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|
%global _empty_manifest_terminate_build 0
Name: python-sparkmonitor
Version: 2.1.1
Release: 1
Summary: Jupyter Notebook & Lab extension to monitor Apache Spark jobs from a notebook
License: Apache-2.0
URL: https://github.com/swan-cern/sparkmonitor#readme
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/2f/33/df61033427bc0d110cf489cb703e23b78803d4f6ac7ef4000ef59f7300dc/sparkmonitor-2.1.1.tar.gz
BuildArch: noarch
Requires: python3-jupyterlab
%description
## Requirements
- Jupyter Lab 3 OR Jupyter Notebook 4.4.0 or higher
- pyspark 2 or 3
## Features
- Automatically displays a live monitoring tool below cells that run Spark jobs in a Jupyter notebook
- A table of jobs and stages with progressbars
- A timeline which shows jobs, stages, and tasks
- A graph showing number of active tasks & executor cores vs time
<table>
<tr>
<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>
<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>
<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>
</tr>
</table>
## Quick Start
### Setting up the extension
```bash
pip install sparkmonitor # install the extension
# set up an ipython profile and add our kernel extension to it
ipython profile create # if it does not exist
echo "c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')" >> $(ipython profile locate default)/ipython_kernel_config.py
# For use with jupyter notebook install and enable the nbextension
jupyter nbextension install sparkmonitor --py
jupyter nbextension enable sparkmonitor --py
# The jupyterlab extension is automatically enabled
```
With the extension installed, a `SparkConf` object called `conf` will be usable from your notebooks. You can use it as follows:
```python
from pyspark import SparkContext
# Start the spark context using the SparkConf object named `conf` the extension created in your kernel.
sc=SparkContext.getOrCreate(conf=conf)
```
If 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_<scala_version>.jar`
```python
from pyspark.sql import SparkSession
spark = SparkSession.builder\
.config('spark.extraListeners', 'sparkmonitor.listener.JupyterSparkMonitorListener')\
.config('spark.driver.extraClassPath', 'venv/lib/python3.<X>/site-packages/sparkmonitor/listener_<scala_version>.jar')\
.getOrCreate()
```
## Development
If you'd like to develop the extension:
```bash
# See package.json scripts for building the frontend
yarn run build:<action>
# Install the package in editable mode
pip install -e .
# Symlink jupyterlab extension
jupyter labextension develop --overwrite .
# Watch for frontend changes
yarn run watch
# Build the spark JAR files
sbt +package
```
## History
- This project was originally written by krishnan-r as a [Google Summer of Code project](https://github.com/krishnan-r/sparkmonitor) for Jupyter Notebook with the [SWAN](https://swan.web.cern.ch/swan/) Notebook Service team at [CERN](http://home.cern/).
- Further fixes and improvements were made by the team at CERN and members of the community maintained at [swan-cern/jupyter-extensions/tree/master/SparkMonitor](https://github.com/swan-cern/jupyter-extensions/tree/master/SparkMonitor)
- [Jafer Haider](https://github.com/itsjafer) created the fork [jupyterlab-sparkmonitor](https://github.com/itsjafer/jupyterlab-sparkmonitor) to update the extension to be compatible with JupyterLab as part of his internship at Yelp.
- This repository merges all the work done above and provides support for Lab & Notebook from a single package.
## Changelog
This repository is published to pypi as [sparkmonitor](https://pypi.org/project/sparkmonitor/)
- 2.x see the [github releases page](https://github.com/swan-cern/sparkmonitor/releases) of this repository
- 1.x and below were published from [swan-cern/jupyter-extensions](https://github.com/swan-cern/jupyter-extensions) and some initial versions from [krishnan-r/sparkmonitor](https://github.com/krishnan-r/sparkmonitor)
%package -n python3-sparkmonitor
Summary: Jupyter Notebook & Lab extension to monitor Apache Spark jobs from a notebook
Provides: python-sparkmonitor
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-sparkmonitor
## Requirements
- Jupyter Lab 3 OR Jupyter Notebook 4.4.0 or higher
- pyspark 2 or 3
## Features
- Automatically displays a live monitoring tool below cells that run Spark jobs in a Jupyter notebook
- A table of jobs and stages with progressbars
- A timeline which shows jobs, stages, and tasks
- A graph showing number of active tasks & executor cores vs time
<table>
<tr>
<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>
<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>
<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>
</tr>
</table>
## Quick Start
### Setting up the extension
```bash
pip install sparkmonitor # install the extension
# set up an ipython profile and add our kernel extension to it
ipython profile create # if it does not exist
echo "c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')" >> $(ipython profile locate default)/ipython_kernel_config.py
# For use with jupyter notebook install and enable the nbextension
jupyter nbextension install sparkmonitor --py
jupyter nbextension enable sparkmonitor --py
# The jupyterlab extension is automatically enabled
```
With the extension installed, a `SparkConf` object called `conf` will be usable from your notebooks. You can use it as follows:
```python
from pyspark import SparkContext
# Start the spark context using the SparkConf object named `conf` the extension created in your kernel.
sc=SparkContext.getOrCreate(conf=conf)
```
If 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_<scala_version>.jar`
```python
from pyspark.sql import SparkSession
spark = SparkSession.builder\
.config('spark.extraListeners', 'sparkmonitor.listener.JupyterSparkMonitorListener')\
.config('spark.driver.extraClassPath', 'venv/lib/python3.<X>/site-packages/sparkmonitor/listener_<scala_version>.jar')\
.getOrCreate()
```
## Development
If you'd like to develop the extension:
```bash
# See package.json scripts for building the frontend
yarn run build:<action>
# Install the package in editable mode
pip install -e .
# Symlink jupyterlab extension
jupyter labextension develop --overwrite .
# Watch for frontend changes
yarn run watch
# Build the spark JAR files
sbt +package
```
## History
- This project was originally written by krishnan-r as a [Google Summer of Code project](https://github.com/krishnan-r/sparkmonitor) for Jupyter Notebook with the [SWAN](https://swan.web.cern.ch/swan/) Notebook Service team at [CERN](http://home.cern/).
- Further fixes and improvements were made by the team at CERN and members of the community maintained at [swan-cern/jupyter-extensions/tree/master/SparkMonitor](https://github.com/swan-cern/jupyter-extensions/tree/master/SparkMonitor)
- [Jafer Haider](https://github.com/itsjafer) created the fork [jupyterlab-sparkmonitor](https://github.com/itsjafer/jupyterlab-sparkmonitor) to update the extension to be compatible with JupyterLab as part of his internship at Yelp.
- This repository merges all the work done above and provides support for Lab & Notebook from a single package.
## Changelog
This repository is published to pypi as [sparkmonitor](https://pypi.org/project/sparkmonitor/)
- 2.x see the [github releases page](https://github.com/swan-cern/sparkmonitor/releases) of this repository
- 1.x and below were published from [swan-cern/jupyter-extensions](https://github.com/swan-cern/jupyter-extensions) and some initial versions from [krishnan-r/sparkmonitor](https://github.com/krishnan-r/sparkmonitor)
%package help
Summary: Development documents and examples for sparkmonitor
Provides: python3-sparkmonitor-doc
%description help
## Requirements
- Jupyter Lab 3 OR Jupyter Notebook 4.4.0 or higher
- pyspark 2 or 3
## Features
- Automatically displays a live monitoring tool below cells that run Spark jobs in a Jupyter notebook
- A table of jobs and stages with progressbars
- A timeline which shows jobs, stages, and tasks
- A graph showing number of active tasks & executor cores vs time
<table>
<tr>
<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>
<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>
<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>
</tr>
</table>
## Quick Start
### Setting up the extension
```bash
pip install sparkmonitor # install the extension
# set up an ipython profile and add our kernel extension to it
ipython profile create # if it does not exist
echo "c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')" >> $(ipython profile locate default)/ipython_kernel_config.py
# For use with jupyter notebook install and enable the nbextension
jupyter nbextension install sparkmonitor --py
jupyter nbextension enable sparkmonitor --py
# The jupyterlab extension is automatically enabled
```
With the extension installed, a `SparkConf` object called `conf` will be usable from your notebooks. You can use it as follows:
```python
from pyspark import SparkContext
# Start the spark context using the SparkConf object named `conf` the extension created in your kernel.
sc=SparkContext.getOrCreate(conf=conf)
```
If 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_<scala_version>.jar`
```python
from pyspark.sql import SparkSession
spark = SparkSession.builder\
.config('spark.extraListeners', 'sparkmonitor.listener.JupyterSparkMonitorListener')\
.config('spark.driver.extraClassPath', 'venv/lib/python3.<X>/site-packages/sparkmonitor/listener_<scala_version>.jar')\
.getOrCreate()
```
## Development
If you'd like to develop the extension:
```bash
# See package.json scripts for building the frontend
yarn run build:<action>
# Install the package in editable mode
pip install -e .
# Symlink jupyterlab extension
jupyter labextension develop --overwrite .
# Watch for frontend changes
yarn run watch
# Build the spark JAR files
sbt +package
```
## History
- This project was originally written by krishnan-r as a [Google Summer of Code project](https://github.com/krishnan-r/sparkmonitor) for Jupyter Notebook with the [SWAN](https://swan.web.cern.ch/swan/) Notebook Service team at [CERN](http://home.cern/).
- Further fixes and improvements were made by the team at CERN and members of the community maintained at [swan-cern/jupyter-extensions/tree/master/SparkMonitor](https://github.com/swan-cern/jupyter-extensions/tree/master/SparkMonitor)
- [Jafer Haider](https://github.com/itsjafer) created the fork [jupyterlab-sparkmonitor](https://github.com/itsjafer/jupyterlab-sparkmonitor) to update the extension to be compatible with JupyterLab as part of his internship at Yelp.
- This repository merges all the work done above and provides support for Lab & Notebook from a single package.
## Changelog
This repository is published to pypi as [sparkmonitor](https://pypi.org/project/sparkmonitor/)
- 2.x see the [github releases page](https://github.com/swan-cern/sparkmonitor/releases) of this repository
- 1.x and below were published from [swan-cern/jupyter-extensions](https://github.com/swan-cern/jupyter-extensions) and some initial versions from [krishnan-r/sparkmonitor](https://github.com/krishnan-r/sparkmonitor)
%prep
%autosetup -n sparkmonitor-2.1.1
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-sparkmonitor -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 2.1.1-1
- Package Spec generated
|
