Orders

Orders pipeline can be used to request and retrieve information about orders created or updated during the time frame indicated by the specified parameters.

Read more about this end-point here

Configuring the Credentials

Select the account credentials which has access to relevant Amazon Selling Partner API data from the dropdown menu & Click Next

Credentials not listed in dropdown ?

Click on + Add New for adding new credentials

Data Pipelines Details

Data Pipeline

Select Orders from the dropdown

amazon sp api orders list

Setting Parameters

Parameter Description Values

Insert Mode

Optional

Specifies the manner in which data will get updated in the data warehouse : UPSERT will insert only new records or records with changes, APPEND will insert all fetched data at the end, REPLACE will drop the existing table and recreate a fresh one on each run.Recommended to use "Upsert" option unless there is a specific requirement.

{Upsert, Append, Replace}

Default Value: UPSERT

Data Fetch Start Date

Required

Indicate the date from which you wish to begin fetching the orders data.

Date

Additional Information

Optional

Specify whether you want to include additional information such as buyer information for the order , detailed order item information, buyer information for the order items in the order, the shipping address for the order.

{OrderItems, OrderBuyerInfo, OrderAddress, OrderItemsBuyerInfo}

amazon sp api orders config

Datapipeline Scheduling

Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.

Manual Run

If scheduling is not required, you can use the toggle to run the pipeline manually.

Normal Scheduling

Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.

Advance Scheduling

Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.

Detailed explanation on scheduling of pipelines can be found here

Dataset & Name

Dataset Name

Key in the Dataset Name(also serves as the table name in your data warehouse).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.

Dataset Description

Enter a short description (optional) describing the dataset being fetched by this particular pipeline.

Notifications

Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".

Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here

Still have Questions?

We’ll be happy to help you with any questions you might have! Send us an email at info@datachannel.co.

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