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			69 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
			
		
		
	
	
			69 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
| # DataHub Quickstart Guide
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| 
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| ## Deploying DataHub
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| 
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| To deploy a new instance of DataHub, perform the following steps.  
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| 
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| 1. Install [docker](https://docs.docker.com/install/) and [docker-compose](https://docs.docker.com/compose/install/) (if using Linux). Make sure to allocate enough hardware resources for Docker engine. Tested & confirmed config: 2 CPUs, 8GB RAM, 2GB Swap area.
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| 
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| 
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| 2. Launch the Docker Engine from command line or the desktop app. 
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| 
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| 
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| 3. Install the DataHub CLI
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|    
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|    a. Ensure you have Python 3.6+ installed & configured. (Check using `python3 --version`)
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|    
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|    b. Run the following commands in your terminal 
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|    ```
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|    python3 -m pip install --upgrade pip wheel setuptools
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|    python3 -m pip uninstall datahub acryl-datahub || true  # sanity check - ok if it fails
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|    python3 -m pip install --upgrade acryl-datahub
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|    datahub version
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|    ```
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|    If you see "command not found", try running cli commands with the prefix 'python3 -m' instead: `python3 -m datahub version`
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| 
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| 
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| 4. To deploy DataHub, run the following CLI command from your terminal
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|    ```
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|    datahub docker quickstart 
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|    ```
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|    Upon completion of this step, you should be able to navigate to the DataHub UI at [http://localhost:9002](http://localhost:9002) in your browser. You can sign in using `datahub` as  username and any password (no password validation by default).
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| 
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| 
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| 5. To ingest the sample metadata, run the following CLI command from your terminal
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|    ```
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|    datahub docker ingest-sample-data
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|    ```
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|    
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| That's it! To start pushing your company's metadata into DataHub, take a look at the [Metadata Ingestion Framework](../metadata-ingestion/README.md).
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| 
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| 
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| ## Resetting DataHub
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| 
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| To cleanse DataHub of all of it's state (e.g. before ingesting your own), you can use the CLI `nuke` command. 
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| 
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| ```
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| datahub docker nuke
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| ```
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| 
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| 
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| ## Troubleshooting
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| 
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| ### Command not found: datahub
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| 
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| If running the datahub cli produces "command not found" errors inside your terminal, your system may be defaulting to an older 
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| version of Python. Try prefixing your `datahub` commands with `python3 -m`:
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| ```
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| python3 -m datahub docker quickstart
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| ```
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| 
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| ### Miscellaneous Docker issues
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| 
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| There can be misc issues with Docker, like conflicting containers and dangling volumes, that can often be resolved by 
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| pruning your Docker state with the following command. Note that this command removes all unused containers, networks, images (both dangling and unreferenced), 
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| and optionally, volumes.
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| 
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| ```
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| docker system prune
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| ``` | 
