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# Preparing Your Local DataHub Environment
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## Deploy DataHub Quickstart
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You'll need a local instance of DataHub running for this tutorial:
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- Follow the [DataHub Quickstart Guide](/docs/quickstart.md) to get one up and running.
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```shell
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python3 -m pip install --upgrade pip wheel setuptools
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python3 -m pip install --upgrade acryl-datahub
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```
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If you can see datahub version like this, you're good to go.
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```shell
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$ datahub version
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DataHub CLI version: 0.10.0.1
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Python version: 3.9.6 (default, Jun 16 2022, 21:38:53)
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[Clang 13.0.0 (clang-1300.0.27.3)]
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```
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Run datahub quickstart. This will deploy local datahub server to http://localhost:9002
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```shell
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datahub docker quickstart
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```
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After logging in with the default credential(`username: datahub / password: datahub`), you can see DataHub ready for you.
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2023-03-19 05:00:41 +09:00
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2023-03-13 10:05:15 +09:00
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Please refer to [DataHub Quickstart Guide](/docs/quickstart.md) for more information.
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## Ingest Sample Data
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We will use sample data provided with datahub quickstart.
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If you already have data on your datahub, you might skip this part.
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```shell
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datahub docker ingest-sample-data
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```
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This will ingest various entities like datasets, terms and tags to your local DataHub.
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2023-03-19 05:00:41 +09:00
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2023-03-13 10:05:15 +09:00
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Now you're ready to start!
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