Add DAG for exporting retool data

airflow_variables_dev.json

@@ -315,6 +315,7 @@
   "schema_filepath": "/home/airflow/gcs/dags/schemas/",
   "sentry_dsn": "https://[email protected]/6190849",
   "sentry_environment": "development",
+  "stellar_etl_internal_image_name": "amishastellar/stellar-etl-internal:cd53bcf70",
   "table_ids": {
     "accounts": "accounts",
     "assets": "history_assets",
@@ -329,6 +330,7 @@
     "liquidity_pools": "liquidity_pools",
     "offers": "offers",
     "operations": "history_operations",
+    "retool_entity_data": "retool_entity_data",
     "signers": "account_signers",
     "trades": "history_trades",
     "transactions": "history_transactions",
@@ -349,9 +351,11 @@
     "create_sandbox": 2400,
     "current_state": 720,
     "default": 60,
+    "del_ins_retool_entity_data_task": 720,
     "elementary_dbt_data_quality": 1620,
     "elementary_generate_report": 1200,
     "enriched_history_operations": 780,
+    "export_retool_data": 720,
     "fee_stats": 840,
     "history_assets": 720,
     "liquidity_pool_trade_volume": 1140,

airflow_variables_prod.json

@@ -313,6 +313,7 @@
   "schema_filepath": "/home/airflow/gcs/dags/schemas/",
   "sentry_dsn": "https://[email protected]/5806618",
   "sentry_environment": "production",
+  "stellar_etl_internal_image_name": "amishastellar/stellar-etl-internal:e3b9a2ea7",
   "table_ids": {
     "accounts": "accounts",
     "assets": "history_assets",
@@ -327,6 +328,7 @@
     "liquidity_pools": "liquidity_pools",
     "offers": "offers",
     "operations": "history_operations",
+    "retool_entity_data": "retool_entity_data",
     "signers": "account_signers",
     "trades": "history_trades",
     "transactions": "history_transactions",
@@ -347,9 +349,11 @@
     "create_sandbox": 1020,
     "current_state": 1200,
     "default": 60,
+    "del_ins_retool_entity_data_task": 720,
     "elementary_dbt_data_quality": 2100,
     "elementary_generate_report": 1200,
     "enriched_history_operations": 1800,
+    "export_retool_data": 720,
     "fee_stats": 360,
     "history_assets": 360,
     "liquidity_pool_trade_volume": 1200,

dags/external_data_dag.py

@@ -0,0 +1,81 @@
+"""
+The external_data_dag DAG exports data from external sources.
+It is scheduled to export information to BigQuery at regular intervals.
+"""
+
+from ast import literal_eval
+from datetime import datetime
+from json import loads
+
+from airflow import DAG
+from airflow.configuration import conf
+from airflow.models.variable import Variable
+from airflow.providers.cncf.kubernetes.operators.pod import KubernetesPodOperator
+from kubernetes.client import models as k8s
+from stellar_etl_airflow import macros
+from stellar_etl_airflow.build_del_ins_operator import create_export_del_insert_operator
+from stellar_etl_airflow.build_internal_export_task import build_export_task
+from stellar_etl_airflow.default import get_default_dag_args, init_sentry
+from stellar_etl_airflow.utils import access_secret
+
+init_sentry()
+
+EXTERNAL_DATA_TABLE_NAMES = Variable.get("table_ids", deserialize_json=True)
+EXTERNAL_DATA_PROJECT_NAME = Variable.get("bq_project")
+EXTERNAL_DATA_DATASET_NAME = Variable.get("bq_dataset")
+RETOOL_TABLE_NAME = EXTERNAL_DATA_TABLE_NAMES["retool_entity_data"]
+RETOOL_EXPORT_TASK_ID = "export_retool_data"
+
+# Initialize the DAG
+dag = DAG(
+    "external_data_dag",
+    default_args=get_default_dag_args(),
+    start_date=datetime(2024, 12, 16, 0, 0),
+    description="This DAG exports data from external sources such as retool.",
+    schedule_interval="0 22 * * *",
+    params={
+        "alias": "external",
+    },
+    render_template_as_native_obj=True,
+    user_defined_macros={
+        "subtract_data_interval": macros.subtract_data_interval,
+        "batch_run_date_as_datetime_string": macros.batch_run_date_as_datetime_string,
+    },
+    user_defined_filters={
+        "fromjson": lambda s: loads(s),
+        "container_resources": lambda s: k8s.V1ResourceRequirements(requests=s),
+        "literal_eval": lambda e: literal_eval(e),
+    },
+)
+
+
+retool_export_task = build_export_task(
+    dag,
+    RETOOL_EXPORT_TASK_ID,
+    command="export-retool",
+    cmd_args=[
+        "--start-time",
+        "{{ subtract_data_interval(dag, data_interval_start).isoformat() }}",
+        "--end-time",
+        "{{ subtract_data_interval(dag, data_interval_end).isoformat() }}",
+    ],
+    use_gcs=True,
+    env_vars={
+        "RETOOL_API_KEY": access_secret("retool-api-key", "default"),
+    },
+)
+
+
+retool_insert_to_bq_task = create_export_del_insert_operator(
+    dag,
+    table_name=RETOOL_TABLE_NAME,
+    project=EXTERNAL_DATA_PROJECT_NAME,
+    dataset=EXTERNAL_DATA_DATASET_NAME,
+    export_task_id=RETOOL_EXPORT_TASK_ID,
+    source_object_suffix="",
+    partition=False,
+    cluster=False,
+    table_id=f"{EXTERNAL_DATA_PROJECT_NAME}.{EXTERNAL_DATA_DATASET_NAME}.{RETOOL_TABLE_NAME}",
+)
+
+retool_export_task >> retool_insert_to_bq_task

dags/stellar_etl_airflow/build_del_ins_operator.py

@@ -1,4 +1,8 @@
 from airflow.operators.python import PythonOperator
+from stellar_etl_airflow.build_del_ins_from_gcs_to_bq_task import (
+    build_del_ins_from_gcs_to_bq_task,
+)
+from stellar_etl_airflow.build_internal_export_task import get_airflow_metadata
 from stellar_etl_airflow.default import alert_after_max_retries
 
 
@@ -74,3 +78,41 @@ def create_del_ins_task(dag, task_vars, del_ins_callable):
         on_failure_callback=alert_after_max_retries,
         dag=dag,
     )
+
+
+def create_export_del_insert_operator(
+    dag,
+    table_name: str,
+    project: str,
+    dataset: str,
+    export_task_id: str,
+    source_object_suffix: str,
+    partition: bool,
+    cluster: bool,
+    table_id: str,
+):
+    metadata = get_airflow_metadata()
+    source_objects = [
+        "{{ task_instance.xcom_pull(task_ids='"
+        + export_task_id
+        + '\')["output"] }}'
+        + source_object_suffix
+    ]
+    task_vars = {
+        "task_id": f"del_ins_{table_name}_task",
+        "project": project,
+        "dataset": dataset,
+        "table_name": table_name,
+        "export_task_id": export_task_id,
+        "source_object_suffix": source_object_suffix,
+        "partition": partition,
+        "cluster": cluster,
+        "batch_id": metadata["batch_id"],
+        "batch_date": metadata["batch_date"],
+        "source_objects": source_objects,
+        "table_id": table_id,
+    }
+    insert_to_bq_task = create_del_ins_task(
+        dag, task_vars, build_del_ins_from_gcs_to_bq_task
+    )
+    return insert_to_bq_task

dags/stellar_etl_airflow/build_elementary_slack_alert_task.py

@@ -1,22 +1,12 @@
-import base64
 import logging
 from datetime import timedelta
 
 from airflow.configuration import conf
 from airflow.models import Variable
 from airflow.providers.cncf.kubernetes.operators.pod import KubernetesPodOperator
-from kubernetes import client, config
 from kubernetes.client import models as k8s
 from stellar_etl_airflow.default import alert_after_max_retries
-
-
-def access_secret(secret_name, namespace):
-    config.load_kube_config()
-    v1 = client.CoreV1Api()
-    secret_data = v1.read_namespaced_secret(secret_name, namespace)
-    secret = secret_data.data
-    secret = base64.b64decode(secret["token"]).decode("utf-8")
-    return secret
+from stellar_etl_airflow.utils import access_secret
 
 
 def elementary_task(dag, task_name, command, cmd_args=[], resource_cfg="default"):

dags/stellar_etl_airflow/build_internal_export_task.py

@@ -0,0 +1,108 @@
+"""
+This file contains functions for creating Airflow tasks to run stellar-etl-internal export functions.
+"""
+
+import os
+from datetime import datetime, timedelta
+
+from airflow import DAG
+from airflow.configuration import conf
+from airflow.models.variable import Variable
+from airflow.providers.cncf.kubernetes.operators.pod import KubernetesPodOperator
+from kubernetes.client import models as k8s
+from stellar_etl_airflow import macros
+from stellar_etl_airflow.default import alert_after_max_retries
+
+
+def get_airflow_metadata():
+    return {
+        "batch_insert_ts": datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"),
+        "batch_date": "{{ batch_run_date_as_datetime_string(dag, data_interval_start) }}",
+        "batch_id": macros.get_batch_id(),
+        "run_id": "{{ run_id }}",
+    }
+
+
+def build_export_task(
+    dag,
+    task_name,
+    command,
+    cmd_args=[],
+    env_vars={},
+    use_gcs=False,
+    resource_cfg="default",
+):
+    namespace = conf.get("kubernetes", "NAMESPACE")
+
+    if namespace == "default":
+        config_file_location = Variable.get("kube_config_location")
+        in_cluster = False
+    else:
+        config_file_location = None
+        in_cluster = True
+
+    requests = {
+        "cpu": f"{{{{ var.json.resources.{resource_cfg}.requests.cpu }}}}",
+        "memory": f"{{{{ var.json.resources.{resource_cfg}.requests.memory }}}}",
+    }
+    container_resources = k8s.V1ResourceRequirements(requests=requests)
+
+    image = "{{ var.value.stellar_etl_internal_image_name }}"
+
+    output_filepath = ""
+    if use_gcs:
+        metadata = get_airflow_metadata()
+        batch_insert_ts = metadata["batch_insert_ts"]
+        batch_date = metadata["batch_date"]
+        batch_id = metadata["batch_id"]
+        run_id = metadata["run_id"]
+
+        output_filepath = os.path.join(
+            Variable.get("gcs_exported_object_prefix"),
+            run_id,
+            f"{task_name}-exported-entity.txt",
+        )
+
+        cmd_args = cmd_args + [
+            "--cloud-storage-bucket",
+            Variable.get("gcs_exported_data_bucket_name"),
+            "--cloud-provider",
+            "gcp",
+            "--output",
+            output_filepath,
+            "-u",
+            f"'batch_id={batch_id},batch_run_date={batch_date},batch_insert_ts={batch_insert_ts}'",
+        ]
+    etl_cmd_string = " ".join(cmd_args)
+    arguments = f""" {command} {etl_cmd_string} 1>> stdout.out 2>> stderr.out && cat stdout.out && cat stderr.out && echo "{{\\"output\\": \\"{output_filepath}\\"}}" >> /airflow/xcom/return.json"""
+    env_vars.update(
+        {
+            "EXECUTION_DATE": "{{ ds }}",
+            "AIRFLOW_START_TIMESTAMP": "{{ ti.start_date.strftime('%Y-%m-%dT%H:%M:%SZ') }}",
+        }
+    )
+
+    return KubernetesPodOperator(
+        task_id=task_name,
+        name=task_name,
+        namespace=Variable.get("k8s_namespace"),
+        service_account_name=Variable.get("k8s_service_account"),
+        env_vars=env_vars,
+        image=image,
+        cmds=["bash", "-c"],
+        arguments=[arguments],
+        do_xcom_push=True,
+        dag=dag,
+        is_delete_operator_pod=True,
+        startup_timeout_seconds=720,
+        in_cluster=in_cluster,
+        config_file=config_file_location,
+        container_resources=container_resources,
+        on_failure_callback=alert_after_max_retries,
+        image_pull_policy="IfNotPresent",
+        image_pull_secrets=[k8s.V1LocalObjectReference("private-docker-auth")],
+        sla=timedelta(
+            seconds=Variable.get("task_sla", deserialize_json=True)[task_name]
+        ),
+        trigger_rule="all_done",
+    )

dags/stellar_etl_airflow/utils.py

@@ -1,10 +1,12 @@
+import base64
 import logging
 import re
 import time
 
 from airflow.configuration import conf
 from airflow.models import Variable
 from airflow.utils.state import TaskInstanceState
+from kubernetes import client, config
 
 base_log_folder = conf.get("logging", "base_log_folder")
 
@@ -100,3 +102,12 @@ def skip_retry_dbt_errors(context) -> None:
         return
     else:
         return
+
+
+def access_secret(secret_name, namespace):
+    config.load_kube_config()
+    v1 = client.CoreV1Api()
+    secret_data = v1.read_namespaced_secret(secret_name, namespace)
+    secret = secret_data.data
+    secret = base64.b64decode(secret["token"]).decode("utf-8")
+    return secret