init

.env

@@ -0,0 +1 @@
+AIRFLOW_UID=1000

.gitignore

@@ -0,0 +1 @@
+logs/

airflow.sh

@@ -0,0 +1,39 @@
+#!/usr/bin/env bash
+# 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.
+
+#
+# Run airflow command in container
+#
+
+PROJECT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+
+set -euo pipefail
+
+# check is there a docker-compose command, if not, use "docker compose" instead.
+if [ -x "$(command -v docker-compose)" ]; then
+    dc=docker-compose
+else
+    dc="docker compose"
+fi
+
+export COMPOSE_FILE="${PROJECT_DIR}/docker-compose.yaml"
+if [ $# -gt 0 ]; then
+    exec $dc run --rm airflow-cli "${@}"
+else
+    exec $dc run --rm airflow-cli
+fi

dags/efficiency_auto_simulate.py

@@ -0,0 +1,46 @@
+from airflow import DAG
+from airflow.operators.http_operator import SimpleHttpOperator
+from datetime import datetime, timedelta
+from airflow.utils.dates import days_ago
+
+default_args = {
+    'owner': 'airflow',
+    'depends_on_past': False,
+    'email_on_failure': False,
+    'email_on_retry': False,
+    'retries': 1,
+    'retry_delay': timedelta(minutes=5),
+}
+
+with DAG(
+    'daily_efficiency_api_calls',
+    default_args=default_args,
+    description='Efficiency API calls at specific times',
+    schedule_interval='30 0,8,15 * * *',  # 07:30, 15:30, 22:30 GMT+7
+    start_date=days_ago(1),
+    tags=['api', 'efficiency'],
+) as dag:
+
+    # Morning call at 07:30 GMT+7 (00:30 UTC)
+    morning_api_call = SimpleHttpOperator(
+        task_id='morning_api_call',
+        http_conn_id='efficiency_api',
+        endpoint='efficiency/data/auto',  # No need to include the base URL
+        method='GET',
+    )
+
+    # Afternoon call at 15:30 GMT+7 (08:30 UTC)
+    afternoon_api_call = SimpleHttpOperator(
+        task_id='afternoon_api_call',
+        http_conn_id='efficiency_api',
+        endpoint='efficiency/data/auto',
+        method='GET',
+    )
+
+    # Night call at 22:30 GMT+7 (15:30 UTC)
+    night_api_call = SimpleHttpOperator(
+        task_id='night_api_call',
+        http_conn_id='efficiency_api',
+        endpoint='efficiency/data/auto',
+        method='GET',
+    )

dags/oh_wo_incremental_data.py

@@ -0,0 +1,103 @@
+from datetime import datetime, timedelta
+from airflow import DAG
+from airflow.operators.python import PythonOperator
+from airflow.hooks.postgres_hook import PostgresHook
+import uuid
+import logging
+
+def get_last_processed_id():
+    """Get the maximum source_id from target table"""
+    target_hook = PostgresHook(postgres_conn_id='target_postgres')
+    result = target_hook.get_first("""
+        SELECT MAX(source_id) 
+        FROM oh_wo_master
+    """)
+    return result[0] if result[0] else 0
+
+def incremental_load(**context):
+    """Load incremental data by comparing IDs"""
+    source_hook = PostgresHook(postgres_conn_id='source_postgres')
+    target_hook = PostgresHook(postgres_conn_id='target_postgres')
+    
+    # Get last processed ID
+    last_id = get_last_processed_id()
+    logging.info(f"Last processed ID: {last_id}")
+    
+    # Fetch new records
+    records = source_hook.get_records("""
+        SELECT id, assetnum, worktype, workgroup, total_cost_max, created_at, updated_at
+        FROM dl_wo_staging
+        WHERE id > %s
+        ORDER BY id
+        LIMIT 1000
+    """, parameters=(last_id,))
+    
+    if not records:
+        logging.info("No new records to process")
+        return
+    
+    # Transform and load records
+    target_hook.run("""
+        CREATE TEMP TABLE temp_records (
+            id UUID,
+            source_id BIGSERIAL,
+            worktype VARCHAR(5),
+            workgroup VARCHAR(30),
+	    total_cost_max FLOAT4,
+            created_at TIMESTAMP,
+            updated_at TIMESTAMP
+        ) ON COMMIT DROP
+    """)
+    
+    # Prepare batch insert
+    insert_values = []
+    for record in records:
+        old_id, assetnum, worktype, workgroup, total_cost_max, created_at, updated_at = record
+        new_uuid = uuid.uuid4()
+        insert_values.append(
+            f"('{new_uuid}', {old_id}, '{assetnum}', '{worktype}', '{workgroup}', '{total_cost_max}', '{created_at}', '{updated_at}')"
+        )
+    
+    if insert_values:
+        # Bulk insert into temp table
+        target_hook.run(f"""
+            INSERT INTO temp_records (id, source_id, worktype, workgroup, total_cost_max, created_at, updated_at)
+            VALUES {','.join(insert_values)}
+        """)
+        
+        # Upsert from temp table to target table
+        target_hook.run("""
+            INSERT INTO oh_wo_master (id, source_id, worktype, workgroup, total_cost_max, created_at, updated_at)
+            SELECT id, source_id, worktype, workgroup, total_cost_max, created_at, updated_at
+            FROM temp_records
+            ON CONFLICT (source_id) DO UPDATE
+	    SET worktype = EXCLUDED.worktype,
+    		workgroup = EXCLUDED.workgroup,
+    		total_cost_max = EXCLUDED.total_cost_max,
+    		updated_at = EXCLUDED.updated_at
+        """)
+    
+    processed_count = len(records)
+    logging.info(f"Processed {processed_count} records")
+
+# Create DAG
+default_args = {
+    'owner': 'airflow',
+    'retries': 1,
+    'retry_delay': timedelta(minutes=5),
+}
+
+dag = DAG(
+    'oh_wo_incremental_etl',
+    default_args=default_args,
+    description='Simple incremental ETL using target table as state',
+    schedule_interval='*/15 * * * *',  # Run every 15 minutes
+    start_date=datetime(2024, 1, 1),
+    catchup=False
+)
+
+load_task = PythonOperator(
+    task_id='incremental_load',
+    python_callable=incremental_load,
+    dag=dag
+)

dags/oh_wo_staging.py

@@ -0,0 +1,161 @@
+from datetime import datetime
+from airflow import DAG
+from airflow.operators.python import PythonOperator
+from airflow.hooks.postgres_hook import PostgresHook
+import uuid
+import logging
+from typing import List, Tuple
+
+def get_source_hook():
+    return PostgresHook(postgres_conn_id='source_postgres')
+
+def get_target_hook():
+    return PostgresHook(postgres_conn_id='target_postgres')
+
+def extract_batch(start_id: int, batch_size: int) -> List[Tuple]:
+    """Extract a batch of records from source database"""
+    source_hook = get_source_hook()
+    
+    query = """
+        SELECT id, assetnum, worktype, workgroup, total_cost_max, created_at, updated_at
+        FROM dl_wo_staging
+        WHERE id >= %s
+        AND worktype IN ('PM', 'CM', 'EM', 'PROACTIVE')
+        ORDER BY id
+        LIMIT %s
+    """
+    
+    try:
+        return source_hook.get_records(
+            sql=query,
+            parameters=(start_id, batch_size)
+        )
+    except Exception as e:
+        logging.error(f"Error extracting data: {str(e)}")
+        raise
+
+def get_max_id() -> int:
+    """Get the maximum ID from source table"""
+    source_hook = get_source_hook()
+    try:
+        result = source_hook.get_first(
+            "SELECT MAX(id) FROM dl_wo_staging WHERE worktype IN ('PM', 'CM', 'EM', 'PROACTIVE')"
+        )
+        return result[0] if result and result[0] else 0
+    except Exception as e:
+        logging.error(f"Error getting max ID: {str(e)}")
+        raise
+
+def transform_batch(batch_data: List[Tuple]) -> List[Tuple]:
+    """Transform batch of records"""
+    transformed = []
+    for row in batch_data:
+        try:
+            # Create temporary table for batch processing
+            transformed.append((
+                str(uuid.uuid4()),  # id (UUID)
+                row[0],            # source_id
+                row[1],            # assetnum
+                row[2],            # worktype
+                row[3],            # workgroup
+                row[4],            # total_cost_max
+                row[5],            # created_at
+                row[6]             # updated_at
+            ))
+        except Exception as e:
+            logging.error(f"Error transforming record {row[0]}: {str(e)}")
+            continue
+    return transformed
+
+def load_batch(transformed_data: List[Tuple]) -> None:
+    """Load transformed data into target database using temp table and upsert"""
+    if not transformed_data:
+        return
+        
+    target_hook = get_target_hook()
+    
+    try:
+        # Bulk insert into temp table
+        target_hook.insert_rows(
+            table='oh_wo_master',
+            rows=transformed_data,
+            target_fields=['id', 'source_id', 'assetnum', 'worktype', 'workgroup', 'total_cost_max', 'created_at', 'updated_at']
+        )
+        
+    except Exception as e:
+        logging.error(f"Error loading data: {str(e)}")
+        raise
+
+def process_batch(start_id: int, batch_size: int) -> int:
+    """Process a single batch of records"""
+    logging.info(f"Processing batch starting from ID {start_id}")
+    
+    try:
+        # Extract
+        batch_data = extract_batch(start_id, batch_size)
+        if not batch_data:
+        	return 0
+        last_processed_id = batch_data[-1][0]
+    
+        # Transform
+        transformed_data = transform_batch(batch_data)
+        
+        # Load
+        load_batch(transformed_data)
+        
+        return last_processed_id
+    except Exception as e:
+        logging.error(f"Error processing batch starting at ID {start_id}: {str(e)}")
+        raise
+
+def get_id_range() -> Tuple[int, int]:
+    """Get the minimum and maximum ID from source table"""
+    source_hook = get_source_hook()
+    try:
+        result = source_hook.get_first("""
+            SELECT MIN(id), MAX(id) 
+            FROM dl_wo_staging 
+            WHERE worktype IN ('PM', 'CM', 'EM', 'PROACTIVE')
+        """)
+        return result[0] if result and result[0] else 0, result[1] if result and result[1] else 0
+    except Exception as e:
+        logging.error(f"Error getting ID range: {str(e)}")
+        raise
+
+def etl_process(**context):
+    """Main ETL process with batch processing"""
+    batch_size = 1000
+    min_id, max_id = get_id_range()
+    current_id = min_id
+    total_processed = 0
+    
+    while current_id <= max_id:
+        try:
+            records_processed = process_batch(current_id, batch_size)
+	    
+            if records_processed == 0:
+               break
+    
+            total_processed += 1000
+            current_id = records_processed + 1
+            logging.info(f"Processed {total_processed} records so far")
+        except Exception as e:
+            logging.error(f"Error in batch processing: {str(e)}")
+            raise
+    
+    logging.info(f"ETL complete. Total records processed: {total_processed}")
+
+# DAG definition
+dag = DAG(
+    'wo_staging_historical_data',
+    start_date=datetime(2024, 1, 1),
+    schedule_interval=None,  # Manual trigger for historical data
+    catchup=False,
+    tags=['historical', 'work_order']
+)
+
+etl_task = PythonOperator(
+    task_id='etl_process',
+    python_callable=etl_process,
+    dag=dag
+)

docker-compose.yaml

@@ -0,0 +1,290 @@
+# 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.
+#
+
+# Basic Airflow cluster configuration for CeleryExecutor with Redis and PostgreSQL.
+#
+# WARNING: This configuration is for local development. Do not use it in a production deployment.
+#
+# This configuration supports basic configuration using environment variables or an .env file
+# The following variables are supported:
+#
+# AIRFLOW_IMAGE_NAME           - Docker image name used to run Airflow.
+#                                Default: apache/airflow:2.10.3
+# AIRFLOW_UID                  - User ID in Airflow containers
+#                                Default: 50000
+# AIRFLOW_PROJ_DIR             - Base path to which all the files will be volumed.
+#                                Default: .
+# Those configurations are useful mostly in case of standalone testing/running Airflow in test/try-out mode
+#
+# _AIRFLOW_WWW_USER_USERNAME   - Username for the administrator account (if requested).
+#                                Default: airflow
+# _AIRFLOW_WWW_USER_PASSWORD   - Password for the administrator account (if requested).
+#                                Default: airflow
+# _PIP_ADDITIONAL_REQUIREMENTS - Additional PIP requirements to add when starting all containers.
+#                                Use this option ONLY for quick checks. Installing requirements at container
+#                                startup is done EVERY TIME the service is started.
+#                                A better way is to build a custom image or extend the official image
+#                                as described in https://airflow.apache.org/docs/docker-stack/build.html.
+#                                Default: ''
+#
+# Feel free to modify this file to suit your needs.
+---
+x-airflow-common:
+  &airflow-common
+  # In order to add custom dependencies or upgrade provider packages you can use your extended image.
+  # Comment the image line, place your Dockerfile in the directory where you placed the docker-compose.yaml
+  # and uncomment the "build" line below, Then run `docker-compose build` to build the images.
+  image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.10.3}
+  # build: .
+  environment:
+    &airflow-common-env
+    AIRFLOW__CORE__EXECUTOR: CeleryExecutor
+    AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
+    AIRFLOW__CELERY__RESULT_BACKEND: db+postgresql://airflow:airflow@postgres/airflow
+    AIRFLOW__CELERY__BROKER_URL: redis://:@redis:6379/0
+    AIRFLOW__CORE__FERNET_KEY: ''
+    AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
+    AIRFLOW__CORE__LOAD_EXAMPLES: 'true'
+    AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth,airflow.api.auth.backend.session'
+    # AIRFLOW__WEBSERVER__BASE_URL: 'http://192.168.1.82:8000/airflow'
+    # AIRFLOW__WEBSERVER__ENABLE_PROXY_FIX: True
+    # yamllint disable rule:line-length
+    # Use simple http server on scheduler for health checks
+    # See https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/logging-monitoring/check-health.html#scheduler-health-check-server
+    # yamllint enable rule:line-length
+    AIRFLOW__SCHEDULER__ENABLE_HEALTH_CHECK: 'true'
+    # WARNING: Use _PIP_ADDITIONAL_REQUIREMENTS option ONLY for a quick checks
+    # for other purpose (development, test and especially production usage) build/extend Airflow image.
+    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
+    # The following line can be used to set a custom config file, stored in the local config folder
+    # If you want to use it, outcomment it and replace airflow.cfg with the name of your config file
+    # AIRFLOW_CONFIG: '/opt/airflow/config/airflow.cfg'
+  volumes:
+    - ${AIRFLOW_PROJ_DIR:-.}/dags:/opt/airflow/dags
+    - ${AIRFLOW_PROJ_DIR:-.}/logs:/opt/airflow/logs
+    - ${AIRFLOW_PROJ_DIR:-.}/config:/opt/airflow/config
+    - ${AIRFLOW_PROJ_DIR:-.}/plugins:/opt/airflow/plugins
+  user: "${AIRFLOW_UID:-50000}:0"
+  depends_on:
+    &airflow-common-depends-on
+    redis:
+      condition: service_healthy
+    postgres:
+      condition: service_healthy
+
+services:
+  postgres:
+    image: postgres:13
+    environment:
+      POSTGRES_USER: airflow
+      POSTGRES_PASSWORD: airflow
+      POSTGRES_DB: airflow
+    volumes:
+      - postgres-db-volume:/var/lib/postgresql/data
+    healthcheck:
+      test: ["CMD", "pg_isready", "-U", "airflow"]
+      interval: 10s
+      retries: 5
+      start_period: 5s
+    restart: always
+
+  redis:
+    # Redis is limited to 7.2-bookworm due to licencing change
+    # https://redis.io/blog/redis-adopts-dual-source-available-licensing/
+    image: redis:7.2-bookworm
+    expose:
+      - 6379
+    healthcheck:
+      test: ["CMD", "redis-cli", "ping"]
+      interval: 10s
+      timeout: 30s
+      retries: 50
+      start_period: 30s
+    restart: always
+
+  airflow-webserver:
+    <<: *airflow-common
+    command: webserver
+    ports:
+      - "8080:8080"
+    healthcheck:
+      test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 30s
+    restart: always
+    depends_on:
+      <<: *airflow-common-depends-on
+      airflow-init:
+        condition: service_completed_successfully
+
+  airflow-scheduler:
+    <<: *airflow-common
+    command: scheduler
+    healthcheck:
+      test: ["CMD", "curl", "--fail", "http://localhost:8974/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 30s
+    restart: always
+    depends_on:
+      <<: *airflow-common-depends-on
+      airflow-init:
+        condition: service_completed_successfully
+
+  airflow-worker:
+    <<: *airflow-common
+    command: celery worker
+    healthcheck:
+      # yamllint disable rule:line-length
+      test:
+        - "CMD-SHELL"
+        - 'celery --app airflow.providers.celery.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}" || celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}"'
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 30s
+    environment:
+      <<: *airflow-common-env
+      # Required to handle warm shutdown of the celery workers properly
+      # See https://airflow.apache.org/docs/docker-stack/entrypoint.html#signal-propagation
+      DUMB_INIT_SETSID: "0"
+    restart: always
+    depends_on:
+      <<: *airflow-common-depends-on
+      airflow-init:
+        condition: service_completed_successfully
+
+  airflow-triggerer:
+    <<: *airflow-common
+    command: triggerer
+    healthcheck:
+      test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${HOSTNAME}"']
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 30s
+    restart: always
+    depends_on:
+      <<: *airflow-common-depends-on
+      airflow-init:
+        condition: service_completed_successfully
+
+  airflow-init:
+    <<: *airflow-common
+    entrypoint: /bin/bash
+    # yamllint disable rule:line-length
+    command:
+      - -c
+      - |
+        if [[ -z "${AIRFLOW_UID}" ]]; then
+          echo
+          echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
+          echo "If you are on Linux, you SHOULD follow the instructions below to set "
+          echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
+          echo "For other operating systems you can get rid of the warning with manually created .env file:"
+          echo "    See: https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#setting-the-right-airflow-user"
+          echo
+        fi
+        one_meg=1048576
+        mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) / one_meg))
+        cpus_available=$$(grep -cE 'cpu[0-9]+' /proc/stat)
+        disk_available=$$(df / | tail -1 | awk '{print $$4}')
+        warning_resources="false"
+        if (( mem_available < 4000 )) ; then
+          echo
+          echo -e "\033[1;33mWARNING!!!: Not enough memory available for Docker.\e[0m"
+          echo "At least 4GB of memory required. You have $$(numfmt --to iec $$((mem_available * one_meg)))"
+          echo
+          warning_resources="true"
+        fi
+        if (( cpus_available < 2 )); then
+          echo
+          echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
+          echo "At least 2 CPUs recommended. You have $${cpus_available}"
+          echo
+          warning_resources="true"
+        fi
+        if (( disk_available < one_meg * 10 )); then
+          echo
+          echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for Docker.\e[0m"
+          echo "At least 10 GBs recommended. You have $$(numfmt --to iec $$((disk_available * 1024 )))"
+          echo
+          warning_resources="true"
+        fi
+        if [[ $${warning_resources} == "true" ]]; then
+          echo
+          echo -e "\033[1;33mWARNING!!!: You have not enough resources to run Airflow (see above)!\e[0m"
+          echo "Please follow the instructions to increase amount of resources available:"
+          echo "   https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#before-you-begin"
+          echo
+        fi
+        mkdir -p /sources/logs /sources/dags /sources/plugins
+        chown -R "${AIRFLOW_UID}:0" /sources/{logs,dags,plugins}
+        exec /entrypoint airflow version
+    # yamllint enable rule:line-length
+    environment:
+      <<: *airflow-common-env
+      _AIRFLOW_DB_MIGRATE: 'true'
+      _AIRFLOW_WWW_USER_CREATE: 'true'
+      _AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME:-airflow}
+      _AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
+      _PIP_ADDITIONAL_REQUIREMENTS: ''
+    user: "0:0"
+    volumes:
+      - ${AIRFLOW_PROJ_DIR:-.}:/sources
+
+  airflow-cli:
+    <<: *airflow-common
+    profiles:
+      - debug
+    environment:
+      <<: *airflow-common-env
+      CONNECTION_CHECK_MAX_COUNT: "0"
+    # Workaround for entrypoint issue. See: https://github.com/apache/airflow/issues/16252
+    command:
+      - bash
+      - -c
+      - airflow
+
+  # You can enable flower by adding "--profile flower" option e.g. docker-compose --profile flower up
+  # or by explicitly targeted on the command line e.g. docker-compose up flower.
+  # See: https://docs.docker.com/compose/profiles/
+  flower:
+    <<: *airflow-common
+    command: celery flower
+    profiles:
+      - flower
+    ports:
+      - "5555:5555"
+    healthcheck:
+      test: ["CMD", "curl", "--fail", "http://localhost:5555/"]
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 30s
+    restart: always
+    depends_on:
+      <<: *airflow-common-depends-on
+      airflow-init:
+        condition: service_completed_successfully
+
+volumes:
+  postgres-db-volume: