Merge pull request apache#2166 from jlowin/speedup

airflow/config_templates/default_airflow.cfg

@@ -0,0 +1,386 @@
+# 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.
+
+
+# This is the template for Airflow's default configuration. When Airflow is
+# imported, it looks for a configuration file at $AIRFLOW_HOME/airflow.cfg. If
+# it doesn't exist, Airflow uses this template to generate it by replacing
+# variables in curly braces with their global values from configuration.py.
+
+# Users should not modify this file; they should customize the generated
+# airflow.cfg instead.
+
+
+# ----------------------- TEMPLATE BEGINS HERE -----------------------
+
+[core]
+# The home folder for airflow, default is ~/airflow
+airflow_home = {AIRFLOW_HOME}
+
+# The folder where your airflow pipelines live, most likely a
+# subfolder in a code repository
+# This path must be absolute
+dags_folder = {AIRFLOW_HOME}/dags
+
+# The folder where airflow should store its log files
+# This path must be absolute
+base_log_folder = {AIRFLOW_HOME}/logs
+
+# Airflow can store logs remotely in AWS S3 or Google Cloud Storage. Users
+# must supply a remote location URL (starting with either 's3://...' or
+# 'gs://...') and an Airflow connection id that provides access to the storage
+# location.
+remote_base_log_folder =
+remote_log_conn_id =
+# Use server-side encryption for logs stored in S3
+encrypt_s3_logs = False
+# DEPRECATED option for remote log storage, use remote_base_log_folder instead!
+s3_log_folder =
+
+# The executor class that airflow should use. Choices include
+# SequentialExecutor, LocalExecutor, CeleryExecutor, DaskExecutor
+executor = SequentialExecutor
+
+# The SqlAlchemy connection string to the metadata database.
+# SqlAlchemy supports many different database engine, more information
+# their website
+sql_alchemy_conn = sqlite:///{AIRFLOW_HOME}/airflow.db
+
+# The SqlAlchemy pool size is the maximum number of database connections
+# in the pool.
+sql_alchemy_pool_size = 5
+
+# The SqlAlchemy pool recycle is the number of seconds a connection
+# can be idle in the pool before it is invalidated. This config does
+# not apply to sqlite.
+sql_alchemy_pool_recycle = 3600
+
+# The amount of parallelism as a setting to the executor. This defines
+# the max number of task instances that should run simultaneously
+# on this airflow installation
+parallelism = 32
+
+# The number of task instances allowed to run concurrently by the scheduler
+dag_concurrency = 16
+
+# Are DAGs paused by default at creation
+dags_are_paused_at_creation = True
+
+# When not using pools, tasks are run in the "default pool",
+# whose size is guided by this config element
+non_pooled_task_slot_count = 128
+
+# The maximum number of active DAG runs per DAG
+max_active_runs_per_dag = 16
+
+# Whether to load the examples that ship with Airflow. It's good to
+# get started, but you probably want to set this to False in a production
+# environment
+load_examples = True
+
+# Where your Airflow plugins are stored
+plugins_folder = {AIRFLOW_HOME}/plugins
+
+# Secret key to save connection passwords in the db
+fernet_key = {FERNET_KEY}
+
+# Whether to disable pickling dags
+donot_pickle = False
+
+# How long before timing out a python file import while filling the DagBag
+dagbag_import_timeout = 30
+
+# The class to use for running task instances in a subprocess
+task_runner = BashTaskRunner
+
+# If set, tasks without a `run_as_user` argument will be run with this user
+# Can be used to de-elevate a sudo user running Airflow when executing tasks
+default_impersonation =
+
+# What security module to use (for example kerberos):
+security =
+
+# Turn unit test mode on (overwrites many configuration options with test
+# values at runtime)
+unit_test_mode = False
+
+[cli]
+# In what way should the cli access the API. The LocalClient will use the
+# database directly, while the json_client will use the api running on the
+# webserver
+api_client = airflow.api.client.local_client
+endpoint_url = http://localhost:8080
+
+[api]
+# How to authenticate users of the API
+auth_backend = airflow.api.auth.backend.default
+
+[operators]
+# The default owner assigned to each new operator, unless
+# provided explicitly or passed via `default_args`
+default_owner = Airflow
+default_cpus = 1
+default_ram = 512
+default_disk = 512
+default_gpus = 0
+
+
+[webserver]
+# The base url of your website as airflow cannot guess what domain or
+# cname you are using. This is used in automated emails that
+# airflow sends to point links to the right web server
+base_url = http://localhost:8080
+
+# The ip specified when starting the web server
+web_server_host = 0.0.0.0
+
+# The port on which to run the web server
+web_server_port = 8080
+
+# Paths to the SSL certificate and key for the web server. When both are
+# provided SSL will be enabled. This does not change the web server port.
+web_server_ssl_cert =
+web_server_ssl_key =
+
+# Number of seconds the gunicorn webserver waits before timing out on a worker
+web_server_worker_timeout = 120
+
+# Number of workers to refresh at a time. When set to 0, worker refresh is
+# disabled. When nonzero, airflow periodically refreshes webserver workers by
+# bringing up new ones and killing old ones.
+worker_refresh_batch_size = 1
+
+# Number of seconds to wait before refreshing a batch of workers.
+worker_refresh_interval = 30
+
+# Secret key used to run your flask app
+secret_key = temporary_key
+
+# Number of workers to run the Gunicorn web server
+workers = 4
+
+# The worker class gunicorn should use. Choices include
+# sync (default), eventlet, gevent
+worker_class = sync
+
+# Log files for the gunicorn webserver. '-' means log to stderr.
+access_logfile = -
+error_logfile = -
+
+# Expose the configuration file in the web server
+expose_config = False
+
+# Set to true to turn on authentication:
+# http://pythonhosted.org/airflow/security.html#web-authentication
+authenticate = False
+
+# Filter the list of dags by owner name (requires authentication to be enabled)
+filter_by_owner = False
+
+# Filtering mode. Choices include user (default) and ldapgroup.
+# Ldap group filtering requires using the ldap backend
+#
+# Note that the ldap server needs the "memberOf" overlay to be set up
+# in order to user the ldapgroup mode.
+owner_mode = user
+
+# Default DAG view.  Valid values are:
+# tree, graph, duration, gantt, landing_times
+dag_default_view = tree
+
+# Default DAG orientation. Valid values are:
+# LR (Left->Right), TB (Top->Bottom), RL (Right->Left), BT (Bottom->Top)
+dag_orientation = LR
+
+# Puts the webserver in demonstration mode; blurs the names of Operators for
+# privacy.
+demo_mode = False
+
+# The amount of time (in secs) webserver will wait for initial handshake
+# while fetching logs from other worker machine
+log_fetch_timeout_sec = 5
+
+# By default, the webserver shows paused DAGs. Flip this to hide paused
+# DAGs by default
+hide_paused_dags_by_default = False
+
+[email]
+email_backend = airflow.utils.email.send_email_smtp
+
+
+[smtp]
+# If you want airflow to send emails on retries, failure, and you want to use
+# the airflow.utils.email.send_email_smtp function, you have to configure an
+# smtp server here
+smtp_host = localhost
+smtp_starttls = True
+smtp_ssl = False
+# Uncomment and set the user/pass settings if you want to use SMTP AUTH
+# smtp_user = airflow
+# smtp_password = airflow
+smtp_port = 25
+smtp_mail_from = [email protected]
+
+
+[celery]
+# This section only applies if you are using the CeleryExecutor in
+# [core] section above
+
+# The app name that will be used by celery
+celery_app_name = airflow.executors.celery_executor
+
+# The concurrency that will be used when starting workers with the
+# "airflow worker" command. This defines the number of task instances that
+# a worker will take, so size up your workers based on the resources on
+# your worker box and the nature of your tasks
+celeryd_concurrency = 16
+
+# When you start an airflow worker, airflow starts a tiny web server
+# subprocess to serve the workers local log files to the airflow main
+# web server, who then builds pages and sends them to users. This defines
+# the port on which the logs are served. It needs to be unused, and open
+# visible from the main web server to connect into the workers.
+worker_log_server_port = 8793
+
+# The Celery broker URL. Celery supports RabbitMQ, Redis and experimentally
+# a sqlalchemy database. Refer to the Celery documentation for more
+# information.
+broker_url = sqla+mysql://airflow:airflow@localhost:3306/airflow
+
+# Another key Celery setting
+celery_result_backend = db+mysql://airflow:airflow@localhost:3306/airflow
+
+# Celery Flower is a sweet UI for Celery. Airflow has a shortcut to start
+# it `airflow flower`. This defines the IP that Celery Flower runs on
+flower_host = 0.0.0.0
+
+# This defines the port that Celery Flower runs on
+flower_port = 5555
+
+# Default queue that tasks get assigned to and that worker listen on.
+default_queue = default
+
+
+[dask]
+# This section only applies if you are using the DaskExecutor in
+# [core] section above
+
+# The IP address and port of the Dask cluster's scheduler.
+cluster_address = 127.0.0.1:8786
+
+
+[scheduler]
+# Task instances listen for external kill signal (when you clear tasks
+# from the CLI or the UI), this defines the frequency at which they should
+# listen (in seconds).
+job_heartbeat_sec = 5
+
+# The scheduler constantly tries to trigger new tasks (look at the
+# scheduler section in the docs for more information). This defines
+# how often the scheduler should run (in seconds).
+scheduler_heartbeat_sec = 5
+
+# after how much time should the scheduler terminate in seconds
+# -1 indicates to run continuously (see also num_runs)
+run_duration = -1
+
+# after how much time a new DAGs should be picked up from the filesystem
+min_file_process_interval = 0
+
+dag_dir_list_interval = 300
+
+# How often should stats be printed to the logs
+print_stats_interval = 30
+
+child_process_log_directory = {AIRFLOW_HOME}/logs/scheduler
+
+# Local task jobs periodically heartbeat to the DB. If the job has
+# not heartbeat in this many seconds, the scheduler will mark the
+# associated task instance as failed and will re-schedule the task.
+scheduler_zombie_task_threshold = 300
+
+# Turn off scheduler catchup by setting this to False.
+# Default behavior is unchanged and
+# Command Line Backfills still work, but the scheduler
+# will not do scheduler catchup if this is False,
+# however it can be set on a per DAG basis in the
+# DAG definition (catchup)
+catchup_by_default = True
+
+# Statsd (https://github.com/etsy/statsd) integration settings
+statsd_on = False
+statsd_host = localhost
+statsd_port = 8125
+statsd_prefix = airflow
+
+# The scheduler can run multiple threads in parallel to schedule dags.
+# This defines how many threads will run. However airflow will never
+# use more threads than the amount of cpu cores available.
+max_threads = 2
+
+authenticate = False
+
+
+[mesos]
+# Mesos master address which MesosExecutor will connect to.
+master = localhost:5050
+
+# The framework name which Airflow scheduler will register itself as on mesos
+framework_name = Airflow
+
+# Number of cpu cores required for running one task instance using
+# 'airflow run <dag_id> <task_id> <execution_date> --local -p <pickle_id>'
+# command on a mesos slave
+task_cpu = 1
+
+# Memory in MB required for running one task instance using
+# 'airflow run <dag_id> <task_id> <execution_date> --local -p <pickle_id>'
+# command on a mesos slave
+task_memory = 256
+
+# Enable framework checkpointing for mesos
+# See http://mesos.apache.org/documentation/latest/slave-recovery/
+checkpoint = False
+
+# Failover timeout in milliseconds.
+# When checkpointing is enabled and this option is set, Mesos waits
+# until the configured timeout for
+# the MesosExecutor framework to re-register after a failover. Mesos
+# shuts down running tasks if the
+# MesosExecutor framework fails to re-register within this timeframe.
+# failover_timeout = 604800
+
+# Enable framework authentication for mesos
+# See http://mesos.apache.org/documentation/latest/configuration/
+authenticate = False
+
+# Mesos credentials, if authentication is enabled
+# default_principal = admin
+# default_secret = admin
+
+
+[kerberos]
+ccache = /tmp/airflow_krb5_ccache
+# gets augmented with fqdn
+principal = airflow
+reinit_frequency = 3600
+kinit_path = kinit
+keytab = airflow.keytab
+
+
+[github_enterprise]
+api_rev = v3
+
+
+[admin]
+# UI to hide sensitive variable fields when set to True
+hide_sensitive_variable_fields = True