Select the check box if you want to overwrite the existing files. Default is true.

For more information Overwrite File(s) If Exists, see Overwriting Existing Files.

If applicable, include the folder name that contains the target file in the

<bucket_name>/<folder_name>

format.

If you do not provide the bucket name and specify the folder path starting with a slash (/) in the

/<folder_name>

format, the folder path appends with the folder path that you specified in the connection properties.

For example, if you specify the

<my_bucket1>/<dir1>

folder path in the connection property and

/<dir2>

folder path in this property, the folder path appends with the folder path that you specified in the connection properties in

<my_bucket1>/<dir1>/<dir2>

format.

If you specify the

<my_bucket1>/<dir1>

folder path in the connection property and

<my_bucket2>/<dir2>

folder path in this property, the Data Integration Service writes the file in the

<my_bucket2>/<dir2>

folder path that you specify in this property.

Select one of the following values:

None
Client Side Encryption
Server Side Encryption
Server Side Encryption with KMS

For more information, see Amazon S3 Data Encryption.

Ensure that the user has write permissions on the directory. In addition, ensure that there is sufficient space to enable staging of the entire file.

Default staging directory is the

/temp

directory on the machine that hosts the Data Integration Service.

Merges the target files into a single file.

Provide semicolon separated name-value attribute pairs to optimize performance when you copy large volumes of data between Amazon S3 and HDFS. Applicable to the Amazon EMR cluster.

For more information about Hadoop performance tuning options, see Hadoop Performance Tuning Options for EMR Distribution.

You can compress the data in the following formats:

Default is None.

You can write files that use the deflate, Gzip, snappy, Lzo, and zlib compression formats in the native environment or on the Spark and Databricks Spark engine..

You can write files that use the Bzip2 compression format on the Spark engine.

For more information about compression formats, see Data Compression in Amazon S3 Sources and Targets.

You can either enter the key value pairs or specify the file path that contains the key value pairs.

For more information about the object tags, see Object Tag.

PowerExchange for Amazon S3 uses the AWS TransferManager API to upload a large object in multiple parts to Amazon S3.

When the file size is more than 5 MB, you can configure multipart upload to upload object in multiple parts in parallel. If you set the value of the

TransferManager Thread Pool Size

to greater than 50, the value reverts to 50.

The part size in bytes to upload an Amazon S3 object. Default is 5 MB.

The time duration during which an IAM user can use the dynamically generated temporarily credentials to access the AWS resource. Enter the time duration in seconds.

Default is 900 seconds.

If you require more than 900 seconds, you can set the time duration maximum up to 12 hours in the AWS console and then enter the same time duration in this property.

None. Partitioning is not configured.
Last N Columns Partitioned. The last N columns are selected for partitioning.
Partition Column Names. Comma-separated column names are selected for partitioning.

If you selected

None

as the partition option, do not specify a partition argument.

If you selected

Last N Columns Partitioned

as the partition option, specify an integer value as the partition argument.

If you selected

Partition Column Names

as the partition option, specify comma-separated column names as the partition argument.