
package Paws::IoTAnalytics;
  use Moose;
  sub service { 'iotanalytics' }
  sub signing_name { 'iotanalytics' }
  sub version { '2017-11-27' }
  sub flattened_arrays { 0 }
  has max_attempts => (is => 'ro', isa => 'Int', default => 5);
  has retry => (is => 'ro', isa => 'HashRef', default => sub {
    { base => 'rand', type => 'exponential', growth_factor => 2 }
  });
  has retriables => (is => 'ro', isa => 'ArrayRef', default => sub { [
  ] });

  with 'Paws::API::Caller', 'Paws::API::EndpointResolver', 'Paws::Net::V4Signature', 'Paws::Net::RestJsonCaller';

  
  sub BatchPutMessage {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::BatchPutMessage', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub CancelPipelineReprocessing {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::CancelPipelineReprocessing', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub CreateChannel {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::CreateChannel', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub CreateDataset {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::CreateDataset', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub CreateDatasetContent {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::CreateDatasetContent', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub CreateDatastore {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::CreateDatastore', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub CreatePipeline {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::CreatePipeline', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DeleteChannel {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DeleteChannel', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DeleteDataset {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DeleteDataset', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DeleteDatasetContent {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DeleteDatasetContent', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DeleteDatastore {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DeleteDatastore', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DeletePipeline {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DeletePipeline', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DescribeChannel {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DescribeChannel', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DescribeDataset {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DescribeDataset', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DescribeDatastore {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DescribeDatastore', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DescribeLoggingOptions {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DescribeLoggingOptions', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub DescribePipeline {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::DescribePipeline', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub GetDatasetContent {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::GetDatasetContent', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub ListChannels {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::ListChannels', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub ListDatasetContents {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::ListDatasetContents', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub ListDatasets {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::ListDatasets', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub ListDatastores {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::ListDatastores', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub ListPipelines {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::ListPipelines', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub ListTagsForResource {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::ListTagsForResource', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub PutLoggingOptions {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::PutLoggingOptions', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub RunPipelineActivity {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::RunPipelineActivity', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub SampleChannelData {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::SampleChannelData', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub StartPipelineReprocessing {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::StartPipelineReprocessing', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub TagResource {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::TagResource', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub UntagResource {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::UntagResource', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub UpdateChannel {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::UpdateChannel', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub UpdateDataset {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::UpdateDataset', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub UpdateDatastore {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::UpdateDatastore', @_);
    return $self->caller->do_call($self, $call_object);
  }
  sub UpdatePipeline {
    my $self = shift;
    my $call_object = $self->new_with_coercions('Paws::IoTAnalytics::UpdatePipeline', @_);
    return $self->caller->do_call($self, $call_object);
  }
  
  sub ListAllChannels {
    my $self = shift;

    my $callback = shift @_ if (ref($_[0]) eq 'CODE');
    my $result = $self->ListChannels(@_);
    my $next_result = $result;

    if (not defined $callback) {
      while ($next_result->nextToken) {
        $next_result = $self->ListChannels(@_, nextToken => $next_result->nextToken);
        push @{ $result->channelSummaries }, @{ $next_result->channelSummaries };
      }
      return $result;
    } else {
      while ($result->nextToken) {
        $callback->($_ => 'channelSummaries') foreach (@{ $result->channelSummaries });
        $result = $self->ListChannels(@_, nextToken => $result->nextToken);
      }
      $callback->($_ => 'channelSummaries') foreach (@{ $result->channelSummaries });
    }

    return undef
  }
  sub ListAllDatasetContents {
    my $self = shift;

    my $callback = shift @_ if (ref($_[0]) eq 'CODE');
    my $result = $self->ListDatasetContents(@_);
    my $next_result = $result;

    if (not defined $callback) {
      while ($next_result->nextToken) {
        $next_result = $self->ListDatasetContents(@_, nextToken => $next_result->nextToken);
        push @{ $result->datasetContentSummaries }, @{ $next_result->datasetContentSummaries };
      }
      return $result;
    } else {
      while ($result->nextToken) {
        $callback->($_ => 'datasetContentSummaries') foreach (@{ $result->datasetContentSummaries });
        $result = $self->ListDatasetContents(@_, nextToken => $result->nextToken);
      }
      $callback->($_ => 'datasetContentSummaries') foreach (@{ $result->datasetContentSummaries });
    }

    return undef
  }
  sub ListAllDatasets {
    my $self = shift;

    my $callback = shift @_ if (ref($_[0]) eq 'CODE');
    my $result = $self->ListDatasets(@_);
    my $next_result = $result;

    if (not defined $callback) {
      while ($next_result->nextToken) {
        $next_result = $self->ListDatasets(@_, nextToken => $next_result->nextToken);
        push @{ $result->datasetSummaries }, @{ $next_result->datasetSummaries };
      }
      return $result;
    } else {
      while ($result->nextToken) {
        $callback->($_ => 'datasetSummaries') foreach (@{ $result->datasetSummaries });
        $result = $self->ListDatasets(@_, nextToken => $result->nextToken);
      }
      $callback->($_ => 'datasetSummaries') foreach (@{ $result->datasetSummaries });
    }

    return undef
  }
  sub ListAllDatastores {
    my $self = shift;

    my $callback = shift @_ if (ref($_[0]) eq 'CODE');
    my $result = $self->ListDatastores(@_);
    my $next_result = $result;

    if (not defined $callback) {
      while ($next_result->nextToken) {
        $next_result = $self->ListDatastores(@_, nextToken => $next_result->nextToken);
        push @{ $result->datastoreSummaries }, @{ $next_result->datastoreSummaries };
      }
      return $result;
    } else {
      while ($result->nextToken) {
        $callback->($_ => 'datastoreSummaries') foreach (@{ $result->datastoreSummaries });
        $result = $self->ListDatastores(@_, nextToken => $result->nextToken);
      }
      $callback->($_ => 'datastoreSummaries') foreach (@{ $result->datastoreSummaries });
    }

    return undef
  }
  sub ListAllPipelines {
    my $self = shift;

    my $callback = shift @_ if (ref($_[0]) eq 'CODE');
    my $result = $self->ListPipelines(@_);
    my $next_result = $result;

    if (not defined $callback) {
      while ($next_result->nextToken) {
        $next_result = $self->ListPipelines(@_, nextToken => $next_result->nextToken);
        push @{ $result->pipelineSummaries }, @{ $next_result->pipelineSummaries };
      }
      return $result;
    } else {
      while ($result->nextToken) {
        $callback->($_ => 'pipelineSummaries') foreach (@{ $result->pipelineSummaries });
        $result = $self->ListPipelines(@_, nextToken => $result->nextToken);
      }
      $callback->($_ => 'pipelineSummaries') foreach (@{ $result->pipelineSummaries });
    }

    return undef
  }


  sub operations { qw/BatchPutMessage CancelPipelineReprocessing CreateChannel CreateDataset CreateDatasetContent CreateDatastore CreatePipeline DeleteChannel DeleteDataset DeleteDatasetContent DeleteDatastore DeletePipeline DescribeChannel DescribeDataset DescribeDatastore DescribeLoggingOptions DescribePipeline GetDatasetContent ListChannels ListDatasetContents ListDatasets ListDatastores ListPipelines ListTagsForResource PutLoggingOptions RunPipelineActivity SampleChannelData StartPipelineReprocessing TagResource UntagResource UpdateChannel UpdateDataset UpdateDatastore UpdatePipeline / }

1;

### main pod documentation begin ###

=head1 NAME

Paws::IoTAnalytics - Perl Interface to AWS AWS IoT Analytics

=head1 SYNOPSIS

  use Paws;

  my $obj = Paws->service('IoTAnalytics');
  my $res = $obj->Method(
    Arg1 => $val1,
    Arg2 => [ 'V1', 'V2' ],
    # if Arg3 is an object, the HashRef will be used as arguments to the constructor
    # of the arguments type
    Arg3 => { Att1 => 'Val1' },
    # if Arg4 is an array of objects, the HashRefs will be passed as arguments to
    # the constructor of the arguments type
    Arg4 => [ { Att1 => 'Val1'  }, { Att1 => 'Val2' } ],
  );

=head1 DESCRIPTION

AWS 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. AWS 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.

AWS IoT Analytics automates the steps required to analyze data from IoT
devices. AWS 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. AWS 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.

For the AWS API documentation, see L<https://docs.aws.amazon.com/goto/WebAPI/iotanalytics-2017-11-27>


=head1 METHODS

=head2 BatchPutMessage

=over

=item ChannelName => Str

=item Messages => ArrayRef[L<Paws::IoTAnalytics::Message>]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::BatchPutMessage>

Returns: a L<Paws::IoTAnalytics::BatchPutMessageResponse> instance

Sends messages to a channel.


=head2 CancelPipelineReprocessing

=over

=item PipelineName => Str

=item ReprocessingId => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::CancelPipelineReprocessing>

Returns: a L<Paws::IoTAnalytics::CancelPipelineReprocessingResponse> instance

Cancels the reprocessing of data through the pipeline.


=head2 CreateChannel

=over

=item ChannelName => Str

=item [ChannelStorage => L<Paws::IoTAnalytics::ChannelStorage>]

=item [RetentionPeriod => L<Paws::IoTAnalytics::RetentionPeriod>]

=item [Tags => ArrayRef[L<Paws::IoTAnalytics::Tag>]]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::CreateChannel>

Returns: a L<Paws::IoTAnalytics::CreateChannelResponse> instance

Creates a channel. A channel collects data from an MQTT topic and
archives the raw, unprocessed messages before publishing the data to a
pipeline.


=head2 CreateDataset

=over

=item Actions => ArrayRef[L<Paws::IoTAnalytics::DatasetAction>]

=item DatasetName => Str

=item [ContentDeliveryRules => ArrayRef[L<Paws::IoTAnalytics::DatasetContentDeliveryRule>]]

=item [LateDataRules => ArrayRef[L<Paws::IoTAnalytics::LateDataRule>]]

=item [RetentionPeriod => L<Paws::IoTAnalytics::RetentionPeriod>]

=item [Tags => ArrayRef[L<Paws::IoTAnalytics::Tag>]]

=item [Triggers => ArrayRef[L<Paws::IoTAnalytics::DatasetTrigger>]]

=item [VersioningConfiguration => L<Paws::IoTAnalytics::VersioningConfiguration>]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::CreateDataset>

Returns: a L<Paws::IoTAnalytics::CreateDatasetResponse> instance

Creates a dataset. A dataset stores data retrieved from a data store by
applying a C<queryAction> (a SQL query) or a C<containerAction>
(executing a containerized application). This operation creates the
skeleton of a dataset. The dataset can be populated manually by calling
C<CreateDatasetContent> or automatically according to a trigger you
specify.


=head2 CreateDatasetContent

=over

=item DatasetName => Str

=item [VersionId => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::CreateDatasetContent>

Returns: a L<Paws::IoTAnalytics::CreateDatasetContentResponse> instance

Creates the content of a data set by applying a C<queryAction> (a SQL
query) or a C<containerAction> (executing a containerized application).


=head2 CreateDatastore

=over

=item DatastoreName => Str

=item [DatastorePartitions => L<Paws::IoTAnalytics::DatastorePartitions>]

=item [DatastoreStorage => L<Paws::IoTAnalytics::DatastoreStorage>]

=item [FileFormatConfiguration => L<Paws::IoTAnalytics::FileFormatConfiguration>]

=item [RetentionPeriod => L<Paws::IoTAnalytics::RetentionPeriod>]

=item [Tags => ArrayRef[L<Paws::IoTAnalytics::Tag>]]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::CreateDatastore>

Returns: a L<Paws::IoTAnalytics::CreateDatastoreResponse> instance

Creates a data store, which is a repository for messages. Only data
stores that are used to save pipeline data can be configured with
C<ParquetConfiguration>.


=head2 CreatePipeline

=over

=item PipelineActivities => ArrayRef[L<Paws::IoTAnalytics::PipelineActivity>]

=item PipelineName => Str

=item [Tags => ArrayRef[L<Paws::IoTAnalytics::Tag>]]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::CreatePipeline>

Returns: a L<Paws::IoTAnalytics::CreatePipelineResponse> instance

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


=head2 DeleteChannel

=over

=item ChannelName => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DeleteChannel>

Returns: nothing

Deletes the specified channel.


=head2 DeleteDataset

=over

=item DatasetName => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DeleteDataset>

Returns: nothing

Deletes the specified dataset.

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


=head2 DeleteDatasetContent

=over

=item DatasetName => Str

=item [VersionId => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DeleteDatasetContent>

Returns: nothing

Deletes the content of the specified dataset.


=head2 DeleteDatastore

=over

=item DatastoreName => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DeleteDatastore>

Returns: nothing

Deletes the specified data store.


=head2 DeletePipeline

=over

=item PipelineName => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DeletePipeline>

Returns: nothing

Deletes the specified pipeline.


=head2 DescribeChannel

=over

=item ChannelName => Str

=item [IncludeStatistics => Bool]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DescribeChannel>

Returns: a L<Paws::IoTAnalytics::DescribeChannelResponse> instance

Retrieves information about a channel.


=head2 DescribeDataset

=over

=item DatasetName => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DescribeDataset>

Returns: a L<Paws::IoTAnalytics::DescribeDatasetResponse> instance

Retrieves information about a dataset.


=head2 DescribeDatastore

=over

=item DatastoreName => Str

=item [IncludeStatistics => Bool]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DescribeDatastore>

Returns: a L<Paws::IoTAnalytics::DescribeDatastoreResponse> instance

Retrieves information about a data store.


=head2 DescribeLoggingOptions


Each argument is described in detail in: L<Paws::IoTAnalytics::DescribeLoggingOptions>

Returns: a L<Paws::IoTAnalytics::DescribeLoggingOptionsResponse> instance

Retrieves the current settings of the AWS IoT Analytics logging
options.


=head2 DescribePipeline

=over

=item PipelineName => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::DescribePipeline>

Returns: a L<Paws::IoTAnalytics::DescribePipelineResponse> instance

Retrieves information about a pipeline.


=head2 GetDatasetContent

=over

=item DatasetName => Str

=item [VersionId => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::GetDatasetContent>

Returns: a L<Paws::IoTAnalytics::GetDatasetContentResponse> instance

Retrieves the contents of a data set as presigned URIs.


=head2 ListChannels

=over

=item [MaxResults => Int]

=item [NextToken => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::ListChannels>

Returns: a L<Paws::IoTAnalytics::ListChannelsResponse> instance

Retrieves a list of channels.


=head2 ListDatasetContents

=over

=item DatasetName => Str

=item [MaxResults => Int]

=item [NextToken => Str]

=item [ScheduledBefore => Str]

=item [ScheduledOnOrAfter => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::ListDatasetContents>

Returns: a L<Paws::IoTAnalytics::ListDatasetContentsResponse> instance

Lists information about data set contents that have been created.


=head2 ListDatasets

=over

=item [MaxResults => Int]

=item [NextToken => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::ListDatasets>

Returns: a L<Paws::IoTAnalytics::ListDatasetsResponse> instance

Retrieves information about data sets.


=head2 ListDatastores

=over

=item [MaxResults => Int]

=item [NextToken => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::ListDatastores>

Returns: a L<Paws::IoTAnalytics::ListDatastoresResponse> instance

Retrieves a list of data stores.


=head2 ListPipelines

=over

=item [MaxResults => Int]

=item [NextToken => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::ListPipelines>

Returns: a L<Paws::IoTAnalytics::ListPipelinesResponse> instance

Retrieves a list of pipelines.


=head2 ListTagsForResource

=over

=item ResourceArn => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::ListTagsForResource>

Returns: a L<Paws::IoTAnalytics::ListTagsForResourceResponse> instance

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


=head2 PutLoggingOptions

=over

=item LoggingOptions => L<Paws::IoTAnalytics::LoggingOptions>


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::PutLoggingOptions>

Returns: nothing

Sets or updates the AWS IoT Analytics logging options.

If you update the value of any C<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 C<roleArn> field (for
example, to correct an invalid policy), it takes up to five minutes for
that change to take effect.


=head2 RunPipelineActivity

=over

=item Payloads => ArrayRef[Str|Undef]

=item PipelineActivity => L<Paws::IoTAnalytics::PipelineActivity>


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::RunPipelineActivity>

Returns: a L<Paws::IoTAnalytics::RunPipelineActivityResponse> instance

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


=head2 SampleChannelData

=over

=item ChannelName => Str

=item [EndTime => Str]

=item [MaxMessages => Int]

=item [StartTime => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::SampleChannelData>

Returns: a L<Paws::IoTAnalytics::SampleChannelDataResponse> instance

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


=head2 StartPipelineReprocessing

=over

=item PipelineName => Str

=item [ChannelMessages => L<Paws::IoTAnalytics::ChannelMessages>]

=item [EndTime => Str]

=item [StartTime => Str]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::StartPipelineReprocessing>

Returns: a L<Paws::IoTAnalytics::StartPipelineReprocessingResponse> instance

Starts the reprocessing of raw message data through the pipeline.


=head2 TagResource

=over

=item ResourceArn => Str

=item Tags => ArrayRef[L<Paws::IoTAnalytics::Tag>]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::TagResource>

Returns: a L<Paws::IoTAnalytics::TagResourceResponse> instance

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


=head2 UntagResource

=over

=item ResourceArn => Str

=item TagKeys => ArrayRef[Str|Undef]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::UntagResource>

Returns: a L<Paws::IoTAnalytics::UntagResourceResponse> instance

Removes the given tags (metadata) from the resource.


=head2 UpdateChannel

=over

=item ChannelName => Str

=item [ChannelStorage => L<Paws::IoTAnalytics::ChannelStorage>]

=item [RetentionPeriod => L<Paws::IoTAnalytics::RetentionPeriod>]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::UpdateChannel>

Returns: nothing

Updates the settings of a channel.


=head2 UpdateDataset

=over

=item Actions => ArrayRef[L<Paws::IoTAnalytics::DatasetAction>]

=item DatasetName => Str

=item [ContentDeliveryRules => ArrayRef[L<Paws::IoTAnalytics::DatasetContentDeliveryRule>]]

=item [LateDataRules => ArrayRef[L<Paws::IoTAnalytics::LateDataRule>]]

=item [RetentionPeriod => L<Paws::IoTAnalytics::RetentionPeriod>]

=item [Triggers => ArrayRef[L<Paws::IoTAnalytics::DatasetTrigger>]]

=item [VersioningConfiguration => L<Paws::IoTAnalytics::VersioningConfiguration>]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::UpdateDataset>

Returns: nothing

Updates the settings of a data set.


=head2 UpdateDatastore

=over

=item DatastoreName => Str

=item [DatastoreStorage => L<Paws::IoTAnalytics::DatastoreStorage>]

=item [FileFormatConfiguration => L<Paws::IoTAnalytics::FileFormatConfiguration>]

=item [RetentionPeriod => L<Paws::IoTAnalytics::RetentionPeriod>]


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::UpdateDatastore>

Returns: nothing

Updates the settings of a data store.


=head2 UpdatePipeline

=over

=item PipelineActivities => ArrayRef[L<Paws::IoTAnalytics::PipelineActivity>]

=item PipelineName => Str


=back

Each argument is described in detail in: L<Paws::IoTAnalytics::UpdatePipeline>

Returns: nothing

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


=head1 PAGINATORS

Paginator methods are helpers that repetively call methods that return partial results

=head2 ListAllChannels(sub { },[MaxResults => Int, NextToken => Str])

=head2 ListAllChannels([MaxResults => Int, NextToken => Str])


If passed a sub as first parameter, it will call the sub for each element found in :

 - channelSummaries, passing the object as the first parameter, and the string 'channelSummaries' as the second parameter 

If not, it will return a a L<Paws::IoTAnalytics::ListChannelsResponse> instance with all the C<param>s;  from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.


=head2 ListAllDatasetContents(sub { },DatasetName => Str, [MaxResults => Int, NextToken => Str, ScheduledBefore => Str, ScheduledOnOrAfter => Str])

=head2 ListAllDatasetContents(DatasetName => Str, [MaxResults => Int, NextToken => Str, ScheduledBefore => Str, ScheduledOnOrAfter => Str])


If passed a sub as first parameter, it will call the sub for each element found in :

 - datasetContentSummaries, passing the object as the first parameter, and the string 'datasetContentSummaries' as the second parameter 

If not, it will return a a L<Paws::IoTAnalytics::ListDatasetContentsResponse> instance with all the C<param>s;  from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.


=head2 ListAllDatasets(sub { },[MaxResults => Int, NextToken => Str])

=head2 ListAllDatasets([MaxResults => Int, NextToken => Str])


If passed a sub as first parameter, it will call the sub for each element found in :

 - datasetSummaries, passing the object as the first parameter, and the string 'datasetSummaries' as the second parameter 

If not, it will return a a L<Paws::IoTAnalytics::ListDatasetsResponse> instance with all the C<param>s;  from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.


=head2 ListAllDatastores(sub { },[MaxResults => Int, NextToken => Str])

=head2 ListAllDatastores([MaxResults => Int, NextToken => Str])


If passed a sub as first parameter, it will call the sub for each element found in :

 - datastoreSummaries, passing the object as the first parameter, and the string 'datastoreSummaries' as the second parameter 

If not, it will return a a L<Paws::IoTAnalytics::ListDatastoresResponse> instance with all the C<param>s;  from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.


=head2 ListAllPipelines(sub { },[MaxResults => Int, NextToken => Str])

=head2 ListAllPipelines([MaxResults => Int, NextToken => Str])


If passed a sub as first parameter, it will call the sub for each element found in :

 - pipelineSummaries, passing the object as the first parameter, and the string 'pipelineSummaries' as the second parameter 

If not, it will return a a L<Paws::IoTAnalytics::ListPipelinesResponse> instance with all the C<param>s;  from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.


=head1 SEE ALSO

This service class forms part of L<Paws>

=head1 BUGS and CONTRIBUTIONS

The source code is located here: L<https://github.com/pplu/aws-sdk-perl>

Please report bugs to: L<https://github.com/pplu/aws-sdk-perl/issues>

=cut