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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. Here I extend the official guide by more details in case you need it.
Npm isn't the only game in town when it comes to installing packages for use in webdev. One of the biggest alternatives to npm is the yarn package manager. Yarn does not host it's own registry. Because of this, when you install a library using yarn, you're using the NPM registry and the yarn CLI tool. Issue Can't run PouchDB node.js with yarn on macOS. It is working on Windows 10. Info Environment: Node.js v11.9.0 Platform: macOS Mojave Version 10.14.3 (18D109) Server: PouchDB Version 7.1.1 Reproduce See repository to reproduce: https. Yarn 2 doesn't support prepare lifecycle script, so husky needs to be installed differently (this doesn't apply to Yarn 1 though). See Yarn 2 install. To add a command to a hook or create a new one, use husky add cmd (don't forget to run husky install before). Npx husky add.husky/pre-commit 'npm test' Try to make a commit.
Also, this guide is part of my Hadoop tutorial 1. It aims to setting up the pseudo-distributed mode in single node cluster. And I will explain the HDFS configurations and command lines in Hadoop tutorial 2.
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Faisals-Mac: Code faisal$ npm. The operation was rejected by your operating system. Setup a Next.js project with PM2, Nginx and Yarn on Ubuntu 18.04. MacOS (OS X) Mac App Store: Official digital distribution platform for OS X apps. Part of OS X 10.7 and available as an update for OS X 10.6; Homebrew: Package manager for macOS, based on Git; Fink: A port of dpkg, it is one of the earliest package managers for macOS.
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1. Required software
1) Java
Run the following command in a terminal:
If Java is already installed, you can see a similar result like:
If not, the terminal will prompt you for installation or you can download Java JDK here.
2) SSH
First enable Remote Login in System Preference -> Sharing.
Now check that you can ssh to the localhost without a passphrase:
If you cannot ssh to localhost without a passphrase, execute the following commands:
2. Get a Hadoop distribution
You can download it from Apache Download Mirror.
3. Prepare to start the Hadoop cluster
1) Unpack the downloaded Hadoop distribution.
2) Run the following command to figure out where is your Java home directory:
You can see a result like:
3) In the distribution, edit the file etc/hadoop/hadoop-env.sh to define some parameters as follows:
4) Try the following command:
This will display the usage documentation for the hadoop script.
Now you are ready to start your Hadoop cluster in one of the three supported modes:
- Standalone mode
- Pseudo-distributed mode
- fully-distributed mode
We will go through pseudo-distributed mode and run a MapReduce job on YARN here. In this mode, Hadoop runs on a single node and each Hadoop daemon runs in a separate Java process.
4. Configuration
Edit following config files in your Hadoop directory
1) etc/hadoop/core-site.xml:
2) etc/hadoop/hdfs-site.xml:
3) etc/hadoop/mapred-site.xml:
4) etc/hadoop/yarn-site.xml:
5. Execution
1) Format and start HDFS and YARN
Format the filesystem:
Start NameNode daemon and DataNode daemon:
Now you can browse the web interface for the NameNode at - http://localhost:50070/
Make the HDFS directories required to execute MapReduce jobs:
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Start ResourceManager daemon and NodeManager daemon:
Browse the web interface for the ResourceManager at - http://localhost:8088/
2) Test examples code that came with the hadoop version
Copy the input files into the distributed filesystem:
Run some of the examples provided:
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This example counts the words starting with 'dfs' in the input.
Examine the output files:
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Copy the output files from the distributed filesystem to the local filesystem and examine them:
or View the output files on the distributed filesystem:
You can see the result like:
3) Stop YARN and HDFS
When you're done, stop the daemons with:
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