sparkmagic | Jupyter magics and kernels for working with remote Spark
kandi X-RAY | sparkmagic Summary
kandi X-RAY | sparkmagic Summary
Sparkmagic is a set of tools for interactively working with remote Spark clusters through Livy, a Spark REST server, in Jupyter notebooks. The Sparkmagic project includes a set of magics for interactively running Spark code in multiple languages, as well as some kernels that you can use to turn Jupyter into an integrated Spark environment.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
- Refresh the widget
- Render pie graph
- Gather the values from the dataframe
- Get the x y values of the dataframe
- Extract x and y values from a pandas DataFrame
- Wrap unexpected exceptions
- Execute the SQL statement
- Emits a SQL execution end event
- Send the event to the handler
- Log an event
- Start the session
- Get the list of existing endpoint widgets
- Get existing session widgets
- Render a dataframe
- Decorator to emit an event
- Decorator to configure a function
- This function is called when the user exits
- Load config from file
- Create the endpoint
- Return the version string
- Execute the model
- Display a pandas dataframe
- Create the controls widget
- Get a session by name
- Render a pandas dataframe
- Return the session id for a given client
sparkmagic Key Features
sparkmagic Examples and Code Snippets
Lines of Code : 14License : Permissive (Apache-2.0)
Copy{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "intentionally-put-invalid-action-to-enable-iam-permissions",
"Effect": "Allow",
"Principal": {
"AWS": "*"
},
%pwd
%ls
import os
print(os.getcwd())
import os
import sys
shared_path = '/home/ec2-user/SageMaker/shared'
if shared_path not in sys.path:
sys.path.append(share#!/bin/bash
sudo -u ec2-user -i <<'EOF'
# This will affect only the Jupyter kernel called "conda_python3".
source activate python3
# Replace myPackage with the name of the package you want to install.
pip install pandas==0.25.3
# Y%matplot plt
%sql SELECTDepDelay, ArrDelay FROM flightData
# packages in environment at /home/ubuntu/anaconda3/envs/automl:
from autovizwidget.widget.utils import display_dataframe
display_dataframe(df)
Community Discussions
Trending Discussions on sparkmagic
QUESTION
I've looked at the document above on how to send from local to spark kernel.
However, I've encountered a problem where I have local pandas df fo 60,000 rows but when I try send_to_spark cell magic on this dataframe, only 2500 rows are sent. Is there anyway I can send the whole 60,000 rows without splitting up the df in local ?
I know for sending from spark to local, %%spark -o df -n 60000 will do the job.
...ANSWER
Answered 2021-Apr-13 at 07:25Use %%send_to_spark -i df_sending -t df -n df_sending -m 60000
-i : file I'm sending
-t : type I'm sending
-n : variable name assigned to the file
-m : max number of rows that I will send
use %%help spark cell magic
QUESTION
I'm trying to plot graphs using plotly on EMR Jupyterhub Notebook however the graphs are not being rendered in Pyspark kernel. (Note: Python kernel renders the graph just fine)
Sample code I am trying:
...ANSWER
Answered 2020-Oct-13 at 23:22This is the limitation of sparkmagic. You would have to resort to %%local magic. From sparkmagic docs.
Since all code is run on a remote driver through Livy, all structured data must be serialized to JSON and parsed by the Sparkmagic library so that it can be manipulated and visualized on the client side. In practice this means that you must use Python for client-side data manipulation in %%local mode.
QUESTION
I am trying to update pandas within a lifecycle configuration, and following the example of AWS I have the next code:
...ANSWER
Answered 2020-Feb-10 at 16:30if you want to install the packages only in for the python3 environment, use the following script in your Create Sagemaker Lifecycle configurations.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install sparkmagic
Install the library pip install sparkmagic
Make sure that ipywidgets is properly installed by running jupyter nbextension enable --py --sys-prefix widgetsnbextension
If you're using JupyterLab, you'll need to run another command: jupyter labextension install "@jupyter-widgets/jupyterlab-manager"
(Optional) Install the wrapper kernels. Do pip show sparkmagic and it will show the path where sparkmagic is installed at. cd to that location and do: jupyter-kernelspec install sparkmagic/kernels/sparkkernel jupyter-kernelspec install sparkmagic/kernels/pysparkkernel jupyter-kernelspec install sparkmagic/kernels/sparkrkernel
(Optional) Modify the configuration file at ~/.sparkmagic/config.json. Look at the example_config.json
(Optional) Enable the server extension so that clusters can be programatically changed: jupyter serverextension enable --py sparkmagic
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
