Releases: adswerve/target-bigquery
target-bigquery v0.12.6
New feature: Parametrize the granularity of BigQuery partitions
target-bigquery v0.12.5
Feature: ability to rename a field with the force_fields
parameter in target-config.
Feature requested here: #29
target-bigquery v0.12.4
Bumped requirements
target-bigquery v0.12.3
Merged pull request #31
The target obtains a BigQuery dataset if it exists or creates the dataset if it doesn't exist.
Thank you to the open source contributor tchiotludo.
target-bigquery v0.12.2
target-bigquery v0.12.1
Allows date, date-time and array be standalone types in JSON schema for simplicity
Fixed this issue: #32
Credit: Anže Kravanja
target-bigquery v0.12.0
New feature:
Infer BigQuery DECIMAL
/NUMERIC
or BIGDECIMAL
/BIGNUMERIC
data types from multipleOf
in JSON schema.
-
Decimal data types are more precise than
FLOAT
, can represent decimal fractions exactly, and are suitable for financial calculations. Learn more here. -
Caution: this is a breaking change, because some fields previously loaded as
FLOAT
will now be loaded asDECIMAL
.
Change:
Bumped setuptools
to version 60.3.1
.
Thank you to the following open source contributors:
Paul Tiplady
Jacob Karcz
Edgar Ramírez
target-bigquery v0.11.3
Added one new feature:
- Enable user to control whether target-bigquery A) merges multiple state messages from the tap into the state file (default option) or B) uses the last state message as the state file.
- This can be controlled by a command line flag
['--no-merge_state_messages' | '--no-merge_state_messages']
or from the target config file by passing"merge_state_messages": 0
. - This feature was requested by an open-source community member Dan Ladd.
- Implementation and development was overseen by Anže Kravanja.
- Code files changed:
target_bigquery/__init__.py
,target_bigquery/state.py
andtests/test_state.py
.
Target BigQuery v0.11.2
- Simplified the function which generates a valid BigQuery field name
- Updated requirements
Target BigQuery v0.11.1
Enhancements:
- Converting JSON schema to BigQuery schema:
- Cleans up field name in a more robust way
- Gets rid of all characters which violate BigQuery field naming conventions
- JSON schema validation:
- Checks for duplicate fields in JSON schema which will cause an error in BigQuery
- Tells the user what these duplicate fields are
- Repository:
- Improved our internal QA process by implementing a CI/CD workflow in GitHub repository
- Runs automated unit tests