add jupyter notebook

Dockerfile

@@ -1,4 +1,22 @@
 FROM bitnami/spark:3.5.1
 
+RUN export ORI_USER=$(id -u)
+# Switch to root to install packages
+USER root
 
-ENTRYPOINT ["sleep 10s"]
+# Install necessary packages
+RUN apt-get update && apt-get install -y \
+    # Fixing error: psutil could not be installed from sources because gcc is not installed
+    gcc \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Jupyterlab and other python dependencies
+RUN pip install jupyterlab==4.2.0 pyspark==3.5.1
+
+COPY scripts/entrypoint.sh /opt/
+RUN chmod a+x /opt/entrypoint.sh
+
+# Switch back to the original user
+USER ${ORI_USER}
+
+ENTRYPOINT ["/opt/entrypoint.sh"]

README.md

@@ -1,4 +1,54 @@
 # CDM Jupyterhub dockerfiles (Prototype)
 
 This prototype establishes a Docker container configuration for JupyterHub, designed to furnish a multi-user 
-environment tailored for executing Spark jobs via Jupyter notebooks.
+environment tailored for executing Spark jobs via Jupyter notebooks.
+
+## Using `docker-compose.yaml`
+
+To deploy the JupyterHub container and Spark nodes locally, execute the following command:
+
+```bash
+docker-compose up --build
+```
+
+## Test Submitting a Spark Job Locally
+
+### Submitting a Spark Job via spark-test-node
+```bash
+docker exec -it spark-test-node \
+    sh -c '
+	    /opt/bitnami/spark/bin/spark-submit \
+	    --master spark://spark-master:7077 \
+	    examples/src/main/python/pi.py 10 \
+	    2>/dev/null
+    '
+```
+
+### Submitting a Spark Job via Jupyter Notebook
+After launching the [Jupyter Notebook](http://localhost:4041/), establish a Spark context or session with the Spark 
+master set to the environment variable `SPARK_MASTER_URL` and proceed to submit your job. Once the job is submitted, 
+you can monitor the job status and logs in the [Spark UI](http://localhost:8080/).
+
+Sample code to calculate Pi using `SparkContext`:
+```python
+from pyspark import SparkConf, SparkContext
+import random
+import os
+
+spark_master_url = os.environ['SPARK_MASTER_URL']
+
+conf = SparkConf().setMaster(spark_master_url).setAppName("Pi")
+sc = SparkContext(conf=conf)
+
+num_samples = 100000000
+def inside(p):     
+  x, y = random.random(), random.random()
+  return x*x + y*y < 1
+count = sc.parallelize(range(0, num_samples)).filter(inside).count()
+pi = 4 * count / num_samples
+print(pi)
+sc.stop()
+```
+
+
+

docker-compose.yaml

@@ -0,0 +1,61 @@
+version: '3'
+
+# This docker-compose is for developer convenience, not for running in production.
+
+services:
+
+  spark-master:
+    image: bitnami/spark:3.5.1
+    container_name: spark-master
+    ports:
+      - "8080:8080"
+      - "7077:7077"
+    environment:
+      - SPARK_MODE=master
+      - SPARK_MASTER_WEBUI_PORT=8080
+      - SPARK_MASTER_HOST=0.0.0.0
+
+  spark-worker-1:
+    image: bitnami/spark:3.5.1
+    container_name: spark-worker-1
+    ports:
+      - "8081:8081"
+    environment:
+      - SPARK_MODE=worker
+      - SPARK_MASTER_URL=spark://spark-master:7077
+      - SPARK_WORKER_CORES=2
+      - SPARK_WORKER_MEMORY=1G
+      - SPARK_WORKER_PORT=8091
+      - SPARK_WORKER_WEBUI_PORT=8081
+
+  spark-worker-2:
+    image: bitnami/spark:3.5.1
+    container_name: spark-worker-2
+    ports:
+      - "8082:8082"
+    environment:
+      - SPARK_MODE=worker
+      - SPARK_MASTER_URL=spark://spark-master:7077
+      - SPARK_WORKER_CORES=2
+      - SPARK_WORKER_MEMORY=1G
+      - SPARK_WORKER_PORT=8092
+      - SPARK_WORKER_WEBUI_PORT=8082
+
+  spark-test-node:
+    image: bitnami/spark:3.5.1
+    container_name: spark-test-node
+    environment:
+      - SPARK_MASTER_URL=spark://spark-master:7077
+
+  notebook:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    ports:
+      - "4040:4040"
+      - "4041:4041"
+    depends_on:
+      - spark-master
+    environment:
+      - NOTEBOOK_PORT=4041
+      - SPARK_MASTER_URL=spark://spark-master:7077

scripts/entrypoint.sh

@@ -0,0 +1,16 @@
+#!/bin/bash
+
+echo "starting jupyter notebook"
+
+WORKSPACE_DIR="/cdm_shared_workspace"
+mkdir -p "$WORKSPACE_DIR"
+cd "$WORKSPACE_DIR"
+
+# Start Jupyter Lab
+jupyter lab --ip=0.0.0.0 \
+            --port=$NOTEBOOK_PORT \
+            --no-browser \
+            --allow-root \
+            --notebook-dir="$WORKSPACE_DIR" \
+            --ServerApp.token='' \
+            --ServerApp.password=''