diff --git a/doc.zih.tu-dresden.de/docs/software/big_data_frameworks_spark.md b/doc.zih.tu-dresden.de/docs/software/big_data_frameworks_spark.md
index 84f5935a168e7d06020b90be011ac314e99f4755..81a66719d20afa05b9bea1dcdf8b7e3175fc18c1 100644
--- a/doc.zih.tu-dresden.de/docs/software/big_data_frameworks_spark.md
+++ b/doc.zih.tu-dresden.de/docs/software/big_data_frameworks_spark.md
@@ -158,46 +158,25 @@ example below:
You can run Jupyter notebooks with Spark on the ZIH systems in a similar way as described on the
[JupyterHub](../access/jupyterhub.md) page.
-### Preparation
-If you want to run Spark in Jupyter notebooks, you have to prepare it first. This is comparable
-to [normal Python virtual environments](../software/python_virtual_environments.md#python-virtual-environment).
-You start with an allocation:
-
-```console
-marie@login$ srun --pty --ntasks=1 --cpus-per-task=2 --mem-per-cpu=2500 --time=01:00:00 bash -l
-```
+### Spawning a Notebook
-When a node is allocated, install the required packages:
+Go to [https://taurus.hrsk.tu-dresden.de/jupyter](https://taurus.hrsk.tu-dresden.de/jupyter).
+In the tab "Advanced", go to the field "Preload modules" and select the following Spark module:
-```console
-marie@compute$ cd $HOME
-marie@compute$ mkdir jupyter-kernel
-marie@compute$ module load Python
-marie@compute$ virtualenv --system-site-packages jupyter-kernel/env #Create virtual environment
-[...]
-marie@compute$ source jupyter-kernel/env/bin/activate #Activate virtual environment.
-(env) marie@compute$ pip install ipykernel
-[...]
-(env) marie@compute$ python -m ipykernel install --user --name haswell-py3.7-spark --display-name="haswell-py3.7-spark"
-Installed kernelspec haswell-py3.7-spark in [...]
-
-(env) marie@compute$ pip install findspark
-(env) marie@compute$ deactivate
+```
+Spark/3.0.1-Hadoop-2.7-Java-1.8-Python-3.7.4-GCCcore-8.3.0
```
-You are now ready to spawn a notebook with Spark.
+When your Jupyter instance is started, you can set up Spark. Since the setup in the notebook
+requires more steps than in an interactive session, we have created an example notebook that you can
+use as a starting point for convenience: [SparkExample.ipynb](misc/SparkExample.ipynb)
-### Spawning a Notebook
+!!! warning
+
+ This notebook only works with the Spark module mentioned above. When using other Spark modules,
+ it is possible that you have to do additional or other steps in order to make Spark running.
-Assuming that you have prepared everything as described above, you can go to
-[https://taurus.hrsk.tu-dresden.de/jupyter](https://taurus.hrsk.tu-dresden.de/jupyter).
-In the tab "Advanced", go to the field "Preload modules" and select one of the Spark modules. When
-your Jupyter instance is started, check whether the kernel that you created in the preparation
-phase (see above) is shown in the top right corner of the notebook. If it is not already selected,
-select the kernel `haswell-py3.7-spark`. Then, you can set up Spark. Since the setup in the
-notebook requires more steps than in an interactive session, we have created an example notebook
-that you can use as a starting point for convenience: [SparkExample.ipynb](misc/SparkExample.ipynb)
!!! note
diff --git a/doc.zih.tu-dresden.de/docs/software/flink.md b/doc.zih.tu-dresden.de/docs/software/flink.md
index 05fb403c2be38cde7a563ac9d86fbb1db7be2522..b20d340fdf810fb508cf2f2714633995321446b3 100644
--- a/doc.zih.tu-dresden.de/docs/software/flink.md
+++ b/doc.zih.tu-dresden.de/docs/software/flink.md
@@ -158,6 +158,39 @@ example below:
[workspaces](../data_lifecycle/workspaces.md) for your study and work projects**. For this
reason, you have to use advanced options of Jupyterhub and put "/" in "Workspace scope" field.
+
+## Jupyter Notebook
+
+You can run Jupyter notebooks with Flink on the ZIH systems in a similar way as described on the
+[JupyterHub](../access/jupyterhub.md) page.
+
+
+### Spawning a Notebook
+
+Go to [https://taurus.hrsk.tu-dresden.de/jupyter](https://taurus.hrsk.tu-dresden.de/jupyter).
+In the tab "Advanced", go to the field "Preload modules" and select the following Flink module:
+
+```
+Flink/1.12.3-Java-1.8.0_161-OpenJDK-Python-3.7.4-GCCcore-8.3.0
+```
+
+When your Jupyter instance is started, you can set up Flink. Since the setup in the notebook
+requires more steps than in an interactive session, we have created an example notebook that you can
+use as a starting point for convenience: [FlinkExample.ipynb](misc/FlinkExample.ipynb)
+
+!!! warning
+
+ This notebook only works with the Flink module mentioned above. When using other Flink modules,
+ it is possible that you have to do additional or other steps in order to make Flink running.
+
+!!! note
+
+ You could work with simple examples in your home directory, but, according to the
+ [storage concept](../data_lifecycle/overview.md), **please use
+ [workspaces](../data_lifecycle/workspaces.md) for your study and work projects**. For this
+ reason, you have to use advanced options of Jupyterhub and put "/" in "Workspace scope" field.
+
+
## FAQ
Q: Command `source framework-configure.sh hadoop
diff --git a/doc.zih.tu-dresden.de/docs/software/misc/FlinkExample.ipynb b/doc.zih.tu-dresden.de/docs/software/misc/FlinkExample.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..5a867b8750704ea92a318087d82bb0ca3355018d
--- /dev/null
+++ b/doc.zih.tu-dresden.de/docs/software/misc/FlinkExample.ipynb
@@ -0,0 +1,159 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "!{sys.executable} -m pip install apache-flink --user"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%%bash\n",
+ "echo $FLINK_ROOT_DIR\n",
+ "echo $JAVA_HOME\n",
+ "hostname\n",
+ "if [ ! -d $HOME/jupyter-flink-conf ]\n",
+ "then\n",
+ "cp -r $FLINK_ROOT_DIR/conf $HOME/jupyter-flink-conf\n",
+ "chmod -R u+w $HOME/jupyter-flink-conf\n",
+ "fi"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "import os\n",
+ "os.environ['FLINK_CONF_DIR'] = os.environ['HOME'] + '/cluster-conf-' + os.environ['SLURM_JOBID'] + '/flink'\n",
+ "os.environ['PYTHONPATH'] = os.environ['PYTHONPATH'] + ':' + os.environ['HOME'] + '/.local/lib/python3.6/site-packages'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!SHELL=/bin/bash bash framework-configure.sh flink $HOME/jupyter-flink-conf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "exitcode = os.system('start-cluster.sh')\n",
+ "if not exitcode:\n",
+ " print(\"started Flink cluster successful\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%%bash\n",
+ "echo \"This is a short story for you. In this story nothing is happening. Have a nice day!\" > myFlinkTestFile"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from pyflink.datastream import StreamExecutionEnvironment\n",
+ "from pyflink.datastream.connectors import FileSource\n",
+ "from pyflink.datastream.connectors import StreamFormat\n",
+ "from pyflink.common.watermark_strategy import WatermarkStrategy\n",
+ "from pyflink.common.typeinfo import Types\n",
+ "\n",
+ "env = StreamExecutionEnvironment.get_execution_environment()\n",
+ "env.set_parallelism(2)\n",
+ "#set the Python executable for the workers\n",
+ "env.set_python_executable(sys.executable)\n",
+ "# define the source\n",
+ "ds = env.from_source(source=FileSource.for_record_stream_format(StreamFormat.text_line_format(),\n",
+ " \"myFlinkTestFile\").process_static_file_set().build(),\n",
+ " watermark_strategy=WatermarkStrategy.for_monotonous_timestamps(),\n",
+ " source_name=\"file_source\")\n",
+ "\n",
+ "def split(line):\n",
+ " yield from line.split()\n",
+ "\n",
+ " \n",
+ "# compute word count\n",
+ "ds = ds.flat_map(split) \\\n",
+ " .map(lambda i: (i, 1), output_type=Types.TUPLE([Types.STRING(), Types.INT()])) \\\n",
+ " .key_by(lambda i: i[0]) \\\n",
+ " .reduce(lambda i, j: (i[0], i[1] + j[1])) \\\n",
+ " .map(lambda i: print(i))\n",
+ "\n",
+ "# submit for execution\n",
+ "env.execute()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%%bash\n",
+ "stop-cluster.sh"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!ps -ef | grep -i java"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!pkill -f \"java\""
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc.zih.tu-dresden.de/docs/software/misc/SparkExample.ipynb b/doc.zih.tu-dresden.de/docs/software/misc/SparkExample.ipynb
index 67eb37e898667946a0a6dbdf60bc104908e12601..959b536b85dd3d5d01c79217b697506a7517d4f3 100644
--- a/doc.zih.tu-dresden.de/docs/software/misc/SparkExample.ipynb
+++ b/doc.zih.tu-dresden.de/docs/software/misc/SparkExample.ipynb
@@ -1,5 +1,24 @@
{
"cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "!{sys.executable} -m pip install findspark --user"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!which python"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -27,7 +46,8 @@
"import sys\n",
"import os\n",
"os.environ['PYSPARK_PYTHON'] = sys.executable\n",
- "os.environ['SPARK_CONF_DIR'] = os.environ['HOME'] + '/cluster-conf-' + os.environ['SLURM_JOBID'] + '/spark'"
+ "os.environ['SPARK_CONF_DIR'] = os.environ['HOME'] + '/cluster-conf-' + os.environ['SLURM_JOBID'] + '/spark'\n",
+ "os.environ['PYTHONPATH'] = os.environ['PYTHONPATH'] + ':' + os.environ['HOME'] + '/.local/lib/python3.6/site-packages'"
]
},
{
@@ -48,6 +68,16 @@
"!start-all.sh"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import findspark\n",
+ "findspark.init(os.environ['SPARK_HOME'])"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -116,20 +146,13 @@
"source": [
"!pkill -f \"pyspark-shell\""
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
}
],
"metadata": {
"kernelspec": {
- "display_name": "haswell-py3.7-spark",
+ "display_name": "Python 3",
"language": "python",
- "name": "haswell-py3.7-spark"
+ "name": "python3"
},
"language_info": {
"codemirror_mode": {
@@ -141,7 +164,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.4"
+ "version": "3.6.10"
}
},
"nbformat": 4,