file dataset documentation
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For more information about specific framework configuration options, look at the [frameworks](frameworks/) section of this documentation.
### Datasets
+
+One aspect of maintaining different deployment environments is where and how you get the data required to run the jobs.
+
+To provide an abstraction, each of our SDKs provides a way to load and persist data easily. This functionality is based on prior configuration.
+
+In a job repository, each environment contains a ```datasets.yml``` file. This file contains the configurations of all datasets to be used in the job.
+
+Below is an example of a simple configuration, for a dataset stored as parquet in Amazon S3.
+
+```yaml
+file:
+ - uri: s3a://amaterasu-example/input/random-beers
+ format: parquet
+ name: random-beers
+```
+
+#### Detailed configuration
+Below are the different types of datasets and their corresponding configuration options.
+Do note that different Apache Amaterasu frameworks may have their take on the configurations below.
+##### File
+The following formats are currently supported - JSON, parquet, CSV, ORC.
+
+The following storage types are currently supported - s3, azure blob storage, file system, HDFS.
+
+The following configuration options are currently supported:
+
+| Parameter | Description |
+|:---------:|:-----------:|
+| name |The name of the dataset|
+| uri |The file URI. Supported schemes are: s3a, file, hdfs, wasb, wasbs, gs, gs|
+| format |The file format - JSON, parquet, CSV, ORC|
+
+Example:
+```yaml
+file:
+ - uri: s3a://amaterasu-example/input/random-beers
+ format: parquet
+ name: random-beers
+```
+
+> Note! If the scheme or format isn't currently supported by the available Apache Amaterasu frameworks, it is still possible to define using a [generic dataset](#generic).
+
### Custom Configuration
\ No newline at end of file
