airflow-commits mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From fo...@apache.org
Subject [20/50] incubator-airflow git commit: [AIRFLOW-1933] Fix some typos
Date Fri, 04 May 2018 07:02:16 GMT
[AIRFLOW-1933] Fix some typos

Closes #2474 from Philippus/patch-1


Project: http://git-wip-us.apache.org/repos/asf/incubator-airflow/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-airflow/commit/ad28decc
Tree: http://git-wip-us.apache.org/repos/asf/incubator-airflow/tree/ad28decc
Diff: http://git-wip-us.apache.org/repos/asf/incubator-airflow/diff/ad28decc

Branch: refs/heads/v1-10-test
Commit: ad28decc74a87f6f9fbff57f200199860a2bfa81
Parents: 3952e05
Author: Philippus Baalman <philippus@gmail.com>
Authored: Sun Apr 29 20:08:48 2018 -0700
Committer: r39132 <siddharthanand@yahoo.com>
Committed: Sun Apr 29 20:08:48 2018 -0700

----------------------------------------------------------------------
 UPDATING.md | 22 +++++++++++-----------
 1 file changed, 11 insertions(+), 11 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/incubator-airflow/blob/ad28decc/UPDATING.md
----------------------------------------------------------------------
diff --git a/UPDATING.md b/UPDATING.md
index 609c8db..8006876 100644
--- a/UPDATING.md
+++ b/UPDATING.md
@@ -74,17 +74,17 @@ With Airflow 1.9 or lower, there were two connection strings for the Google
Clou
 
 ### SSH Hook updates, along with new SSH Operator & SFTP Operator
 
-SSH Hook now uses Paramiko library to create ssh client connection, instead of sub-process
based ssh command execution previously (<1.9.0), so this is backward incompatible.
+SSH Hook now uses the Paramiko library to create an ssh client connection, instead of the
sub-process based ssh command execution previously (<1.9.0), so this is backward incompatible.
   - update SSHHook constructor
-  - use SSHOperator class in place of SSHExecuteOperator which is removed now. Refer test_ssh_operator.py
for usage info.
-  - SFTPOperator is added to perform secure file transfer from serverA to serverB. Refer
test_sftp_operator.py.py for usage info.
+  - use SSHOperator class in place of SSHExecuteOperator which is removed now. Refer to test_ssh_operator.py
for usage info.
+  - SFTPOperator is added to perform secure file transfer from serverA to serverB. Refer
to test_sftp_operator.py.py for usage info.
   - No updates are required if you are using ftpHook, it will continue to work as is.
 
 ### S3Hook switched to use Boto3
 
 The airflow.hooks.S3_hook.S3Hook has been switched to use boto3 instead of the older boto
(a.k.a. boto2). This results in a few backwards incompatible changes to the following classes:
S3Hook:
   - the constructors no longer accepts `s3_conn_id`. It is now called `aws_conn_id`.
-  - the default conneciton is now "aws_default" instead of "s3_default"
+  - the default connection is now "aws_default" instead of "s3_default"
   - the return type of objects returned by `get_bucket` is now boto3.s3.Bucket
   - the return type of `get_key`, and `get_wildcard_key` is now an boto3.S3.Object.
 
@@ -106,7 +106,7 @@ Once a logger has determined that a message needs to be processed, it
is passed
 
 #### Changes in Airflow Logging
 
-Airflow's logging mechanism has been refactored to uses Python’s builtin `logging` module
to perform logging of the application. By extending classes with the existing `LoggingMixin`,
all the logging will go through a central logger. Also the `BaseHook` and `BaseOperator` already
extends this class, so it is easily available to do logging.
+Airflow's logging mechanism has been refactored to use Python’s builtin `logging` module
to perform logging of the application. By extending classes with the existing `LoggingMixin`,
all the logging will go through a central logger. Also the `BaseHook` and `BaseOperator` already
extend this class, so it is easily available to do logging.
 
 The main benefit is easier configuration of the logging by setting a single centralized python
file. Disclaimer; there is still some inline configuration, but this will be removed eventually.
The new logging class is defined by setting the dotted classpath in your `~/airflow/airflow.cfg`
file:
 
@@ -153,7 +153,7 @@ The `file_task_handler` logger has been made more flexible. The default
format c
 If you are logging to Google cloud storage, please see the [Google cloud platform documentation](https://airflow.incubator.apache.org/integration.html#gcp-google-cloud-platform)
for logging instructions.
 
 If you are using S3, the instructions should be largely the same as the Google cloud platform
instructions above. You will need a custom logging config. The `REMOTE_BASE_LOG_FOLDER` configuration
key in your airflow config has been removed, therefore you will need to take the following
steps:
- - Copy the logging configuration from [`airflow/config_templates/airflow_logging_settings.py`](https://github.com/apache/incubator-airflow/blob/master/airflow/config_templates/airflow_local_settings.py)
and copy it.
+ - Copy the logging configuration from [`airflow/config_templates/airflow_logging_settings.py`](https://github.com/apache/incubator-airflow/blob/master/airflow/config_templates/airflow_local_settings.py).
  - Place it in a directory inside the Python import path `PYTHONPATH`. If you are using Python
2.7, ensuring that any `__init__.py` files exist so that it is importable.
  - Update the config by setting the path of `REMOTE_BASE_LOG_FOLDER` explicitly in the config.
The `REMOTE_BASE_LOG_FOLDER` key is not used anymore.
  - Set the `logging_config_class` to the filename and dict. For example, if you place `custom_logging_config.py`
on the base of your pythonpath, you will need to set `logging_config_class = custom_logging_config.LOGGING_CONFIG`
in your config as Airflow 1.8.
@@ -180,12 +180,12 @@ supported and will be removed entirely in Airflow 2.0
   Note that JSON serialization is stricter than pickling, so if you want to e.g. pass
   raw bytes through XCom you must encode them using an encoding like base64.
   By default pickling is still enabled until Airflow 2.0. To disable it
-  Set enable_xcom_pickling = False in your Airflow config.
+  set enable_xcom_pickling = False in your Airflow config.
 
 ## Airflow 1.8.1
 
 The Airflow package name was changed from `airflow` to `apache-airflow` during this release.
You must uninstall
-previously installed version of Airflow before installing 1.8.1.
+a previously installed version of Airflow before installing 1.8.1.
 
 ## Airflow 1.8
 
@@ -202,12 +202,12 @@ Systemd unit files have been updated. If you use systemd please make
sure to upd
 Airflow 1.7.1 has issues with being able to over subscribe to a pool, ie. more slots could
be used than were
 available. This is fixed in Airflow 1.8.0, but due to past issue jobs may fail to start although
their
 dependencies are met after an upgrade. To workaround either temporarily increase the amount
of slots above
-the the amount of queued tasks or use a new pool.
+the amount of queued tasks or use a new pool.
 
 ### Less forgiving scheduler on dynamic start_date
 Using a dynamic start_date (e.g. `start_date = datetime.now()`) is not considered a best
practice. The 1.8.0 scheduler
 is less forgiving in this area. If you encounter DAGs not being scheduled you can try using
a fixed start_date and
-renaming your dag. The last step is required to make sure you start with a clean slate, otherwise
the old schedule can
+renaming your DAG. The last step is required to make sure you start with a clean slate, otherwise
the old schedule can
 interfere.
 
 ### New and updated scheduler options
@@ -243,7 +243,7 @@ By default the scheduler will fill any missing interval DAG Runs between
the las
 This setting changes that behavior to only execute the latest interval. This can also be
specified per DAG as
 `catchup = False / True`. Command line backfills will still work.
 
-### Faulty Dags do not show an error in the Web UI
+### Faulty DAGs do not show an error in the Web UI
 
 Due to changes in the way Airflow processes DAGs the Web UI does not show an error when processing
a faulty DAG. To
 find processing errors go the `child_process_log_directory` which defaults to `<AIRFLOW_HOME>/scheduler/latest`.


Mime
View raw message