AWS.IoTAnalytics — AWS SDK for JavaScript (original) (raw)

Constructs a service interface object. Each API operation is exposed as a function on service.

Service Description

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.

Sending a Request Using IoTAnalytics

var iotanalytics = new AWS.IoTAnalytics();
iotanalytics.batchPutMessage(params, function (err, data) {
  if (err) console.log(err, err.stack); // an error occurred
  else     console.log(data);           // successful response
});

Locking the API Version

In order to ensure that the IoTAnalytics object uses this specific API, you can construct the object by passing the apiVersion option to the constructor:

var iotanalytics = new AWS.IoTAnalytics({apiVersion: '2017-11-27'});

You can also set the API version globally in AWS.config.apiVersions using the iotanalytics service identifier:

AWS.config.apiVersions = {
  iotanalytics: '2017-11-27',
  // other service API versions
};

var iotanalytics = new AWS.IoTAnalytics();

Property Details

endpoint ⇒ AWS.Endpoint

Returns an Endpoint object representing the endpoint URL for service requests.

Method Details

batchPutMessage(params = {}, callback) ⇒ AWS.Request

Sends messages to a channel.

cancelPipelineReprocessing(params = {}, callback) ⇒ AWS.Request

Cancels the reprocessing of data through the pipeline.

createChannel(params = {}, callback) ⇒ AWS.Request

Used 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.

createDataset(params = {}, callback) ⇒ AWS.Request

Used to create a dataset. A dataset stores data retrieved from a data store by applying a queryAction (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.

createDatasetContent(params = {}, callback) ⇒ AWS.Request

Creates the content of a dataset by applying a queryAction (a SQL query) or a containerAction (executing a containerized application).

createDatastore(params = {}, callback) ⇒ AWS.Request

Creates a data store, which is a repository for messages.

createPipeline(params = {}, callback) ⇒ AWS.Request

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 a channel and a datastore activity and, optionally, as many as 23 additional activities in the pipelineActivities array.

deleteChannel(params = {}, callback) ⇒ AWS.Request

Deletes the specified channel.

deleteDataset(params = {}, callback) ⇒ AWS.Request

Deletes the specified dataset.

You do not have to delete the content of the dataset before you perform this operation.

deleteDatasetContent(params = {}, callback) ⇒ AWS.Request

Deletes the content of the specified dataset.

deleteDatastore(params = {}, callback) ⇒ AWS.Request

Deletes the specified data store.

deletePipeline(params = {}, callback) ⇒ AWS.Request

Deletes the specified pipeline.

describeChannel(params = {}, callback) ⇒ AWS.Request

Retrieves information about a channel.

describeDataset(params = {}, callback) ⇒ AWS.Request

Retrieves information about a dataset.

describeDatastore(params = {}, callback) ⇒ AWS.Request

Retrieves information about a data store.

describeLoggingOptions(params = {}, callback) ⇒ AWS.Request

Retrieves the current settings of the IoT Analytics logging options.

describePipeline(params = {}, callback) ⇒ AWS.Request

Retrieves information about a pipeline.

getDatasetContent(params = {}, callback) ⇒ AWS.Request

Retrieves the contents of a dataset as presigned URIs.

listChannels(params = {}, callback) ⇒ AWS.Request

Retrieves a list of channels.

listDatasetContents(params = {}, callback) ⇒ AWS.Request

Lists information about dataset contents that have been created.

listDatasets(params = {}, callback) ⇒ AWS.Request

Retrieves information about datasets.

listDatastores(params = {}, callback) ⇒ AWS.Request

Retrieves a list of data stores.

listPipelines(params = {}, callback) ⇒ AWS.Request

Retrieves a list of pipelines.

listTagsForResource(params = {}, callback) ⇒ AWS.Request

Lists the tags (metadata) that you have assigned to the resource.

putLoggingOptions(params = {}, callback) ⇒ AWS.Request

Sets or updates the IoT Analytics logging options.

If you update the value of any loggingOptions 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.

runPipelineActivity(params = {}, callback) ⇒ AWS.Request

Simulates the results of running a pipeline activity on a message payload.

sampleChannelData(params = {}, callback) ⇒ AWS.Request

Retrieves a sample of messages from the specified channel ingested during the specified timeframe. Up to 10 messages can be retrieved.

startPipelineReprocessing(params = {}, callback) ⇒ AWS.Request

Starts the reprocessing of raw message data through the pipeline.

tagResource(params = {}, callback) ⇒ AWS.Request

Adds to or modifies the tags of the given resource. Tags are metadata that can be used to manage a resource.

untagResource(params = {}, callback) ⇒ AWS.Request

Removes the given tags (metadata) from the resource.

updateChannel(params = {}, callback) ⇒ AWS.Request

Used to update the settings of a channel.

updateDataset(params = {}, callback) ⇒ AWS.Request

Updates the settings of a dataset.

updateDatastore(params = {}, callback) ⇒ AWS.Request

Used to update the settings of a data store.

updatePipeline(params = {}, callback) ⇒ AWS.Request

Updates the settings of a pipeline. You must specify both a channel and a datastore activity and, optionally, as many as 23 additional activities in the pipelineActivities array.