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Lab extension to monitor Apache Spark Jobs","homepage":"https://github.com/itsjafer/jupyterlab-sparkmonitor#readme","keywords":["jupyter","jupyterlab","jupyterlab-extension","Spark","sparkmonitor"],"repository":{"type":"git","url":"git+https://github.com/itsjafer/jupyterlab-sparkmonitor.git"},"author":{"name":"Krishnan R"},"bugs":{"url":"https://github.com/itsjafer/jupyterlab-sparkmonitor/issues"},"license":"LGPL-2.1","readme":"# Spark Monitor - An extension for Jupyter Lab\n\nThis project was originally written by krishnan-r as a Google Summer of Code project for Jupyter Notebook. [Check his website out here.](https://krishnan-r.github.io/sparkmonitor/) \n\nAs a part of my internship as a Software Engineer at Yelp, I created this fork to update the extension to be compatible with JupyterLab - Yelp's choice for sharing and collaborating on notebooks.\n\n## About\n\n<table>\n<tr>\n<td><a href=\"http://jupyter.org/\"><img src=\"https://user-images.githubusercontent.com/6822941/29750386-872556fe-8b5c-11e7-95e1-42b12d709017.png\" height=\"50\"/></a></td>\n<td><b>+</b></td>\n<td><a href=\"https://spark.apache.org/\"><img src=\"https://user-images.githubusercontent.com/6822941/29750352-e9807b36-8b5b-11e7-929a-249f56c7cf79.png\" height=\"80\"/></a></td>\n<td><b>=</b></td>\n<td><a href=\"https://user-images.githubusercontent.com/6822941/29601568-d5e42934-87f9-11e7-9780-3cd3a0d8d86b.png\" title=\"The SparkMonitor Extension.\"><img src=\"https://user-images.githubusercontent.com/6822941/29601568-d5e42934-87f9-11e7-9780-3cd3a0d8d86b.png\" height=\"80\"/></a></td>\n</tr>\n</table>\nSparkMonitor is an extension for Jupyter Lab that enables the live monitoring of Apache Spark Jobs spawned from a notebook. The extension provides several features to monitor and debug a Spark job from within the notebook interface itself. <br>\n\n---\n\n![jobdisplay](https://user-images.githubusercontent.com/6822941/29753710-ff8849b6-8b94-11e7-8f9c-bdc59bf72143.gif)\n\n## Features\n\n- Automatically displays a live monitoring tool below cells that run Spark jobs in a Jupyter notebook\n- A table of jobs and stages with progressbars\n- A timeline which shows jobs, stages, and tasks\n- A graph showing number of active tasks & executor cores vs time\n- A notebook server extension that proxies the Spark UI and displays it in an iframe popup for more details\n- For a detailed list of features see the use case [notebooks](https://krishnan-r.github.io/sparkmonitor/#common-use-cases-and-tests)\n- [How it Works](https://krishnan-r.github.io/sparkmonitor/how.html)\n\n<table>\n<tr>\n<td><a href=\"https://user-images.githubusercontent.com/6822941/29601990-d6256a1e-87fb-11e7-94cb-b4418c61d221.png\" title=\"Jobs and stages started from a cell.\"><img src=\"https://user-images.githubusercontent.com/6822941/29601990-d6256a1e-87fb-11e7-94cb-b4418c61d221.png\"></a></td>\n<td><a href=\"https://user-images.githubusercontent.com/6822941/29601769-d8e82a26-87fa-11e7-9b0e-91b1414e7821.png\" title=\"A graph of the number of active tasks and available executor cores.\"><img src=\"https://user-images.githubusercontent.com/6822941/29601769-d8e82a26-87fa-11e7-9b0e-91b1414e7821.png\" ></a></td>\n<td><a href=\"https://user-images.githubusercontent.com/6822941/29601776-d919dae4-87fa-11e7-8939-a6c0d0072d90.png\" title=\"An event timeline with jobs, stages and tasks across various executors. The tasks are split into various coloured phases, providing insight into the nature of computation.\"><img src=\"https://user-images.githubusercontent.com/6822941/29601776-d919dae4-87fa-11e7-8939-a6c0d0072d90.png\"></a></td>\n</tr>\n<tr>\n<td><a href=\"https://user-images.githubusercontent.com/6822941/29750236-be1f6b0c-8b59-11e7-9a36-92e04e3bf05b.png\" title=\"The Spark web UI as a popup within the notebook interface.\"><img src=\"https://user-images.githubusercontent.com/6822941/29750236-be1f6b0c-8b59-11e7-9a36-92e04e3bf05b.png\" ></a></td>\n<td><a href=\"https://user-images.githubusercontent.com/6822941/29750177-ea2c18b8-8b58-11e7-955e-69ecf33a6284.png\" title=\"Details of a task.\"><img src=\"https://user-images.githubusercontent.com/6822941/29750177-ea2c18b8-8b58-11e7-955e-69ecf33a6284.png\" ></a></td>\n<td><a href=\"https://user-images.githubusercontent.com/6822941/29601997-d6533840-87fb-11e7-90ce-daa0fe73b9e5.png\" title=\"An event timeline.\"><img src=\"https://user-images.githubusercontent.com/6822941/29601997-d6533840-87fb-11e7-90ce-daa0fe73b9e5.png\"></a></td>\n</tr>\n</table>\n\n## Quick Start\n\n### To do a quick test of the extension\nThis docker image has pyspark and several other related packages installed alongside the sparkmonitor extension.\n```bash\ndocker run -it -p 8888:8888 itsjafer/sparkmonitor\n```\n\n### Setting up the extension \n```bash\njupyter labextension install jupyterlab_sparkmonitor # install the jupyterlab extension\npip install jupyterlab-sparkmonitor # install the server/kernel extension\njupyter serverextension enable --py sparkmonitor\n\n# set up ipython profile and add our kernel extension to it\nipython profile create --ipython-dir=.ipython\necho \"c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')\" >>  .ipython/profile_default/ipython_config.py\n\n# run jupyter lab\nIPYTHONDIR=.ipython jupyter lab --watch \n```\n\nWith the extension installed, a SparkConf object called `conf` will be usable from your notebooks. You can use it as follows:\n\n```python\nfrom pyspark import SparkContext\n\n# start the spark context using the SparkConf the extension inserted\nsc=SparkContext.getOrCreate(conf=conf) #Start the spark context\n\n# Monitor should spawn under the cell with 4 jobs\nsc.parallelize(range(0,100)).count()\nsc.parallelize(range(0,100)).count()\nsc.parallelize(range(0,100)).count()\nsc.parallelize(range(0,100)).count()\n```\n\nIf you already have your own spark configuration, you will need to set `spark.extraListeners` to `sparkmonitor.listener.JupyterSparkMonitorListener` and `spark.driver.extraClassPath` to the path to the sparkmonitor python package `path/to/package/sparkmonitor/listener.jar`\n```python\nfrom pyspark.sql import SparkSession\nspark = SparkSession.builder\\\n        .config('spark.extraListeners', 'sparkmonitor.listener.JupyterSparkMonitorListener')\\\n        .config('spark.driver.extraClassPath', 'venv/lib/python3.7/site-packages/sparkmonitor/listener.jar')\\\n        .getOrCreate()\n\n# should spawn 4 jobs in a monitor bnelow the cell\nspark.sparkContext.parallelize(range(0,100)).count()\nspark.sparkContext.parallelize(range(0,100)).count()\nspark.sparkContext.parallelize(range(0,100)).count()\nspark.sparkContext.parallelize(range(0,100)).count()\n```\n\n\n## Development\n\nIf you'd like to develop the extension:\n\n```bash\nmake venv # Creates a virtual environment using tox \nsource venv/bin/activate # Make sure we're using the virtual environment\nmake build # Build the extension\nmake develop # Run a local jupyterlab with the extension installed\n```\n","readmeFilename":"README.md"}