Pada 15 September 2026, semua lingkungan Cloud Composer 1 dan Cloud Composer 2 versi 2.0.x akan mencapai akhir masa pakainya yang direncanakan, dan Anda tidak akan dapat menggunakannya. Sebaiknya rencanakan migrasi ke Cloud Composer 3.
Halaman ini menjelaskan cara mengelompokkan tugas di pipeline Airflow
menggunakan pola desain berikut:
Mengelompokkan tugas dalam grafik DAG.
Memicu DAG turunan dari DAG induk.
Mengelompokkan tugas dengan operator TaskGroup.
Mengelompokkan tugas dalam grafik DAG
Untuk mengelompokkan tugas dalam fase tertentu di pipeline, Anda dapat menggunakan hubungan
antar-tugas dalam file DAG.
Perhatikan contoh berikut:
Gambar 1. Tugas dapat dikelompokkan dalam DAG Airflow (klik untuk memperbesar)
Dalam alur kerja ini, tugas op-1 dan op-2 berjalan bersama setelah tugas
awal start. Anda dapat melakukannya dengan mengelompokkan tugas menggunakan pernyataan
start >> [task_1, task_2].
Contoh berikut memberikan penerapan lengkap DAG ini:
fromairflowimportDAGfromairflow.operators.bashimportBashOperatorfromairflow.operators.dummyimportDummyOperatorfromairflow.utils.datesimportdays_agoDAG_NAME="all_tasks_in_one_dag"args={"owner":"airflow","start_date":days_ago(1),"schedule_interval":"@once"}withDAG(dag_id=DAG_NAME,default_args=args)asdag:start=DummyOperator(task_id="start")task_1=BashOperator(task_id="op-1",bash_command=":",dag=dag)task_2=BashOperator(task_id="op-2",bash_command=":",dag=dag)some_other_task=DummyOperator(task_id="some-other-task")task_3=BashOperator(task_id="op-3",bash_command=":",dag=dag)task_4=BashOperator(task_id="op-4",bash_command=":",dag=dag)end=DummyOperator(task_id="end")start >> [task_1,task_2] >> some_other_task >> [task_3,task_4] >> end
Gambar 2. DAG dapat dipicu dari dalam DAG dengan
TriggerDagRunOperator (klik untuk memperbesar)
Dalam alur kerja ini, blok dag_1 dan dag_2 merepresentasikan serangkaian tugas
yang dikelompokkan bersama dalam DAG terpisah di lingkungan Cloud Composer.
Penerapan alur kerja ini memerlukan dua file DAG terpisah.
File DAG pengendali akan terlihat seperti berikut:
fromairflowimportDAGfromairflow.operators.dummyimportDummyOperatorfromairflow.operators.trigger_dagrunimportTriggerDagRunOperatorfromairflow.utils.datesimportdays_agowithDAG(dag_id="controller_dag_to_trigger_other_dags",default_args={"owner":"airflow"},start_date=days_ago(1),schedule_interval="@once",)asdag:start=DummyOperator(task_id="start")trigger_1=TriggerDagRunOperator(task_id="dag_1",trigger_dag_id="dag-to-trigger",# Ensure this equals the dag_id of the DAG to triggerconf={"message":"Hello World"},)trigger_2=TriggerDagRunOperator(task_id="dag_2",trigger_dag_id="dag-to-trigger",# Ensure this equals the dag_id of the DAG to triggerconf={"message":"Hello World"},)some_other_task=DummyOperator(task_id="some-other-task")end=DummyOperator(task_id="end")start >> trigger_1 >> some_other_task >> trigger_2 >> end
Implementasi DAG turunan, yang dipicu oleh DAG
pengontrol, akan terlihat seperti berikut:
Anda dapat menggunakan
operator TaskGroup untuk mengelompokkan tugas
bersama-sama dalam DAG. Tugas yang ditentukan dalam blok TaskGroup masih menjadi bagian
dari DAG utama.
Perhatikan contoh berikut:
Gambar 3. Tugas dapat dikelompokkan secara visual di
UI dengan operator TaskGroup (klik untuk memperbesar)
Tugas op-1 dan op-2 dikelompokkan bersama dalam blok dengan ID
taskgroup_1. Penerapan alur kerja ini terlihat seperti kode berikut:
fromairflow.models.dagimportDAGfromairflow.operators.bashimportBashOperatorfromairflow.operators.dummyimportDummyOperatorfromairflow.utils.datesimportdays_agofromairflow.utils.task_groupimportTaskGroupwithDAG(dag_id="taskgroup_example",start_date=days_ago(1))asdag:start=DummyOperator(task_id="start")withTaskGroup("taskgroup_1",tooltip="task group #1")assection_1:task_1=BashOperator(task_id="op-1",bash_command=":")task_2=BashOperator(task_id="op-2",bash_command=":")withTaskGroup("taskgroup_2",tooltip="task group #2")assection_2:task_3=BashOperator(task_id="op-3",bash_command=":")task_4=BashOperator(task_id="op-4",bash_command=":")some_other_task=DummyOperator(task_id="some-other-task")end=DummyOperator(task_id="end")start >> section_1 >> some_other_task >> section_2 >> end
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-26 UTC."],[[["\u003cp\u003eThis document outlines methods for grouping tasks within Airflow pipelines, covering approaches like structuring relationships in the DAG graph, triggering child DAGs from a parent DAG, and utilizing the \u003ccode\u003eTaskGroup\u003c/code\u003e operator.\u003c/p\u003e\n"],["\u003cp\u003eGrouping tasks directly in the DAG graph is achieved by defining relationships between tasks, demonstrated with the syntax \u003ccode\u003estart >> [task_1, task_2]\u003c/code\u003e, which executes \u003ccode\u003etask_1\u003c/code\u003e and \u003ccode\u003etask_2\u003c/code\u003e concurrently after \u003ccode\u003estart\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eParent DAGs can trigger child DAGs using the \u003ccode\u003eTriggerDagRunOperator\u003c/code\u003e, requiring the \u003ccode\u003etrigger_dag_id\u003c/code\u003e to match the \u003ccode\u003edag_id\u003c/code\u003e of the child DAG.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eTaskGroup\u003c/code\u003e operator allows for grouping tasks within a DAG, which provides a visual organization in the Airflow UI and simplifies complex workflows.\u003c/p\u003e\n"],["\u003cp\u003eIt is recommended to avoid using SubDAGs for grouping tasks due to performance and functional issues; the document presents superior alternative methods for structuring workflows.\u003c/p\u003e\n"]]],[],null,["\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\n[Cloud Composer 3](/composer/docs/composer-3/group-tasks-inside-dags \"View this page for Cloud Composer 3\") \\| **Cloud Composer 2** \\| [Cloud Composer 1](/composer/docs/composer-1/group-tasks-inside-dags \"View this page for Cloud Composer 1\")\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nThis page describes how you can group tasks in your Airflow pipelines\nusing the following design patterns:\n\n- Grouping tasks in the DAG graph.\n- Triggering children DAGs from a parent DAG.\n- Grouping tasks with the `TaskGroup` operator.\n\n| **Important:** Airflow provides [SubDAGs](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html#subdags) to address repeating tasks. Despite being a common design pattern for grouping tasks together, SubDAGs often cause performance and functional issues, and is deprecated in Airflow. We recommend to **avoid using SubDAGs to group tasks together** in your workflow and prefer one of the alternative approaches described in this page.\n\nGroup tasks in the DAG graph\n\nTo group tasks in certain phases of your pipeline, you can use relationships\nbetween the tasks in your DAG file.\n\nConsider the following example:\n[](/static/composer/docs/images/workflow-group-dags.png) **Figure 1.** Tasks can be grouped together in an Airflow DAG (click to enlarge)\n\nIn this workflow, tasks `op-1` and `op-2` run together after the initial\ntask `start`. You can achieve this by grouping tasks together with the statement\n`start \u003e\u003e [task_1, task_2]`.\n\nThe following example provides a complete implementation of this DAG:\n\n\n from airflow import DAG\n from airflow.operators.bash import BashOperator\n from airflow.operators.dummy import DummyOperator\n from airflow.utils.dates import days_ago\n\n DAG_NAME = \"all_tasks_in_one_dag\"\n\n args = {\"owner\": \"airflow\", \"start_date\": days_ago(1), \"schedule_interval\": \"@once\"}\n\n with DAG(dag_id=DAG_NAME, default_args=args) as dag:\n start = DummyOperator(task_id=\"start\")\n\n task_1 = BashOperator(task_id=\"op-1\", bash_command=\":\", dag=dag)\n\n task_2 = BashOperator(task_id=\"op-2\", bash_command=\":\", dag=dag)\n\n some_other_task = DummyOperator(task_id=\"some-other-task\")\n\n task_3 = BashOperator(task_id=\"op-3\", bash_command=\":\", dag=dag)\n\n task_4 = BashOperator(task_id=\"op-4\", bash_command=\":\", dag=dag)\n\n end = DummyOperator(task_id=\"end\")\n\n start \u003e\u003e [task_1, task_2] \u003e\u003e some_other_task \u003e\u003e [task_3, task_4] \u003e\u003e end\n\n\u003cbr /\u003e\n\n\nTrigger children DAGs from a parent DAG\n\nYou can trigger one DAG from another DAG with the\n[`TriggerDagRunOperator` operator](https://airflow.apache.org/docs/apache-airflow/stable/_api/airflow/operators/trigger_dagrun/).\n\nConsider the following example:\n[](/static/composer/docs/images/workflow-trigger-dags.png) **Figure 2.** DAGs can be triggered from within a DAG with the TriggerDagRunOperator (click to enlarge)\n\nIn this workflow, the blocks `dag_1` and `dag_2` represent a series of tasks\nthat are grouped together in a separate DAG in the Cloud Composer\nenvironment.\n\nThe implementation of this workflow requires two separate DAG files.\nThe controlling DAG file looks like the following:\n\n\n from airflow import DAG\n from airflow.operators.dummy import DummyOperator\n from airflow.operators.trigger_dagrun import TriggerDagRunOperator\n from airflow.utils.dates import days_ago\n\n\n with DAG(\n dag_id=\"controller_dag_to_trigger_other_dags\",\n default_args={\"owner\": \"airflow\"},\n start_date=days_ago(1),\n schedule_interval=\"@once\",\n ) as dag:\n start = DummyOperator(task_id=\"start\")\n\n trigger_1 = TriggerDagRunOperator(\n task_id=\"dag_1\",\n trigger_dag_id=\"dag-to-trigger\", # Ensure this equals the dag_id of the DAG to trigger\n conf={\"message\": \"Hello World\"},\n )\n trigger_2 = TriggerDagRunOperator(\n task_id=\"dag_2\",\n trigger_dag_id=\"dag-to-trigger\", # Ensure this equals the dag_id of the DAG to trigger\n conf={\"message\": \"Hello World\"},\n )\n\n some_other_task = DummyOperator(task_id=\"some-other-task\")\n\n end = DummyOperator(task_id=\"end\")\n\n start \u003e\u003e trigger_1 \u003e\u003e some_other_task \u003e\u003e trigger_2 \u003e\u003e end\n\n\u003cbr /\u003e\n\n\n| **Note:** The value for `trigger_dag_id` inside `TriggerDagRunOperator` must match the `dag_id` value of the DAG you want to trigger.\n\nThe implementation of the child DAG, which is triggered by the controlling\nDAG, looks like the following:\n\n\n from airflow import DAG\n from airflow.operators.dummy import DummyOperator\n from airflow.utils.dates import days_ago\n\n DAG_NAME = \"dag-to-trigger\"\n\n args = {\"owner\": \"airflow\", \"start_date\": days_ago(1), \"schedule_interval\": \"None\"}\n\n with DAG(dag_id=DAG_NAME, default_args=args) as dag:\n dag_task = DummyOperator(task_id=\"dag-task\")\n\n\u003cbr /\u003e\n\n\nYou must [upload both DAG files](/composer/docs/composer-2/manage-dags#add)\nin your Cloud Composer environment for the DAG to work.\n\nGrouping tasks with the TaskGroup operator\n\nYou can use the\n[`TaskGroup` operator](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html#taskgroups) to group tasks\ntogether in your DAG. Tasks defined within a `TaskGroup` block are still part\nof the main DAG.\n\nConsider the following example:\n[](/static/composer/docs/images/workflow-taskgroup-dag.png) **Figure 3.** Tasks can be visually grouped together in the UI with the TaskGroup operator (click to enlarge)\n\nThe tasks `op-1` and `op-2` are grouped together in a block with ID\n`taskgroup_1`. An implementation of this workflow looks like the following code: \n\n from airflow.models.dag import DAG\n from airflow.operators.bash import BashOperator\n from airflow.operators.dummy import DummyOperator\n from airflow.utils.dates import days_ago\n from airflow.utils.task_group import TaskGroup\n\n with DAG(dag_id=\"taskgroup_example\", start_date=days_ago(1)) as dag:\n start = DummyOperator(task_id=\"start\")\n\n with TaskGroup(\"taskgroup_1\", tooltip=\"task group #1\") as section_1:\n task_1 = BashOperator(task_id=\"op-1\", bash_command=\":\")\n task_2 = BashOperator(task_id=\"op-2\", bash_command=\":\")\n\n with TaskGroup(\"taskgroup_2\", tooltip=\"task group #2\") as section_2:\n task_3 = BashOperator(task_id=\"op-3\", bash_command=\":\")\n task_4 = BashOperator(task_id=\"op-4\", bash_command=\":\")\n\n some_other_task = DummyOperator(task_id=\"some-other-task\")\n\n end = DummyOperator(task_id=\"end\")\n\n start \u003e\u003e section_1 \u003e\u003e some_other_task \u003e\u003e section_2 \u003e\u003e end\n\nWhat's next\n\n- [Write DAGs](/composer/docs/composer-2/write-dags)\n- [Test DAGs](/composer/docs/composer-2/test-dags)"]]