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| volumes = [{ | |
| "name": "input_data", | |
| "persistentVolumeClaim": {"claimName": 'my_pvc'} | |
| }] | |
| volume_mounts = [{ | |
| "name": "input_data", | |
| "mountPath": "/data" | |
| }] | |
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| def prep_data(input_param): | |
| # TO BE IMPLEMENTED | |
| def train_model(input_param): | |
| # TO BE IMPLEMENTED |
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| import pandas as pd | |
| def prep_data(input_param): | |
| df = pd.read_parquet(input_param['input_data'] | |
| return df | |
| def train_model(input_param): | |
| # TO BE IMPLEMENTED | |
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| import pandas as pd | |
| def prep_data(input_param): | |
| df = pd.read_parquet(input_param['input_data'] | |
| return df | |
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| # The library for responding feature branch and developer, | |
| # avoid conflict in case other people using the same Databricks cluster | |
| # but working on other feature branch | |
| dbutils.library.install("dbfs:/path/to/<feature_brach_name>/<developer_id>/library.egg") | |
| # Removes Python state, but some libraries might not work without calling this function | |
| dbutils.library.restartPython() |
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| [Unit] | |
| Description=Jupyter Notebook | |
| [Service] | |
| Type=simple | |
| PIDFile=/run/jupyter.pid | |
| # Step 1 and Step 2 details are here.. | |
| # ------------------------------------ | |
| #Note: `workon tf` is to switch to tf virtualenv where i have jupyter installed | |
| ExecStart=/bin/bash -c 'cd /home/keven/notebooks && source /home/keven/.profile && workon tf && jupyter notebook' |
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| import org.apache.spark.SparkContext | |
| import org.apache.spark.SparkContext._ | |
| import org.apache.spark.SparkConf | |
| import org.apache.spark.sql._ | |
| import org.apache.spark.sql.types._ | |
| /* We use this to pass configuration properties to Vertica and CoreNLP */ | |
| import java.util.{Properties, UUID} |
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| #!/bin/sh | |
| set -e | |
| # | |
| # This script is meant for quick & easy install via: | |
| # 'curl -sSL https://get.docker.com/ | sh' | |
| # or: | |
| # 'wget -qO- https://get.docker.com/ | sh' | |
| # | |
| # For test builds (ie. release candidates): | |
| # 'curl -fsSL https://test.docker.com/ | sh' |
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| #!/bin/bash | |
| # play YUV444 FULL HD file | |
| gst-launch-1.0 -v filesrc location=size_1920x1080.yuv ! \ | |
| videoparse width=1920 height=1080 framerate=25/1 format=GST_VIDEO_FORMAT_Y444 ! \ | |
| videoconvert ! \ | |
| autovideosink | |
| # play YUV422 FULL HD file | |
| gst-launch-1.0 -v filesrc location=size_1920x1080.yuv ! \ |