Hadoop Mac Download

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In this blog, I will be demonstating how to setup single node Hadoop cluster using Docker on Mac os X. Before actuallyinstalling any of these components, let us first understand what these components are and what are they used for.

Download
  • Guide to Install Hadoop on Mac OS. Run this command before everything in order to check if Java is already installed on your system: $ java – version. If Java is installed, move forward with the guide but if it isn’t, download it from here. Follow these steps accurately in order to install Hadoop on your Mac operating system: Part-1.
  • Setting up Hadoop 2.6 on Mac OS X Yosemite. After comparing different guides on the internet, I ended up my own version base on the Hadoop official guide with manual download. If you prefer Homebrew, this one would be your best choice. Actually there is no difference in the configuration of these two methods except the file directories.

Hadoop Mac Download Windows 10

There are 6 steps to complete in order setup Hadoop (HDFS) Validate if java is installed. Setup environment variables in.profile file. Setup configuration files for local Hadoop. Setup password less ssh to localhost. Initialize Hadoop cluster.

Apache Hadoop is software framework which is used to perform distributed processingof large data sets accross clusters of computers using simple programming models. Hadoop does a lot more than what is describedin this blog. For the sake of simplicity we will only consider the two major components of Hadoop i.e.

  • Hadoop File System(HDFS)
  • Mappers and Reducers

HDFS is Java based file system that provides reliable, scalable and a distributed way of storing application data into different nodes. In the hadoop cluster, the actual data isstored on the data nodes and the metadata (data about data) is stored on the Name node.

Mapping is the first phase in Hadoop processing in which the entire data is split in tuples of keys and values.After this operation these key value tuples are passed to the shuffler which collects the same type keys from all the mappersand send them to the reducers which finally combine them and writes the output in a file.

Now, lets talk a little bit about Docker. Docker is a tool to provision containers to run different applications withoutrequiring the installation of entire OS. It can be thought of like a Virtual Machine running tool(like VMWare, Virtual box), butit is more flexible, fast, powerful and less resource consuming. You can literally spawn up a container for your application in a fractionof seconds.

Now that we have a basic idea about what Hadoop and Docker is, we will start installing them on our machine.

First we will download the docker dmg file. To download the docker dmg file, go to Docker Store and click on the Get Docker download button.This will start the download of the dmg file. Once the file is downloaded on your machine, double click the dmg file and then install docker by dragging the docker icon into the acpplication folder.

After installing docker, start the docker application from spotlight as shown in the below given picture.

Now to run a test application in your docker, open a terminal a fire the below given query.

This command will try to fetch an image named hello-world and run in a container. After running this command you should see output somewhat like this.

Congratulations, you have successfully installed docker on your machine. Now you can fetch images from docker store or can create your own images using Dockerfile. I will write a seperate blog on how to write a Dockerfile and Docker compose file.

As we have completed the Docker installation part, now we have to pull the Hadoop image from the docker store and run that in a container. The command we used above not only pulls the image, but it also runs that image in a container after pulling it from docker store. We can separate these two operations by instructing docker only to pull the image and not running it untill asked explicitly. To run the hadoop image just fire the below given command.

The above command should produce output like this

To check whether the image downloaded successfully, run the command to list all the images. You should see sequenceiq/hadoop-docker:2.7.1 image among all the listeddocker images.

Now that we have got our hadoop image downloaded on our system we need to run it in a container so that we can run the basic map-reduce tasks on it.To run a docker image you need to fire the following command on the terminal.

You must be very puzzeled after seeing such a lengthy command with so many parameters, but don’t worry I will help you in understatingwhat all these parameters actually mean and what this command is doing.

  1. The docker run part instructs the docker program to run an image in a container. This is the basic command to run any container.
  2. -it specifies that that we need to run an interactive process (bash in this case) and docker should tty session to the container so that we can execute commands inside the container.
  3. -p 50070:50070 is used to map the host port with the container port. If you want to access some ports of the container then you need need to specify the mapping with -p flag and host_machine_port:container_port mapping.
  4. sequenceiq/hadoop-docker:2.7.1 is the name of the image that we want to run.
  5. /etc/bootstrap.sh is the program we want to start once out docker is up and running.
  6. -bash is the argument to the program /etc/bootstrap.sh

After running the above command you should get the bash prompt (as shown below) of the container. Now you can actually execute commands inside this container using this bash prompt.

To make sure that the hadoop service is running on you docker container, open any browser on your mac and visit http://localhost:50070/.You should see a page similar to the one give below. This page lists information about the Namenode and HDFS.

Congratulations once again, you have a running Hadoop instance on a docker container. Now you can run the basic in-built hadoop map and reduce programs.To run these programs run the following commands on the container bash prompt. (Notice the bash-4.1# after you ran the container. This is the container prompt).

Let us split the above command and analyse each of the arguments in to understand their role.

  1. bin/hadoop is used to initiate the hadoop program.
  2. Every map and reduce task is defined in hadoop by giving a jar which contains the implementation of Map and Reduce tasks. In the above command, jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.1.jar is used to pass the location of the jar file which contains the definition of out map and reduce tasks.
  3. grep input output 'dfs[a-z.]+ is an argument to our jar file. grep specify that we want to count the words in all the files present in the directory named input put the output in the directory named as output

To check the output whether our job ran successfully and gave correct output we need to print the contents of all the filespresent in the output directory. Since data in HDFS is spread across multiple data nodes, so we cannot just simply list or open the files by using commands like ls or cat.Instead we need to tell HDFS that we want to execute these commands to get our output. To do this we need to execute following commands.

This should produce output like this.

The first column in this output represents the count of the number of time the string given in second column occured in all the file present in input direcory.

To have more fun with hadoop you can also try solving the Sudoku. Since by now, you must have got an idea of how can we run map/reduce jobs, it would be pretty easy for you to understand this example.To solve the sudoku, first create a file named unsolved_sudoku.txt and paste the unsolved sudoku in that file. For example, lets solve this sudoku.

Tu solve this sudoku we will be using the same jar file but with different arguments. So the new command will be

The execution of above command should print the solved sudoku on the terminal.

Conclusion

We successfully ran a hadoop single node cluster in docker container running on a mac machine. We learned the basics ofhadoop operations and how can we run map and reduce jobs using sample hadoop jar files. We solved one sudoku problem as well using thehadoop map/reduce. We also learned that docker containers are the easiest and fastest way to get an application up and running withoutinvesting much effort on configuration.

Hadoop Download Mac

Download Apache Spark™

  1. Choose a Spark release:

  2. Choose a package type:

  3. Download Spark:

  4. Verify this release using the and project release KEYS.

Note that, Spark 2.x is pre-built with Scala 2.11 except version 2.4.2, which is pre-built with Scala 2.12. Spark 3.0+ is pre-built with Scala 2.12.

Latest Preview Release

Preview releases, as the name suggests, are releases for previewing upcoming features.Unlike nightly packages, preview releases have been audited by the project’s management committeeto satisfy the legal requirements of Apache Software Foundation’s release policy.Preview releases are not meant to be functional, i.e. they can and highly likely will containcritical bugs or documentation errors.The latest preview release is Spark 3.0.0-preview2, published on Dec 23, 2019.

Link with Spark

Spark artifacts are hosted in Maven Central. You can add a Maven dependency with the following coordinates:

Hadoop Mac Download Full

Hadoop os

Hadoop Mac Download Windows 10

Installing with PyPi

PySpark is now available in pypi. To install just run pip install pyspark.

Release Notes for Stable Releases

Archived Releases

Download Hadoop Jar Files

As new Spark releases come out for each development stream, previous ones will be archived,but they are still available at Spark release archives.

Mac Download Game

NOTE: Previous releases of Spark may be affected by security issues. Please consult theSecurity page for a list of known issues that may affect the version you downloadbefore deciding to use it.