issues Search Results · repo:aws/sagemaker-sparkml-serving-container language:Java
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inaws/sagemaker-sparkml-serving-container (press backspace or delete to remove)Hi
We re looking to use Spark ml pipelines in realtime inference and deploying in Sagemaker. Assume this is our only option
- that correct?
I can still see it referenced by official Sagemaker docs eg. ...
wandrar
- Opened on Feb 25
- #47
Hi, I am trying to build the docker image in this repository, and the build fails at - Step 6/20 : RUN apt -y install
python3.6 Due to compliance and security restrictions at my organization, we cannot ...
mabel91
- 1
- Opened on Sep 16, 2021
- #25
Hi! How can this container be used for batch transfrom in sagemaker. Because my env variable holds schema for 561
columns which is very long. to pass as env variable. I was following this tutorial
https://sagemaker-examples.readthedocs.io/en/latest/sagemaker-python-sdk/sparkml_serving_emr_mleap_abalone/sparkml_serving_emr_mleap_abalone.html ...
hafsahabib-educator
- Opened on Nov 1, 2020
- #18
Hi,
I was referring to this repo to build a custom docker image that does the feature transformation and use lightGBM model
for prediction.
I wanted to use mleap to serialize my feature transformation ...
prasadpande1990
- Opened on Sep 15, 2020
- #17
After deploying mleap model artifact on sagemaker endpoint, during the inferencing stage, how can I get probabilities of
prediction rather than binary outcome? I tried changing output column from prediction ...
janvekarnaveed
- 2
- Opened on Jun 5, 2020
- #13
Hello, I would like to understand why this limitation is in place. Presumably most machine learning models take in much
more than 16 features.
I created a model and had over 100 features. I tried to pass ...
rchazelle
- 4
- Opened on May 16, 2020
- #12
Hello, is there a plan to upgrade the sparkml serving containers to support pipeline models generated using Spark 2.4.3
and serialized using Mleap 0.14.0. Greatly appreciate if some could please share ...
sajjap
- 1
- Opened on Nov 13, 2019
- #10
I am trying to create Pipeline model that combines the SparkML model with the BlazingText model for a text
classification task. The SparkML model is used to pre-process the input texts. I configured SparkML ...
vincentnqt
- 5
- Opened on Aug 16, 2019
- #6
I am trying to deploy bundled a Spark ML NaiveBayesModel with sagemaker-sparkml-serving-container.
I am running sagemaker-sparkml-serving-container with following command:
SCHEMA= { input :[{ name : ...
make
- 7
- Opened on Nov 30, 2018
- #3
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