describe_dimension_keys ¶

def describe_dimension_keys(
    self,
    service_type: "capo_pi.types.service_type.ServiceType",
    identifier: "capo_pi.types.identifier_string.IdentifierString",
    start_time: "capo_pi.types.iso_timestamp.ISOTimestamp",
    end_time: "capo_pi.types.iso_timestamp.ISOTimestamp",
    metric: "capo_pi.types.request_string.RequestString",
    group_by: "capo_pi.types.dimension_group.DimensionGroup",
    *,
    config_overrides: Optional[PIClientConfig] = None,
    period_in_seconds: Optional["capo_pi.types.integer.Integer"] = None,
    additional_metrics: Optional[
        "capo_pi.types.additional_metrics_list.AdditionalMetricsList"
    ] = None,
    partition_by: Optional["capo_pi.types.dimension_group.DimensionGroup"] = None,
    filter: Optional[
        "capo_pi.types.metric_query_filter_map.MetricQueryFilterMap"
    ] = None,
    max_results: Optional["capo_pi.types.max_results.MaxResults"] = None,
    next_token: Optional["capo_pi.types.next_token.NextToken"] = None,
) -> "capo_pi.types.describe_dimension_keys_response.DescribeDimensionKeysResponse":
    """<p>For a specific time period, retrieve the top <code>N</code> dimension keys for a metric. </p> <note> <p>Each response element returns a maximum of 500 bytes. For larger elements, such as SQL statements, only the first 500 bytes are returned.</p> </note>

    Args:
        service_type: <p>The Amazon Web Services service for which Performance Insights will return metrics. Valid values are as follows:</p> <ul> <li> <p> <code>RDS</code> </p> </li> <li> <p> <code>DOCDB</code> </p> </li> </ul>
        identifier: <p>An immutable, Amazon Web Services Region-unique identifier for a data source. Performance Insights gathers metrics from this data source.</p> <p>To use an Amazon RDS instance as a data source, you specify its <code>DbiResourceId</code> value. For example, specify <code>db-FAIHNTYBKTGAUSUZQYPDS2GW4A</code>. </p>
        start_time: <p>The date and time specifying the beginning of the requested time series data. You must specify a <code>StartTime</code> within the past 7 days. The value specified is <i>inclusive</i>, which means that data points equal to or greater than <code>StartTime</code> are returned. </p> <p>The value for <code>StartTime</code> must be earlier than the value for <code>EndTime</code>. </p>
        end_time: <p>The date and time specifying the end of the requested time series data. The value specified is <i>exclusive</i>, which means that data points less than (but not equal to) <code>EndTime</code> are returned.</p> <p>The value for <code>EndTime</code> must be later than the value for <code>StartTime</code>.</p>
        metric: <p>The name of a Performance Insights metric to be measured.</p> <p>Valid values for <code>Metric</code> are:</p> <ul> <li> <p> <code>db.load.avg</code> - A scaled representation of the number of active sessions for the database engine. </p> </li> <li> <p> <code>db.sampledload.avg</code> - The raw number of active sessions for the database engine. </p> </li> </ul> <p>If the number of active sessions is less than an internal Performance Insights threshold, <code>db.load.avg</code> and <code>db.sampledload.avg</code> are the same value. If the number of active sessions is greater than the internal threshold, Performance Insights samples the active sessions, with <code>db.load.avg</code> showing the scaled values, <code>db.sampledload.avg</code> showing the raw values, and <code>db.sampledload.avg</code> less than <code>db.load.avg</code>. For most use cases, you can query <code>db.load.avg</code> only. </p>
        period_in_seconds: <p>The granularity, in seconds, of the data points returned from Performance Insights. A period can be as short as one second, or as long as one day (86400 seconds). Valid values are: </p> <ul> <li> <p> <code>1</code> (one second)</p> </li> <li> <p> <code>60</code> (one minute)</p> </li> <li> <p> <code>300</code> (five minutes)</p> </li> <li> <p> <code>3600</code> (one hour)</p> </li> <li> <p> <code>86400</code> (twenty-four hours)</p> </li> </ul> <p>If you don't specify <code>PeriodInSeconds</code>, then Performance Insights chooses a value for you, with a goal of returning roughly 100-200 data points in the response. </p>
        group_by: <p>A specification for how to aggregate the data points from a query result. You must specify a valid dimension group. Performance Insights returns all dimensions within this group, unless you provide the names of specific dimensions within this group. You can also request that Performance Insights return a limited number of values for a dimension. </p>
        additional_metrics: <p>Additional metrics for the top <code>N</code> dimension keys. If the specified dimension group in the <code>GroupBy</code> parameter is <code>db.sql_tokenized</code>, you can specify per-SQL metrics to get the values for the top <code>N</code> SQL digests. The response syntax is as follows: <code>"AdditionalMetrics" : { "<i>string</i>" : "<i>string</i>" }</code>.</p> <p>The only supported statistic function is <code>.avg</code>.</p>
        partition_by: <p>For each dimension specified in <code>GroupBy</code>, specify a secondary dimension to further subdivide the partition keys in the response. </p>
        filter: <p>One or more filters to apply in the request. Restrictions:</p> <ul> <li> <p>Any number of filters by the same dimension, as specified in the <code>GroupBy</code> or <code>Partition</code> parameters.</p> </li> <li> <p>A single filter for any other dimension in this dimension group.</p> </li> </ul> <note> <p>The <code>db.sql.db_id</code> filter isn't available for RDS for SQL Server DB instances.</p> </note>
        max_results: <p>The maximum number of items to return in the response. If more items exist than the specified <code>MaxRecords</code> value, a pagination token is included in the response so that the remaining results can be retrieved. </p>
        next_token: <p>An optional pagination token provided by a previous request. If this parameter is specified, the response includes only records beyond the token, up to the value specified by <code>MaxRecords</code>.</p>

    Raises:
        capo_pi.errors.internal_service_error.InternalServiceError: <p>The request failed due to an unknown error.</p>
        capo_pi.errors.invalid_argument_exception.InvalidArgumentException: <p>One of the arguments provided is invalid for this request.</p>
        capo_pi.errors.not_authorized_exception.NotAuthorizedException: <p>The user is not authorized to perform this request.</p>
        capo_pi.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_pi.types.describe_dimension_keys_request.DescribeDimensionKeysRequest]",
    ) -> OperationResponse[
        "capo_pi.types.describe_dimension_keys_response.DescribeDimensionKeysResponse"
    ]:
        import capo_pi._operations.performance_insightsv20180227.describe_dimension_keys

        output, http_response = (
            capo_pi._operations.performance_insightsv20180227.describe_dimension_keys.describe_dimension_keys(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DescribeDimensionKeys")
    )
    input_: capo_pi.types.describe_dimension_keys_request.DescribeDimensionKeysRequest = {
        "service_type": service_type,
        "identifier": identifier,
        "start_time": start_time,
        "end_time": end_time,
        "metric": metric,
        "group_by": group_by,
    }
    if period_in_seconds is not None:
        input_["period_in_seconds"] = period_in_seconds
    if additional_metrics is not None:
        input_["additional_metrics"] = additional_metrics
    if partition_by is not None:
        input_["partition_by"] = partition_by
    if filter is not None:
        input_["filter"] = filter
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output