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API for AWS IoT Analytics

ABAP Interface /AWS1/IF_IOA

The "TLA" is a Three Letter Abbreviation that appears in ABAP class names, data dictionary objects and other ABAP objects throughout the AWS SDK for SAP ABAP. The TLA for AWS IoT Analytics is IOA. This TLA helps squeeze ABAP objects into the 30-character length limit of the ABAP data dictionary.


To install the AWS SDK for SAP ABAP, import the Core transport, along with the transport for the IoTAnalytics module and other API modules you are interested in. A few modules are included in the Core transport itself. For more information, see the Developer Guide guide.

About The Service

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight.

Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources.

IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

Using the SDK

In your code, create a client using the SDK module for AWS IoT Analytics, which is created with factory method /AWS1/CL_IOA_FACTORY=>create(). In this example we will assume you have configured an SDK profile in transaction /AWS1/IMG called ZFINANCE.

DATA(go_session)   = /aws1/cl_rt_session_aws=>create( 'ZFINANCE' ).
DATA(go_ioa)       = /aws1/cl_ioa_factory=>create( go_session ).

Your variable go_ioa is an instance of /AWS1/IF_IOA, and all of the operations in the AWS IoT Analytics service are accessed by calling methods in /AWS1/IF_IOA.

API Operations

For an overview of ABAP method calls corresponding to API operations in AWS IoT Analytics, see the Operation List.

Factory Method

/AWS1/CL_IOA_FACTORY=>create( )

Creates an object of type /AWS1/IF_IOA.


Optional arguments:







/AWS1/IF_IOA represents the ABAP client for the IoTAnalytics service, representing each operation as a method call. For more information see the API Page page.

Configuring Programmatically

DATA(lo_config) = DATA(go_ioa)->get_config( ).

lo_config is a variable of type /AWS1/CL_IOA_CONFIG. See the documentation for /AWS1/CL_IOA_CONFIG for details on the settings that can be configured.


Paginators for AWS IoT Analytics can be created via get_paginator() which returns a paginator object of type /AWS1/IF_IOA_PAGINATOR. The operation method that is being paginated is called using the paginator object, which accepts any necessary parameters to provide to the underlying API operation. This returns an iterator object which can be used to iterate over paginated results using has_next() and get_next() methods.

Details about the paginator methods available for service AWS IoT Analytics can be found in interface /AWS1/IF_IOA_PAGINATOR.