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https://issues.apache.org/jira/browse/PIO-192?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Takako Shimamoto updated PIO-192:
---------------------------------
Description:
h3. Summary
Enhance the pypio, which is the Python API for PIO.
h3. Goals
The limitations of the current Python support always force developers to have
access to sbt. This enhancement will get rid of the build phase.
h3. Description
A Python engine has nothing to need. Developers can use the pypio module with
jupyter notebook and Python code.
First, import the necessary modules.
{code:python}
import pypio
{code}
Once the module in imported, the first step is to initialize the pypio module.
{code:python}
# not create App
pypio.init()
# create App (pio app new BHPApp)
pypio.init('BHPApp')
{code}
Next, find data from the event store.
{code:python}
event_df = pypio.find_events('BHPApp')
{code}
And then, save the model.
{code:python}
# model is a PipelineModel, which is produced after a Pipeline’s fit() method
runs
pipeline = Pipeline(...)
model = pipeline.fit(train_df)
engine_instance_id = pypio.save_model(model, ["prediction"])
{code}
h4. Run & Deploy
h5. Run Jupyter
{code:sh}
pio-shell --with-pyspark
{code}
h5. Run on Spark
{code:sh}
pio train --main-py-file xxxx.py
{code}
h5. Deploy App
{code:sh}
pio deploy --engine-instance-id <engine_instance_id>
{code}
was:
h3. Summary
Enhance the pypio, which is the Python API for PIO.
h3. Goals
The limitations of the current Python support always force developers to have
access to sbt. This enhancement will get rid of the build phase.
h3. Description
A Python engine has nothing to need. Developers can use the pypio module with
jupyter notebook and Python code.
First, import the necessary modules.
{code:python}
import pypio
{code}
Once the module in imported, the first step is to initialize the pypio module.
{code:python}
# not create App
pypio.init()
# create App (pio app new BHPApp)
pypio.init('BHPApp')
{code}
Next, find data from the event store.
{code:python}
event_df = pypio.find_events('BHPApp')
{code}
And then, save the model.
{code:python}
# model is a PipelineModel, which is produced after a Pipeline’s fit() method
runs
pipeline = Pipeline(...)
model = pipeline.fit(train_df)
engine_instance_id = pypio.save_model(model, ["prediction"])
{code}
> Enhance PySpark support
> -----------------------
>
> Key: PIO-192
> URL: https://issues.apache.org/jira/browse/PIO-192
> Project: PredictionIO
> Issue Type: Improvement
> Components: Core
> Affects Versions: 0.13.0
> Reporter: Takako Shimamoto
> Assignee: Takako Shimamoto
> Priority: Major
>
> h3. Summary
> Enhance the pypio, which is the Python API for PIO.
> h3. Goals
> The limitations of the current Python support always force developers to have
> access to sbt. This enhancement will get rid of the build phase.
> h3. Description
> A Python engine has nothing to need. Developers can use the pypio module with
> jupyter notebook and Python code.
> First, import the necessary modules.
> {code:python}
> import pypio
> {code}
> Once the module in imported, the first step is to initialize the pypio module.
> {code:python}
> # not create App
> pypio.init()
> # create App (pio app new BHPApp)
> pypio.init('BHPApp')
> {code}
> Next, find data from the event store.
> {code:python}
> event_df = pypio.find_events('BHPApp')
> {code}
> And then, save the model.
> {code:python}
> # model is a PipelineModel, which is produced after a Pipeline’s fit() method
> runs
> pipeline = Pipeline(...)
> model = pipeline.fit(train_df)
> engine_instance_id = pypio.save_model(model, ["prediction"])
> {code}
> h4. Run & Deploy
> h5. Run Jupyter
> {code:sh}
> pio-shell --with-pyspark
> {code}
> h5. Run on Spark
> {code:sh}
> pio train --main-py-file xxxx.py
> {code}
> h5. Deploy App
> {code:sh}
> pio deploy --engine-instance-id <engine_instance_id>
> {code}
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