airflow.providers.apache.drill.hooks.drill
¶
Module Contents¶
Classes¶
Interact with Apache Drill via sqlalchemy-drill. |
- class airflow.providers.apache.drill.hooks.drill.DrillHook(*args, schema=None, log_sql=True, **kwargs)[source]¶
Bases:
airflow.providers.common.sql.hooks.sql.DbApiHook
Interact with Apache Drill via sqlalchemy-drill.
You can specify the SQLAlchemy dialect and driver that sqlalchemy-drill will employ to communicate with Drill in the extras field of your connection, e.g.
{"dialect_driver": "drill+sadrill"}
for communication over Drill’s REST API. See the sqlalchemy-drill documentation for descriptions of the supported dialects and drivers.You can specify the default storage_plugin for the sqlalchemy-drill connection using the extras field e.g.
{"storage_plugin": "dfs"}
.- abstract insert_rows(table, rows, target_fields=None, commit_every=1000, replace=False, **kwargs)[source]¶
Insert a collection of tuples into a table.
Rows are inserted in chunks, each chunk (of size
commit_every
) is done in a new transaction.- Parameters
table (str) – Name of the target table
rows (Iterable[tuple[str]]) – The rows to insert into the table
target_fields (Iterable[str] | None) – The names of the columns to fill in the table
commit_every (int) – The maximum number of rows to insert in one transaction. Set to 0 to insert all rows in one transaction.
replace (bool) – Whether to replace instead of insert
executemany – If True, all rows are inserted at once in chunks defined by the commit_every parameter. This only works if all rows have same number of column names, but leads to better performance.
fast_executemany – If True, the fast_executemany parameter will be set on the cursor used by executemany which leads to better performance, if supported by driver.
autocommit – What to set the connection’s autocommit setting to before executing the query.