View Source aws_iotanalytics (aws v1.0.4)
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.Summary
Functions
Used to create a channel.
Used to create a dataset.
queryAction
(a SQL query) or a containerAction
(executing a containerized application).Creates a pipeline.
Deletes the specified dataset.
Sets or updates the IoT Analytics logging options.
Retrieves a sample of messages from the specified channel ingested during the specified timeframe.
Adds to or modifies the tags of the given resource.
Updates the settings of a pipeline.
Functions
cancel_pipeline_reprocessing(Client, PipelineName, ReprocessingId, Input)
View Sourcecancel_pipeline_reprocessing(Client, PipelineName, ReprocessingId, Input0, Options0)
View SourceUsed to create a channel.
A channel collects data from an MQTT topic and archives the raw, unprocessed messages before publishing the data to a pipeline.Used to create a dataset.
A dataset stores data retrieved from a data store by applying aqueryAction
(a SQL query) or a containerAction
(executing a containerized application). This operation creates the skeleton of a dataset. The dataset can be populated manually by calling CreateDatasetContent
or automatically according to a trigger you specify.
queryAction
(a SQL query) or a containerAction
(executing a containerized application).
Creates a pipeline.
A pipeline consumes messages from a channel and allows you to process the messages before storing them in a data store. You must specify both achannel
and a datastore
activity and, optionally, as many as 23 additional activities in the pipelineActivities
array.
Deletes the specified dataset.
You do not have to delete the content of the dataset before you perform this operation.describe_channel(Client, ChannelName, QueryMap, HeadersMap, Options0)
View Sourcedescribe_dataset(Client, DatasetName, QueryMap, HeadersMap, Options0)
View Sourcedescribe_datastore(Client, DatastoreName, QueryMap, HeadersMap, Options0)
View Sourcedescribe_pipeline(Client, PipelineName, QueryMap, HeadersMap, Options0)
View Sourceget_dataset_content(Client, DatasetName, QueryMap, HeadersMap, Options0)
View Sourcelist_dataset_contents(Client, DatasetName, QueryMap, HeadersMap, Options0)
View Sourcelist_tags_for_resource(Client, ResourceArn, QueryMap, HeadersMap, Options0)
View SourceSets or updates the IoT Analytics logging options.
If you update the value of anyloggingOptions
field, it takes up to one minute for the change to take effect. Also, if you change the policy attached to the role you specified in the roleArn
field (for example, to correct an invalid policy), it takes up to five minutes for that change to take effect.
Retrieves a sample of messages from the specified channel ingested during the specified timeframe.
Up to 10 messages can be retrieved.sample_channel_data(Client, ChannelName, QueryMap, HeadersMap, Options0)
View Sourcestart_pipeline_reprocessing(Client, PipelineName, Input0, Options0)
View SourceAdds to or modifies the tags of the given resource.
Tags are metadata that can be used to manage a resource.Updates the settings of a pipeline.
You must specify both achannel
and a datastore
activity and, optionally, as many as 23 additional activities in the pipelineActivities
array.