awswrangler.timestream.create_table¶
- awswrangler.timestream.create_table(database: str, table: str, memory_retention_hours: int, magnetic_retention_days: int, tags: Dict[str, str] | None = None, timestream_additional_kwargs: Dict[str, Any] | None = None, boto3_session: Session | None = None) str ¶
Create a new Timestream database.
Note
If the KMS key is not specified, the database will be encrypted with a Timestream managed KMS key located in your account.
- Parameters:
database (str) – Database name.
table (str) – Table name.
memory_retention_hours (int) – The duration for which data must be stored in the memory store.
magnetic_retention_days (int) – The duration for which data must be stored in the magnetic store.
tags (Optional[Dict[str, str]]) – Key/Value dict to put on the table. Tags enable you to categorize databases and/or tables, for example, by purpose, owner, or environment. e.g. {“foo”: “boo”, “bar”: “xoo”})
timestream_additional_kwargs (Optional[Dict[str, Any]]) – Forwarded to botocore requests. e.g. timestream_additional_kwargs={‘MagneticStoreWriteProperties’: {‘EnableMagneticStoreWrites’: True}}
boto3_session (boto3.Session(), optional) – Boto3 Session. The default boto3 Session will be used if boto3_session receive None.
- Returns:
The Amazon Resource Name that uniquely identifies this database. (ARN)
- Return type:
str
Examples
Creating a table.
>>> import awswrangler as wr >>> arn = wr.timestream.create_table( ... database="MyDatabase", ... table="MyTable", ... memory_retention_hours=3, ... magnetic_retention_days=7 ... )