derrickaw commented on code in PR #35568: URL: https://github.com/apache/beam/pull/35568#discussion_r2208280492
########## sdks/python/apache_beam/yaml/examples/transforms/ml/taxi-fare/README.md: ########## @@ -0,0 +1,85 @@ +<!-- + Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + regarding copyright ownership. The ASF licenses this file + to you under the Apache License, Version 2.0 (the + "License"); you may not use this file except in compliance + with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, + software distributed under the License is distributed on an + "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + KIND, either express or implied. See the License for the + specific language governing permissions and limitations + under the License. +--> + +## Streaming Taxi Fare Prediction Pipeline + +The example leverages the `RunInference` transform with Vertex AI +model handler [VertexAIModelHandlerJSON]( +https://beam.apache.org/releases/pydoc/current/apache_beam.yaml.yaml_ml#apache_beam.yaml.yaml_ml.VertexAIModelHandlerJSONProvider), +in addition to PubSub, Kafka and BiqQuery IO to demonstrate an end-to-end +example of a streaming ML pipeline predicting NYC taxi fare amounts. + +The data stream of NYC taxi ride events are from the existing public +PubSub topic `projects/pubsub-public-data/topics/taxirides-realtime`. + +For setting up Kafka, an option is to use [Click to Deploy]( +https://console.cloud.google.com/marketplace/details/click-to-deploy-images/kafka?) +to quickly launch a Kafka cluster on GCE. See [existing example here]( +../../../README.md#kafka) for more context around using Kafka with Beam +and Dataflow. + +BigQuery is the pipeline's sink for the inference result output. +A BigQuery dataset needs to exist first before the pipeline can +create/write to a table. Run the following command to create +a BigQuery dataset: + +```sh +bq --location=us-central1 mk \ + --dataset DATASET_ID +``` +See also [here]( +https://cloud.google.com/bigquery/docs/datasets) for more details on +how to create BigQuery datasets + +A trained model hosted on Vertex AI is needed before being able to use +the Vertex AI model handler. To train and deploy a custom model for the +taxi fare prediction problem, open and run this [notebook]( +custom_nyc_taxifare_model_deployment.ipynb) in Colab Enterprise. + +The pipeline first reads the data stream of taxi rides events from the +public PubSub topic and performs some transformations before writing it +to a Kafka topic. The pipeline then reads from that Kafka topic and applies +the necessary transformation logic, before `RunInference` transform performs +remote inference with the Vertex AI model handler and the custom-trained +model deployed to a Vertex AI endpoint. The inference result is then +parsed and written to a BigQuery table. + +Run the pipeline (replace with appropriate variables in the command +below): + +```sh +export PROJECT="$(gcloud config get-value project)" +export TEMP_LOCATION="gs://YOUR-BUCKET/tmp" +export REGION="us-central1" +export JOB_NAME="streaming-taxiride-prediction`date +%Y%m%d-%H%M%S`" +export NUM_WORKERS="3" + +python -m apache_beam.yaml.main \ + --yaml_pipeline_file transforms/ml/taxi-fare/streaming_sentiment_analysis.yaml \ Review Comment: ```suggestion --yaml_pipeline_file transforms/ml/taxi-fare/streaming_taxifare_prediction.yaml \ ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: github-unsubscr...@beam.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
