merlin-batch-predictor 0.49.0

Base PySpark application for running Merlin prediction batch job

Merlin Batch Predictor

Merlin Batch Predictor is a PySpark application for running batch prediction job in Merlin system.

Usage

The application accept a yaml file for configuring source, model, and sink of the prediction job. The schema of the configuration file is described by the proto file. An example of the config file is as follow.

kind: PredictionJob
version: v1
name: integration-test
bigquerySource:
  table: "project.dataset.table_iris"
  features:
    - sepal_length
    - sepal_width
    - petal_length
    - petal_width
model:
  type: PYFUNC_V2
  uri: gs://bucket-name/e2e/artifacts/model
  result:
    type: DOUBLE
bigquerySink:
  table: "project.dataset.table_iris_result"
  result_column: "prediction"
  save_mode: OVERWRITE
  options:
    project: "project"
    temporaryGcsBucket: "bucket-name"

The above prediction job specification will read data from bigquery-public-data:samples.shakespeare Bigquery table, run prediction using a PYFUNC_V2 model located at gs://bucket-name/mlflow/6/2c3703fbbf9f4866b26e4cf91641f02c/artifacts/model GCS bucket, and write the result to another bigquery table project.dataset.table.

To start the application locally you need:

• Set GOOGLE_APPLICATION_CREDENTIALS environment variable and point it to the service account which has following privileges:
  1. Storage Writer for the temporaryGcsBucket
  2. Storage Object Writer for temporaryGcsBucket
  3. BigQuery Job User
  4. BigQuery Read Session User
  5. BigQuery Data Reader from the source dataset
  6. BigQuery Data Editor for the destination dataset

Then you can invoke

python main.py --job-name <job-name> --spec-path <path-to-spec-yaml> --local

In mac OS you need to set OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES

OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES python main.py --job-name <job-name> --spec-path <path-to-spec-yaml> --local

For example

OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES python main.py --job-name iris-prediction --spec-path sample/sample_1.yaml --local

Development

Requirements

• python >= 3.9.0
• pipenv (install using pip install pipenv)
• protoc (see installation instruction)
• gcloud (see installation instruction)
• docker (see installation instruction)

Setup Dev Dependencies

make setup

Run all test

You need to set GOOGLE_APPLICATION_CREDENTIALS and point it to service account file which has following privileges:

1. BigQuery Job User
2. BigQuery Read Session User
3. BigQuery Data Editor for dataset project:dataset
4. Storage Writer for bucket-name bucket
5. Storage Object Writer for bucket-name bucket

make test

Run only unit test

make unit-test