Feat: Onboard dataset Open Buildings (#453)

datasets/open_buildings/infra/open_buildings_dataset.tf

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+/**
+ * Copyright 2022 Google LLC
+ *
+ * Licensed 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.
+ */
+
+
+resource "google_bigquery_dataset" "open_buildings" {
+  dataset_id  = "open_buildings"
+  project     = var.project_id
+  description = "A dataset of building footprints to support social good applications. This large-scale open dataset contains the outlines of buildings derived from high-resolution satellite imagery in order to support these types of uses. The project being based in Ghana, the current focus is on the continent of Africa."
+}
+
+output "bigquery_dataset-open_buildings-dataset_id" {
+  value = google_bigquery_dataset.open_buildings.dataset_id
+}

datasets/open_buildings/infra/provider.tf

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+/**
+ * Copyright 2022 Google LLC
+ *
+ * Licensed 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.
+ */
+
+
+provider "google" {
+  project                     = var.project_id
+  impersonate_service_account = var.impersonating_acct
+  region                      = var.region
+}
+
+data "google_client_openid_userinfo" "me" {}
+
+output "impersonating-account" {
+  value = data.google_client_openid_userinfo.me.email
+}

datasets/open_buildings/infra/variables.tf

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+/**
+ * Copyright 2022 Google LLC
+ *
+ * Licensed 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.
+ */
+
+
+variable "project_id" {}
+variable "bucket_name_prefix" {}
+variable "impersonating_acct" {}
+variable "region" {}
+variable "env" {}
+variable "iam_policies" {
+  default = {}
+}
+

datasets/open_buildings/pipelines/_images/run_script_kub/Dockerfile

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+# Copyright 2021 Google LLC
+#
+# Licensed 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.
+
+# The base image for this build
+FROM python:3.8
+
+# Allow statements and log messages to appear in Cloud logs
+ENV PYTHONUNBUFFERED True
+
+# Copy the requirements file into the image
+COPY requirements.txt ./
+
+# Install the packages specified in the requirements file
+RUN python3 -m pip install --no-cache-dir -r requirements.txt
+
+# The WORKDIR instruction sets the working directory for any RUN, CMD,
+# ENTRYPOINT, COPY and ADD instructions that follow it in the Dockerfile.
+# If the WORKDIR doesn’t exist, it will be created even if it’s not used in
+# any subsequent Dockerfile instruction
+WORKDIR /custom
+
+# Copy the specific data processing script/s in the image under /custom/*
+COPY ./script.py .
+COPY ./schema.json .
+
+# Command to run the data processing script when the container is run
+CMD ["python3", "script.py"]

datasets/open_buildings/pipelines/_images/run_script_kub/requirements.txt

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+requests
+pandas
+google-cloud-storage
+google-cloud-bigquery
+numpy
+

datasets/open_buildings/pipelines/_images/run_script_kub/schema.json

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+[
+	{
+		"name": "latitude",
+		"type": "STRING",
+		"mode": "NULLABLE",
+		"description": "This represents the latitude of the building polygon centroid."
+	},
+	{
+		"name": "longitude",
+		"type": "STRING",
+		"mode": "NULLABLE",
+		"description": "This represents the longitude of the building polygon centroid."
+	},
+	{
+		"name": "area_in_meters",
+		"type": "STRING",
+		"mode": "NULLABLE",
+		"description": "This represents the area in square meters of the polygon."
+	},
+	{
+		"name": "confidence",
+		"type": "STRING",
+		"mode": "NULLABLE",
+		"description": "This represents the confidence score [0.5;1.0] assigned by the model."
+	},
+	{
+		"name": "geometry",
+		"type": "STRING",
+		"mode": "NULLABLE",
+		"description": "This represents the building polygon in the WKT format (POLYGON)."
+	},
+	{
+		"name": "full_plus_code",
+		"type": "STRING",
+		"mode": "NULLABLE",
+		"description": "This represents the full Plus Code(latitude longitude based) at the building polygon centroid."
+	}
+]

datasets/open_buildings/pipelines/_images/run_script_kub/script.py

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+import json
+import logging
+import os
+
+from google.api_core.exceptions import NotFound
+from google.cloud import bigquery, storage
+
+
+def main(source_gcs_path, project_id, dataset_id, gcs_bucket, schema_filepath) -> None:
+    source_file_names = fetch_gcs_file_names(source_gcs_path, gcs_bucket)
+    for each_file in source_file_names:
+        pipeline_name = each_file
+        table_id = each_file[:-4]
+        logging.info(f"Started Extraction and Load process for {pipeline_name} --->")
+        execute_pipeline(
+            source_gcs_path,
+            project_id,
+            dataset_id,
+            gcs_bucket,
+            pipeline_name,
+            table_id,
+            schema_filepath,
+        )
+        logging.info(f"Finished process for {pipeline_name}")
+        print()
+    logging.info("Cleaning up extracted csv files in GCS. Source csv.gz files present.")
+    cleanup(gcs_bucket, source_gcs_path)
+
+
+def fetch_gcs_file_names(source_gcs_path, gcs_bucket):
+    client = storage.Client()
+    blobs = client.list_blobs(gcs_bucket, prefix=source_gcs_path)
+    source_file_names = []
+    for blob in blobs:
+        if blob.name.endswith(".csv"):
+            source_file_names.append(blob.name.split("/")[-1])
+    logging.info(f"{len(source_file_names)} tables to be loaded in bq")
+    return source_file_names
+
+
+def execute_pipeline(
+    source_gcs_path,
+    project_id,
+    dataset_id,
+    gcs_bucket,
+    pipeline_name,
+    table_id,
+    schema_filepath,
+):
+    logging.info(f"ETL started for {pipeline_name}")
+    client = storage.Client()
+    blob = client.list_blobs(gcs_bucket, prefix=source_gcs_path + pipeline_name)
+    if blob:
+        table_exists = create_dest_table(
+            project_id=project_id,
+            dataset_id=dataset_id,
+            table_id=table_id,
+            gcs_bucket=gcs_bucket,
+            schema_filepath=schema_filepath,
+            drop_table=True,
+        )
+        if table_exists:
+            load_data_to_bq(
+                project_id=project_id,
+                dataset_id=dataset_id,
+                table_id=table_id,
+                gcs_bucket=gcs_bucket,
+                source_gcs_path=source_gcs_path,
+                truncate_table=True,
+                field_delimiter="|",
+            )
+        else:
+            error_msg = f"Error: Data was not loaded because the destination table {project_id}.{dataset_id}.{table_id} does not exist and/or could not be created."
+            raise ValueError(error_msg)
+    else:
+        logging.info(f"Informational: The data file {blob} is unavailable")
+
+
+def create_dest_table(
+    project_id: str,
+    dataset_id: str,
+    table_id: str,
+    gcs_bucket: str,
+    schema_filepath: str,
+    drop_table: bool,
+) -> bool:
+    table_ref = f"{project_id}.{dataset_id}.{table_id}"
+    logging.info(f"Attempting to create table {table_ref} if it doesn't already exist")
+    client = bigquery.Client()
+    try:
+        table = client.get_table(table_ref)
+        table_exists_id = table.table_id
+        logging.info(f"Table {table_exists_id} currently exists.")
+        if drop_table:
+            logging.info("Dropping existing table")
+            client.delete_table(table)
+            table = None
+    except NotFound:
+        table = None
+    if not table:
+        logging.info(
+            f"Table {table_ref} currently does not exist.  Attempting to create table."
+        )
+        if schema_filepath:
+            schema = create_table_schema(schema_filepath)
+            table = bigquery.Table(table_ref, schema=schema)
+            client.create_table(table)
+            logging.info(f"Table {table_id} was created")
+            table_exists = True
+        else:
+            logging.info(f"Schema {schema_filepath} file not found")
+            table_exists = False
+    else:
+        table_exists = True
+    return table_exists
+
+
+def create_table_schema(schema_filepath) -> list:
+    logging.info("Defining table schema")
+    schema = []
+    with open(schema_filepath) as f:
+        sc = f.read()
+    schema_struct = json.loads(sc)
+    for schema_field in schema_struct:
+        fld_name = schema_field["name"]
+        fld_type = schema_field["type"]
+        try:
+            fld_descr = schema_field["description"]
+        except KeyError:
+            fld_descr = ""
+        fld_mode = schema_field["mode"]
+        schema.append(
+            bigquery.SchemaField(
+                name=fld_name, field_type=fld_type, mode=fld_mode, description=fld_descr
+            )
+        )
+    return schema
+
+
+def load_data_to_bq(
+    project_id: str,
+    dataset_id: str,
+    table_id: str,
+    gcs_bucket: str,
+    source_gcs_path: str,
+    truncate_table: bool,
+    field_delimiter: str = "|",
+) -> None:
+    logging.info(
+        f"Loading output data from {source_gcs_path} into {project_id}.{dataset_id}.{table_id} ...."
+    )
+    client = bigquery.Client(project=project_id)
+    table_ref = f"{project_id}.{dataset_id}.{table_id}"
+    job_config = bigquery.LoadJobConfig(
+        skip_leading_rows=1, source_format=bigquery.SourceFormat.CSV
+    )
+    job = client.load_table_from_uri(
+        f"gs://{gcs_bucket}/{source_gcs_path}{table_id}.csv",
+        table_ref,
+        job_config=job_config,
+    )
+    logging.info(job.result())
+    logging.info("Loading table completed")
+
+
+def cleanup(gcs_bucket, source_gcs_path):
+    client = storage.Client()
+    pre = client.list_blobs(gcs_bucket, prefix=source_gcs_path)
+    bucket = client.bucket(gcs_bucket)
+    for i in pre:
+        if i.name.endswith(".csv"):
+            delblob = bucket.blob(i.name)
+            delblob.delete()
+
+
+if __name__ == "__main__":
+    logging.getLogger().setLevel(logging.INFO)
+    main(
+        source_gcs_path=os.environ.get("SOURCE_GCS_PATH"),
+        project_id=os.environ.get("PROJECT_ID"),
+        dataset_id=os.environ.get("DATASET_ID"),
+        gcs_bucket=os.environ.get("GCS_BUCKET"),
+        schema_filepath=os.environ.get("SCHEMA_FILEPATH"),
+    )

datasets/open_buildings/pipelines/dataset.yaml

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+# Copyright 2021 Google LLC
+#
+# Licensed 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.
+
+dataset:
+  name: open_buildings
+  friendly_name: Open Buildings
+  description: A dataset of building footprints to support social good applications. This large-scale open dataset contains the outlines of buildings derived from high-resolution satellite imagery in order to support these types of uses. The project being based in Ghana, the current focus is on the continent of Africa.
+  dataset_sources: https://sites.research.google/open-buildings/#download
+  terms_of_use: ~
+
+
+resources:
+  - type: bigquery_dataset
+    dataset_id: open_buildings
+    description: A dataset of building footprints to support social good applications. This large-scale open dataset contains the outlines of buildings derived from high-resolution satellite imagery in order to support these types of uses. The project being based in Ghana, the current focus is on the continent of Africa.