Challenge Lab Solution

Task - 1 : Run a simple Dataflow job

bq mk lab

gsutil cp gs://cloud-training/gsp323/lab.csv .

cat lab.csv

gsutil cp gs://cloud-training/gsp323/lab.schema .

cat lab.schema


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Task - 2 : Run a simple Dataproc job
This has to be done mannually.


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Task - 3 : Run a simple Dataprep job
This has to be done mannually.

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Task - 4 : AI

gcloud iam service-accounts create my-natlang-sa \
  --display-name "my natural language service account"

gcloud iam service-accounts keys create ~/key.json \
  --iam-account my-natlang-sa@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com

export GOOGLE_APPLICATION_CREDENTIALS="/home/$USER/key.json"

gcloud auth activate-service-account my-natlang-sa@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com --key-file=$GOOGLE_APPLICATION_CREDENTIALS

gcloud ml language analyze-entities --content="Old Norse texts portray Odin as one-eyed and long-bearded, frequently wielding a spear named Gungnir and wearing a cloak and a broad hat." > result.json

gcloud auth login
(Copy the token from the link provided)

gsutil cp result.json gs://YOUR_PROJECT-marking/task4-cnl.result


Create an API key and export as API_KEY variable.

export API_KEY={Replace with API KEY}

nano request.json

Add this content:

{
  "config": {
      "encoding":"FLAC",
      "languageCode": "en-US"
  },
  "audio": {
      "uri":"gs://cloud-training/gsp323/task4.flac"
  }
}

curl -s -X POST -H "Content-Type: application/json" --data-binary @request.json \
"https://speech.googleapis.com/v1/speech:recognize?key=${API_KEY}" > result.json

gsutil cp result.json gs://YOUR_PROJECT-marking/task4-gcs.result

gcloud iam service-accounts create quickstart

gcloud iam service-accounts keys create key.json --iam-account quickstart@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com

gcloud auth activate-service-account --key-file key.json

export ACCESS_TOKEN=$(gcloud auth print-access-token)


nano request.json


Add this content:

{
   "inputUri":"gs://spls/gsp154/video/chicago.mp4",

 "features": [
       "TEXT_DETECTION"
   ]
}


Now add the following commands on the command line:

curl -s -H 'Content-Type: application/json' \
-H "Authorization: Bearer $ACCESS_TOKEN" \
    'https://videointelligence.googleapis.com/v1/videos:annotate' \
    -d @request.json


curl -s -H 'Content-Type: application/json' -H "Authorization: Bearer $ACCESS_TOKEN" 'https://videointelligence.googleapis.com/v1/operations/OPERATION_FROM_PREVIOUS_REQUEST' > result1.json

    gsutil cp result1.json gs://YOUR_PROJECT-marking/task4-gvi.result


Congratulations, you're all done with the lab 😄