
  5. Check the scripts/versions.sh file for the versions of the components.
  6. In your terminal change your directory into the project directory (i.e. cd vagrant-hadoop-spark-hive).
  7. Run vagrant up --provider=virtualbox to create the VM using virtualbox as a provider. Or run vagrant up --provider=docker to use docker as a provider. (NOTE This will take a while the first time as many dependencies are downloaded - subsequent deployments will be quicker as dependencies are cached in the resources directory).
  8. Execute vagrant ssh to login to the VM.

Work out the ip-address of the docker container

To access the web user interfaces of the various services from your host machine, you need to work out which ip address to connect to. To determine this run the following docker commands on the host: -

docker container ls

CONTAINER ID        IMAGE                                      COMMAND               CREATED             STATUS              PORTS                                                                                                                    NAMES
a44ca8ded5b8        nishidayuya/docker-vagrant-ubuntu:xenial   "/usr/sbin/sshd -D"   About an hour ago   Up About an hour    0.0.0.0:4040->4040/tcp, 0.0.0.0:8080->8080/tcp, 0.0.0.0:8088->8088/tcp, 0.0.0.0:9083->9083/tcp, 127.0.0.1:2222->22/tcp   vagrant-hadoop-hive-spark_node1_1539427474

then

docker inspect a44ca8ded5b8 | grep -i ipaddress
            "SecondaryIPAddresses": null,
            "IPAddress": "172.17.0.2",
                    "IPAddress": "172.17.0.2",

So, in the case above the container's ip address is 172.17.0.2 - you can substitute this address if 'node1' does not work.

Work out the ip-address of the virtualbox VM

The ip address of the virtualbox machine should be 10.211.55.101

Map Reduce - Tez

By default map reduce jobs will be executed via Tez to change this to standard MR, change the following parameter in $HADOOP_CONF/mapred-site.xml from: -

    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn-tez</value>
    </property>

to

    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>

Web user interfaces

Here are some useful links to navigate to various UI's:

Substitute the ip address of the container or virtualbox VM for node1 if necessary.

Shared Folder

Vagrant automatically mounts the folder containing the Vagrant file from the host machine into the guest machine as /vagrant inside the guest.

Validating your virtual machine setup

To test out the virtual machine setup, and for examples of how to run MapReduce, Hive and Spark, head on over to VALIDATING.md.

Managment of Vagrant VM

To stop the VM and preserve all setup/data within the VM: -

vagrant halt

or

vagrant suspend

Issue a vagrant up command again to restart the VM from where you left off.

To completely wipe the VM so that vagrant up command gives you a fresh machine: -

vagrant destroy

Then issue vagrant up command as usual.

To shutdown services cleanly

$ vagrant ssh
$ sudo -sE
$ /vagrant/scripts/stop-spark.sh
$ /vagrant/scripts/stop-hbase.sh
$ /vagrant/scripts/stop-hadoop.sh

Swapspace - Memory

Spark in particular needs quite a bit of memory to run - to work around this a swapspace daemon is also configured and started that uses normal disk to dynamically allocate swapspace when memory is low.

Problems

Sometimes the Spark UI is not available from the host machine when running with virtualbox. Setting: -

 export SPARK_LOCAL_IP=10.211.55.101
 spark-shell .....

Seems to solve this.

More advanced setup

If you'd like to learn more about working and optimizing Vagrant then take a look at ADVANCED.md.

For developers

The file DEVELOP.md contains some tips for developers.

Credits

Thanks to Alex Holmes for the great work at (https://github.com/alexholmes/vagrant-hadoop-spark-hive)

Matheus Cunha