[GitHub] [beam] TheNeuralBit commented on a diff in pull request #17481: added the blog post

[GitBox <gi...@apache.org>]

TheNeuralBit commented on code in PR #17481:
URL: https://github.com/apache/beam/pull/17481#discussion_r860308582


##########
website/www/site/content/en/blog/beam-sql-with-notebooks-and-dataflow.md:
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@@ -0,0 +1,761 @@
+---
+title:  "Running SQL with Apache Beam Notebooks and Google Cloud Dataflow"
+date:   2022-04-26 00:00:01 -0800
+categories:
+  - blog
+aliases:
+  - /blog/2022/04/26/beam-sql-with-notebooks-and-dataflow.html
+authors:
+  - ningk
+---
+<!--
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+## Intro
+
+[Beam SQL](https://beam.apache.org/documentation/dsls/sql/overview/) allows a
+Beam user to query PCollections with SQL statements.
+[Apache Beam Notebooks](https://cloud.google.com/dataflow/docs/guides/interactive-pipeline-development)
+provides a cloud-hosted [JupyterLab](https://jupyter.org/) environment and lets
+a Beam user iteratively develop pipelines, inspect pipeline graphs, and parse
+individual PCollections in a read-eval-print-loop (REPL) workflow.
+
+In this post, you will see how to use `beam_sql`, a notebook
+[magic](https://ipython.readthedocs.io/en/stable/interactive/magics.html), to
+execute Beam SQL in notebooks and later move on to Dataflow. To follow the steps
+given in this post, you should have a project in Google Cloud Platform with
+[necessary APIs enabled](https://cloud.google.com/dataflow/docs/guides/interactive-pipeline-development#before_you_begin)
+, and you should have enough permissions to create a Google Cloud Storage bucket
+(or to use an existing one), query a public Google Cloud BigQuery dataset, and
+run Dataflow jobs.
+
+Once you have your Google Cloud project ready, you will need to create an Apache
+Beam Notebooks instance and open the JupyterLab web interface. Please follow the
+instructions given at:
+https://cloud.google.com/dataflow/docs/guides/interactive-pipeline-development#launching_an_notebooks_instance
+
+
+## Getting familiar with the environment
+
+### Landing page
+
+After clicking the `OPEN JUPYTERLAB` link, you will land on the default launcher
+page of the notebook environment.
+
+<img class="center-block"
+     src="/images/blog/beam-sql-notebooks/image1.png"
+     alt="Beam SQL in Notebooks: landing page">

Review Comment:
   These images don't seem to be rendering in the staged version of the website: 
   ![image](https://user-images.githubusercontent.com/675055/165645255-2f07d595-db64-4c66-b04c-78056e08f9bb.png)
   
   I think because of the extra "blog" in the src?
   
   You might also look at using the markdown syntax for linking an image `![Example image](/image.png)` (see https://gohugo.io/content-management/static-files/)



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