awswrangler.s3.merge_datasets¶
- awswrangler.s3.merge_datasets(source_path: str, target_path: str, mode: Literal['append', 'overwrite', 'overwrite_partitions'] = 'append', ignore_empty: bool = False, use_threads: bool | int = True, boto3_session: Session | None = None, s3_additional_kwargs: dict[str, Any] | None = None) list[str] ¶
Merge a source dataset into a target dataset.
This function accepts Unix shell-style wildcards in the source_path argument. * (matches everything), ? (matches any single character), [seq] (matches any character in seq), [!seq] (matches any character not in seq). If you want to use a path which includes Unix shell-style wildcard characters (*, ?, []), you can use glob.escape(source_path) before passing the path to this function.
Note
If you are merging tables (S3 datasets + Glue Catalog metadata), remember that you will also need to update your partitions metadata in some cases. (e.g. wr.athena.repair_table(table=’…’, database=’…’))
Note
In case of use_threads=True the number of threads that will be spawned will be gotten from os.cpu_count().
Note
Following arguments are not supported in distributed mode with engine EngineEnum.RAY:
boto3_session
- Parameters:
source_path (str,) – S3 Path for the source directory.
target_path (str,) – S3 Path for the target directory.
mode (str, optional) –
append
(Default),overwrite
,overwrite_partitions
.ignore_empty (bool) – Ignore files with 0 bytes.
use_threads (bool, int) – True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. If integer is provided, specified number is used.
boto3_session (boto3.Session(), optional) – Boto3 Session. The default boto3 session will be used if boto3_session receive None.
s3_additional_kwargs (dict[str, Any], optional) – Forwarded to botocore requests. e.g. s3_additional_kwargs={‘ServerSideEncryption’: ‘aws:kms’, ‘SSEKMSKeyId’: ‘YOUR_KMS_KEY_ARN’}
- Returns:
List of new objects paths.
- Return type:
List[str]
Examples
Merging
>>> import awswrangler as wr >>> wr.s3.merge_datasets( ... source_path="s3://bucket0/dir0/", ... target_path="s3://bucket1/dir1/", ... mode="append" ... ) ["s3://bucket1/dir1/key0", "s3://bucket1/dir1/key1"]
Merging with a KMS key
>>> import awswrangler as wr >>> wr.s3.merge_datasets( ... source_path="s3://bucket0/dir0/", ... target_path="s3://bucket1/dir1/", ... mode="append", ... s3_additional_kwargs={ ... 'ServerSideEncryption': 'aws:kms', ... 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN' ... } ... ) ["s3://bucket1/dir1/key0", "s3://bucket1/dir1/key1"]