fix: avoid parallel DAG run & disabling catchup!

[amindadgar]

• the catchup was for running multiple instances of a DAG in case the DAG ran on very old past.
• the parallel avoiding was because we're doing ETL job and if we ran multiple times, we could end up in having duplicate data

Summary by CodeRabbit

• Improvements
  • Enhanced scheduling behavior by limiting the number of active runs to 1 for various DAGs.
  • Disabled catch-up runs for improved task execution consistency across multiple ETL pipelines.

[coderabbitai[bot]]

[!WARNING]

Review failed

The pull request is closed.

Walkthrough

The recent updates primarily focus on enhancing the scheduling behavior of various DAGs by incorporating the max_active_runs=1 parameter across multiple files, ensuring only one active run at a time. Additionally, the catchup=False parameter is added to several DAG declarations to prevent task backlog. These changes aim to streamline task execution and improve overall system stability.

Changes

Files	Change Summaries
dags/github.py	Added max_active_runs=1 to the DAG declaration.
dags/hivemind_discord_etl.py	Added max_active_runs=1 and removed catchup=False in DAG declarations for hivemind_discord_etl and start_discord_vectorstore.
dags/hivemind_discourse_etl.py	Added catchup=False and max_active_runs=1 to DAG configurations for discourse_vector_store and discourse_summary_vector_store.
dags/hivemind_github_etl.py	Added catchup=False and max_active_runs=1 to the DAG definition.
dags/hivemind_google_drive_etl.py	Added catchup=False and max_active_runs=1 to the DAG definition for gdrive_vector_store.
dags/hivemind_mediawiki_etl.py	Added catchup=False and max_active_runs=1 to the DAG declaration.
dags/hivemind_notion_etl.py	Added catchup=False and max_active_runs=1 to the DAG declaration.

Poem

In the land of data's endless run,
A rabbit hopped, the tasks begun,
With max_active_runs set to one,
And catchup gone, the race was won.
Now DAGs do dance in perfect tune,
Under the bright scheduling moon. 🌕

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