[
https://issues.apache.org/jira/browse/PIO-192?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16681716#comment-16681716
]
Wei Chen commented on PIO-192:
------------------------------
Hello [~shimamoto], just a question.
Since we are doing the restructuring, are we looking for providing functions to
deploy prediction service:
{code:python}
pypio.deploy(model)
{code}
Also, should we allow users to create new apps in the notebook?
{code:python}
pypio.newApp("myApp1")
{code}
So users can have complete control just by using the notebook.
Doing so will make Jupiter notebook a control center for experiments, which I
think we should also take into consideration before settling the new
architecture.
> 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 template requires 3 files:
> * Python code to specify for the --main-py-file option
> * template.json
> {code:json}
> {"pio": {"version": { "min": "0.14.0-SNAPSHOT" }}}
> {code}
> * engine.json
> {code:json}
> {
> "id": "default",
> "description": "Default settings",
> "engineFactory": "org.apache.predictionio.e2.engine.PythonEngine",
> "algorithms": [
> {
> "name": "default",
> "params": {
> "name": "BHPApp"
> }
> }
> ],
> "serving": {
> "params": {
> "columns": ["prediction"]
> }
> }
> }
> {code}
> h4. pypio module
> Developers can use the pypio module with jupyter notebook and Python code.
> First, import the necessary modules.
> {code:python}
> from pypio import pypio
> {code}
> Once the module in imported, the first step is to initialize the pypio module.
> {code:python}
> pypio.init()
> {code}
> Next, find data from the event store.
> {code:python}
> event_df = pypio.find('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)
> pypio.save(model)
> {code}
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
