From 3932a14216332679d688c545308216dc000ddfe5 Mon Sep 17 00:00:00 2001 From: Razvan-Daniel Mihai <84674+razvan@users.noreply.github.com> Date: Tue, 22 Jul 2025 12:14:13 +0200 Subject: [PATCH] feat: link picture to rendered GH notebook (#279) * fix: link picture to GH notebook * fix attributes * another try * fix typo * replace built in attr with custom one (without .git suffix) --- .../jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data.adoc | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/modules/demos/pages/jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data.adoc b/docs/modules/demos/pages/jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data.adoc index 45036590..535dde2d 100644 --- a/docs/modules/demos/pages/jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data.adoc +++ b/docs/modules/demos/pages/jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data.adoc @@ -12,6 +12,7 @@ :jupyter: https://jupyter.org :spark-connect: https://spark.apache.org/docs/latest/spark-connect-overview.html :spark-connect-client: https://github.com/stackabletech/docker-images/blob/main/spark-connect-client/Dockerfile +:repo-url: https://github.com/stackabletech/demos This demo showcases the integration between {jupyterlab}[JupyterLab], {spark-connect}[Spark Connect] and {hadoop}[Apache Hadoop] deployed on the Stackable Data Platform (SDP) Kubernetes cluster. The SDP makes this integration easy by publishing a discovery ConfigMap for the HDFS cluster and a Spark Connect service. @@ -115,7 +116,7 @@ image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyterlab_login.png[ Log in with token `adminadmin`. You should arrive at your workspace: -image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyterlab_workspace.png[] +image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyterlab_workspace.png[link={repo-url}/blob/{page-origin-refname}/stacks/jupyterhub-pyspark-hdfs/notebook.ipynb,linktarget=_blank,alt="JupyterLab Notebook"] Now you can double-click on the `notebook` folder on the left, open and run the contained file. Click on the double arrow (⏩️) to execute the Python scripts (click on the image above to go to the notebook file).