Base pyspark-jupyter image in official jupyter/pyspark-notebook

Author: luisbelloch

infra/pyspark-jupyter/Dockerfile

@@ -1,24 +1,7 @@
-FROM luisbelloch/spark
+FROM jupyter/pyspark-notebook
 LABEL maintainer="Luis Belloch <[email protected]>"
-
-ENV DEBIAN_FRONTEND=noninteractive
-RUN apt-get update && \
-    apt-get install -y --no-install-recommends python3-pip && \
-    rm -rf /var/lib/apt/lists/*
-
-RUN pip3 install --upgrade setuptools wheel && \
-    rm -rf ~/.cache/*
-
-RUN pip3 install --upgrade jupyterlab pandas && \
-    rm -rf ~/.cache/*
-
-ENV PYSPARK_DRIVER_PYTHON=jupyter
-ENV PYSPARK_DRIVER_PYTHON_OPTS="lab --ip $(awk \'END{print $1}\' /etc/hosts) --allow-root --port 8888"
-
-WORKDIR /opt/notebook
-COPY entrypoint.sh /opt/notebook
-
-EXPOSE 8888
-
-CMD ["/opt/notebook/entrypoint.sh"]
-
+ENV JUPYTER_ENABLE_LAB=yes
+RUN git clone https://github.com/luisbelloch/data_processing_course.git && \
+    mv data_processing_course/data . && \
+    mv data_processing_course/spark ./ejemplos && \
+    rm -rf data_processing_course

infra/pyspark-jupyter/Makefile

@@ -13,7 +13,7 @@ push:
 	docker push luisbelloch/pyspark-jupyter
 
 run:
-	./pyspark-jupyter.sh
+	docker run -p 8888:8888 -p 4040:4040 luisbelloch/pyspark-jupyter
 
 list:
 	docker images luisbelloch/pyspark-jupyter

infra/pyspark-jupyter/README.md

@@ -1,6 +1,8 @@
 # PySpark + Jupyter
 
-This folder contains a docker container with PySpark ready to be run from a Jupyter Notebook.
+This folder contains a docker container with PySpark ready to be run from a Jupyter Notebook, specifically customized for the course.
+
+For more general uses, we recommend to use the official [Jupyter Docker Stacks](https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html). This image itself is derived from `jupyter/pyspark-notebook` one.
 
 To run it, simply do:
 
@@ -10,7 +12,7 @@ docker run -p 8888:8888 -ti luisbelloch/pyspark-jupyter
 
 And navigate to [http://localhost:8888](http://localhost:8888). The password token will be displayed in the terminal.
 
-There's a simple script that will also mount `data` folder used in samples. You can easily access to it from the notebook:
+This image contains `data` folder used in the examples. You can easily access to it from the notebook:
 
 ```python
 rdd = sc.textFile('./data/compras_tiny.csv')