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From Pat Ferrel <>
Subject Re: PIO 0.12.0 on cloud server: ImportError: No module named predictionio
Date Tue, 24 Oct 2017 15:19:57 GMT
Ok, you said, "the UR's handmade's integration test I got the following error message” so
naturally assumed,

On Oct 24, 2017, at 12:36 AM, Noelia Osés Fernández <> wrote:

Hi Donald and Pat,

I'm following the installation instructions at
<> Thank you for
your help!

Pat, I believe randomly generates the data for the E-Commerce Recommendation
Template, so I'm not using the UR test data with it. Thanks for the tip! Looking forward to
the UR release.

Best regards,

On 23 October 2017 at 17:28, Donald Szeto < <>>
Hi Noelia,

Looks like the instructions you are following is missing the step to install the `predictionio`
Python client. If you can point us to the material you are following we can fix it.

For now please do `pip install predictionio`.


On Mon, Oct 23, 2017 at 7:50 AM Noelia Osés Fernández < <>>
Hi all,

I have made a clean installation of Prediction IO 0.12.0 on a cloud server following all the
installation defaults. The installation seemed to go well and pio status reported no errors.
However, when I ran the UR's handmade's integration test I got the following error message:

Checking status, should exit if pio is not running.
[INFO] [Management$] Inspecting PredictionIO...
[INFO] [Management$] PredictionIO 0.12.0-incubating is installed at /home/ubuntu/PredictionIO/apache-predictionio-0.12.0-incubating/PredictionIO-0.12.0-incubating
[INFO] [Management$] Inspecting Apache Spark...
[INFO] [Management$] Apache Spark is installed at /home/ubuntu/PredictionIO/apache-predictionio-0.12.0-incubating/PredictionIO-0.12.0-incubating/vendors/spark-2.1.1-bin-hadoop2.6
[INFO] [Management$] Apache Spark 2.1.1 detected (meets minimum requirement of 1.3.0)
[INFO] [Management$] Inspecting storage backend connections...
[INFO] [Storage$] Verifying Meta Data Backend (Source: ELASTICSEARCH)...
[INFO] [Storage$] Verifying Model Data Backend (Source: LOCALFS)...
[INFO] [Storage$] Verifying Event Data Backend (Source: HBASE)...
[INFO] [Storage$] Test writing to Event Store (App Id 0)...
[INFO] [HBLEvents] The table pio_event:events_0 doesn't exist yet. Creating now...
[INFO] [HBLEvents] Removing table pio_event:events_0...
[INFO] [Management$] Your system is all ready to go.
[ERROR] [App$] App handmade already exists. Aborting.

Checking to see if handmade app exists, should exit if not.
[INFO] [Pio$]     App Name: handmade
[INFO] [Pio$]       App ID: 1
[INFO] [Pio$]  Description: 
[INFO] [Pio$]   Access Key: HLc0UgUVbRsxRjwhXuT1s_TFfdtU7JE66_J7Ro0a31BtJo4Guf-HbYhwDTZMPbKv
| (all)

Moving engine.json to user-engine.json if it exists

Moving examples/handmade-engine.json to engine.json for integration test.

Deleting handmade app data since the test is date dependent
[INFO] [Pio$] Data of the following app (default channel only) will be deleted. Are you sure?
[INFO] [Pio$]     App Name: handmade
[INFO] [Pio$]       App ID: 1
[INFO] [Pio$]  Description: None
[INFO] [HBLEvents] Removing table pio_event:events_1...
[INFO] [App$] Removed Event Store for the app ID: 1
[INFO] [HBLEvents] The table pio_event:events_1 doesn't exist yet. Creating now...
[INFO] [App$] Initialized Event Store for the app ID: 1

Importing data for integration test
Access key: HLc0XgUWbRsxRjwhYuT1s_TDfdtU7AE66_J7Ro0a31BtJo4Guf-HbYhwDTZMPbKv
Traceback (most recent call last):
  File "examples/", line 5, in <module>
    import predictionio
ImportError: No module named predictionio

As the github repo doesn't mention that UR has been upgraded to work with PIO 0.12.0, I have
also tried with the E-Commerce Recommendation Template (
<>) which
explicitly mentions it has been upgraded to keep up with PIO 0.12.0. However, I have run into
the same error message when importing the data using python.

I would very much appreciate any pointers that help me solve this problem.
Thank you!


Noelia Osés Fernández, PhD
Senior Researcher |
Investigadora Senior <>
+[34] 943 30 92 30
Data Intelligence for Energy and
Industrial Processes | Inteligencia
de Datos para Energía y Procesos

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