Using the advanced editor of the summary data mart wizard

The Advanced Editor of the summary data mart wizard is a JSON editor that includes the same values as of basic editor, but in the JSON format. You can view, add, and update the properties in this editor. While the Basic Editor includes all essential features to build a data mart, the Advanced Editor supports additional functionalities such as thresholds and tags. 

To launch the Advanced Editor, click Advanced Editor toggle button in the summary page of the data mart wizard. All properties and values that were defined in other pages of the Summary Data Mart wizard are displayed in the Advanced Editor. Any changes that you make in the Advanced Editor are saved and reflected in other pages of the Summary Data Mart wizard.

The Advanced Editor consists of the following fields:

data_mart_wizard_summary_advanced.png

1

Editor toggle

Use the toggle button to switch between the Basic and Advanced editors.

2

Editor pane

Use this pane to add or update the properties and their values.

3

Properties list

List of top level properties supported in the Advanced Editor.
When you click the property name, the code sample and documentation for that property is displayed.
If the property has sub properties, their details are also displayed.

You can copy the code sample to the editor and make the required changes.

data_mart_wizard_advanced_help.PNG

4

Search

Specify the property that you want to search for in the Advanced Editor.

5

Home

Home button to navigate back to the list of properties

To use the advanced editor

  1. In the summary page of the Summary Data Mart wizard, click Advanced Editor. 
    In the Editor pane, all properties and values that were defined in the other pages of summary data mart wizard are displayed.

  2. Review the properties and make the required changes:

    • Update the values of existing properties.
    • Add new properties:

      1. Search for the property in the help pane. 
      2. Copy the code sample. You can either copy entire sample, or drag and drop the desired code to the editor.
      3. Make the necessary modifications to the sample code.
  3. Click Apply. If you receive any validation errors, correct the code and click Apply again. 
    The changes you made to the advanced editor are saved and reflected in the basic editor.

Error handling

  • Syntax or schema errors:
    • As you add or modify properties in the editor, if there are any syntax or schema errors, they are displayed runtime and the Apply option is disabled. You must fix these issues to save the changes. 
  • Validation errors:
    • If you click Basic Editor or Close the editor without applying the changes, any changes made to the editor will be lost.
    • If you click Reset, any changes made to the editor in the current session will be lost.
      A warning message is displayed indicating the same.

Properties used in the editor

The following table lists the properties that can be used in the editor. While some properties can be configured in both basic and advanced editors, some properties are available in the advanced editor only.

Property > Sub property (Level 1) > Sub property (Level 2)

Description

Requirement

Available/editable in the advanced editor only?

name

Name of the data mart.

Click here to view the code sample
"name": "Virtual Clusters Overview"

Required


description

Description of the data mart.

Click here to view the code sample
"description": "Extract data for all virtual clusters"

Optional


structureid

Category of entity types to be included in the data mart. Specify SYS for System and WKLD for Business driver.

Click here to view the code sample

  "structureid": "SYS"

Required


entitytypenames

List of entity types for which to extract data. For details on all entity types, see Entity-types.

Click here to view the code sample

"entitytypenames": [
 "sys:cp:aix",
 "sys:cp:spp",
 "sys:vh:vmw"
 ]


Required


timefilter

Filter Used for specifying the time range of data extracted by the data mart. Four different types are supported.

Click here to view the code sample

"timefilter": {
 "type": "LASTEX",
 "lastex": {
 "period": "D",
 "quantity": 7,
 "include_current": false
 }
 }

Required


timefilter > type

Type of the time filter to be used in the data mart. You can include one of the following values:

  • GLOBAL: based on a global time filter configured in the Capacity Optimization console.
  • SINCE_TO: based on a period defined with a from and to dates
  • LASTEX: based on last hours, days, months, or years
  • ROLL: based on predefined roll periods

Required


timefilter > label

Label for the time filter.

Optional


timefilter > resolution

Resolution used for summarization of data saved in the metric store.

Optional


timefilter > globalfilterid

Unique identifier of the global time filter. You can check the list of available global filter IDs from Workspace > Filters. For details, see Managing-time-filters.

Required when type = GLOBAL

Optional


timefilter > since

Start date of the time range option (YYYY-MM-DD).  Required when type = SINCE_TO

Optional


timefilter > to

End date of the Time range option (YYYY-MM-DD). Required when type = SINCE_TO

Optional


timefilter > lastex

Time filter definition based on the last 'x' hours, days, months, or years. Required when type = LASTEX

Optional


timefilter > lastex > period

Type of last 'x' period.  period: "H" for hours, "D" for days, "M" for months or "Y" for years

Required


timefilter > lastex > quantity

Numeric value that specifies the last 'x' period to summarize.

Required


timefilter > lastex > includeCurrent

Indicates if the time filter includes the current date.

Required


columns

Detailed information for each column (metric) included in the data mart.

Click here to view the code sample

"columns": [
 {
 "name": "CPU_UTIL",
 "label": "CPU Utilization %",
 "description": "Percentage of time the CPU was not idle during the interval.",
 "resname": "CPU_UTIL",
 "type": "RESOURCE",
 "statistic": {
 "name": "AVGVALUE"
 },
 "sort_order": 1,
 "sort_direction": "DESC",
 "include_threshold_column": true
 }
 ]

Required


columns > type

Type used to distinguish metrics. Valid values are: GENERIC, RESOURCE, SUPPORTED_GROWTH, FORECAST_RESULTS, or TAG.

  • GENERIC: Used for entity ID, entity name, entity type etc. that are automatically generated by the wizard.  These columns should not be removed.
  • RESOURCE: Used for metrics and indicators.
  • SUPPORTED_GROWTH: Used for growth prediction results that are computed automatically for business drivers based on the resources of the associated service pools. Will be available only if the business driver metrics correlate with the service pool metrics.
  • FORECAST_RESULTS: Used for golden model forecast results that are available if the user has created a model in the workspace and promoted that to golden. The forecast could be for any time forecasting, extrapolation, or queuing network models.
  • TAG: Used for tag values.

Click here to view the example to add days to saturation indicator for BYFS metric by using Type as RESOURCE
{
      "name": "IND_DAYS_TO_SATURATION",
      "label": "Days to saturation",
      "description": "This value represents how many days left before a container will overcome its warning threshold",
      "statistic": {
        "name": "MAX"
      },
      "type": "RESOURCE",
      "resname": "IND_DAYS_TO_SATURATION",
      "sub_resnames": [
        "STORAGE"
      ],
      "ref_resource_name": "BYFS_NAME"
}
Click here to view the example for Golden models metric with Type as FORECAST_RESULTS

{
"name": "GM_CPU_UTIL", 
"label": "Golden model cpu util", 
"description": "Golden model cpu util", 
"statistics": ["DAYS_TO_SATURATION", "SATURATION_VALUE"],
"type": "FORECAST_RESULTS","resname":"CPU_UTIL" 

}
Click here to view the example for GM_BYENTITY metric for golden models

{
"name": "GM_BYENTITY_ID",
"label": "Golden Model byentity id",
"description": "Golden Model byentity id",
"type": "FORECAST_RESULTS",
"statistics": [
              "CAPACITY" <-- must be valid statistic(s) of the defined FORECAST_RESULTS metric (e.g. GM_CPU_UTIL)
               ],

"resname": "GM_BYENTITY_ID"
},

For a list of supported GM_BYENTITY metrics, see GM_BYENTITY metrics for golden models.

For a list of supported statistics for golden models, see Statistics for golden models.

Click here to view the example for Type as Supported Growth

{ 
"name": "SG_BOTTLENECK_RESOURCE",
 "label": "Bottleneck resource",
"description": "Business driver bottleneck resource",
"type": " SUPPORTED_GROWTH",
 "resname":"SG_BOTTLENECK_RESOURCE"
}

For a list of valid values for SUPPORTED GROWTH, see Metrics for SUPPORTED GROWTH.

Required


columns > name

Unique name used to identify the column in this data mart.

Required


columns > label

Label that can be used when displaying this column in the view or report.

Required


columns > description

Detailed description of the column. 

Required


columns > statistics

Specify multiple statistics for the column. It takes an array of comma-separated input values. The data mart result shows multiple values, one for each of the specified statistics.

The following statistics are available for an ID, string, configuration, and performance metric:

  • ID and string
    • Basic Editor: Value
    • Advanced Editor: VALUE
  • Configuration metric
    • Basic Editor: Last value, Maximum, Minimum
    • Advanced Editor: VALUE, LAST_VALUE, MIN, MAX
  • Performance metric
    • Basic Editor: Average, Count, Duration, Last value, Maximum, Minimum, Percentile 5, Percentile 10,  Percentile 25, Percentile 50, Percentile 75, Percentile 90, Percentile 95, Percentile 99, Slope, Standard Deviation, Sum
    • Advanced Editor: AVG, COUNT, COUNTERROR COUNTGOOD COUNTPOOR COUNTWARN, LAST_VALUE, MAX, MIN, PCT5, PCT10, PCT25, PCT50, PCT75, PCT90, PCT95, PCT99, SLOPE, STDDEV, SUM, VALUE

The following examples illustrate how to specify multiple statistics for the same metric in the summary data mart:

Example 1:
{
      "name": "CPU_READY",
      "label": "CPU Ready %",
      "description": "Percentage of time the CPU was in Ready state during the interval",
      "statistics": [
        "MAX",
        "AVG"
      ],
      "type": "RESOURCE",
      "resname": "CPU_READY"

}


Sample output:

statistics_dm_output.png

Example 2:
{
     "name": "CPU_UTIL",
     "label": "CPU Utilization %",
     "description": "Percentage of time the CPU was not idle during the interval",
      "statistics": [
        "MAX",
       "PCT 95"
      ],
      "type": "RESOURCE",
     "resname": "CPU_UTIL"

}

statistics_array_summary_data_mart.png

Optional


columns > statistic

Statistic to use in the summarized output. The basic editor lists the statistics available for each metric

Click here to view the code sample

"statistic": {
 "name": "AVGVALUE",
 "statid": 1
 }

Optional


columns > statistic > name

Name of the statistic. It represents a unique key with the statid field.

Required when statid is null.

Required


columns > statistic > statId

ID of the statistic. It represents a unique key with the name field.Required when the name is null.

Optional


columns > related_to

Used for identifying the name column corresponding to the unique ID column of the data mart.

Optional


columns > resname

Name of the resource (metric) in the catalog.

Optional


columns > sub_resnames

Name of the subresource (metric) in the catalog.

Optional


columns > tagtype

Name of the tag type in the catalog.

Click here to view the example

{
    //...
    "columns": [{
        "name": "Owner",
        "label": "Owner",
        "description": "The owner of the system.",
        "type": "TAG",
        "tagtype": "Owner"
    }]
}

Optional


columns > include_metadata

Name of the indicator metadata (metric) in the catalog.

Optional

Yes

columns > include_statistic_ts

Used to include the timestamp associated with the statistic. The column displays the time when the value has reached its peak for the first time in the given period. You can also verify the value by performing an analysis on the selected metric. This property is valid for MIN/MAX/PCTX statistics. The include_statistic_ts property cannot be used if the SLOPE statistic is selected.

Click here to view the example

{
      "name": "CPU_UTILMHZ",
      "label": "CPU Utilization in MHz",
      "description": "Average number of MHz the CPU was not idle during the interval",
      "statistics": [
        "MIN",
        "MAX",
        "PCT95"
        ],

      "type": "RESOURCE",
      "resname": "CPU_UTILMHZ",
      "include_statistic_ts":true
      }
 },

Optional

Yes

columns > ref_resource_name

Name of the referenced subresource (bymetric) column. It is applicable to indicator resnames only.

Optional

Yes

columns > parent_entity_type_name

Entity type of the parent or related entity to be extracted. To know the list of all entity types, see Entity-types.

Optional


columns > parent_relationship_id

Relationship of the parent or related entity to be extracted.

Optional


columns > include_threshold_column

Indicates whether to include thresholds for this column. Applicable only if column type is RESOURCE.

Click here to view the example

{
    //...
    "columns": [{
        "name": "CPU_UTIL",
        "label": "CPU Utilization %",
        "description": "Percentage of time the CPU was not idle during the interval.",
        "datatype": "NUMBER",
        "resname": "CPU_UTIL",
        "type": "RESOURCE",
        "unit": "PCT",
        "statistic": {
            "name": "AVGVALUE"
        },
        "includeThresholdColumn": true
    }]
}

Optional

Yes

columns > sort_order

Precedence order for column sorting.

Optional


columns > sort_direction

Direction to use for column sorting. You can include one of the following values:

  • ASC: For the ascending order
  • DESC: For the descending order

Optional


materializertask

Task used to materialize the content of the data mart.

Click here to view the code sample

"materializertask": {
 "taskid": 20
 }

Required


materializertask > taskid

Identifier of the task used to materialize the content of the data mart. It is recommended to select a materializer task name by using the Basic Editor.

Required


materializertask > name

Name of the materialization task used to materialize the content of the data mart. It is recommended to select a task name by using the Basic Editor.

Optional


materializertask > class_name

Class name of the materialization task used to materialize the content of the data mart.



entityfilterid

Unique identifier of the entity filter configured in the Workspace tab. A list of IDs is available from the Workspace -> Filters section. It is recommended to set the Entityfilter by using the Basic Editor.

Click here to view the code sample
"entityfilterid": 3

Optional


domain

Columns with domain information

Click here to view the code sample

"domain": {
 "include_parent": true,
 "parent_tags": [
 "tag_type_name1"
 ],
 "include_root_business_service": true,
 "root_business_service_tags": [
 "tag_type_name1"
 ],
 "include_root_application": true,
 "root_application_tags": [
 "tag_type_name1"
 ],
 "include_root_parent": true,
 "root_parent_tags": [
 "tag_type_name1"
 ]
 }

Optional

Yes

domain > include_parent

Columns with Parent Domain information

Optional

Yes

domain > parent_tags

List of parent tag type names

Optional

Yes

domain > parent_tag.macro

The parent tag macro schema for data mart summary

Optional

Yes

domain > root_parent_tag.macro

The root parent tag macro schema for data mart summary

Optional

Yes

domain > root_application_tag.macro

The root application tag macro schema for data mart summary

Optional

Yes

domain > root_business_service_tag.macro

The root business service tag macro schema for data mart summary

Optional

Yes

domain > include_root_business_service

Columns with root business service information

Optional

Yes

domain > root_business_service_tags

List of root business service tag type names

Optional

Yes

domain > include_root_application

Columns with root application information

Optional

Yes

domain > root_application_tags

List of root application tag type names

Optional

Yes

domain > include_root_parent

Columns with root domain information

Optional

Yes

domain > root_parent_tags

List of root parent tag type names

Optional

Yes

namespace

The virtual node namespace. Allowed values are opt:meas:vn and opt:meas

Click here to view the code sample
"namespace": "opt:meas:vn"

Optional

Yes

contextids

Used for specifying the scenario IDs of the golden model. This property is relevant only when the data mart is used for extracting metrics from the golden model results. Golden model results can be extracted using columns of "type": "FORECAST_RESULTS".

Scenario ID must be specified if the golden model contains multiple scenarios. If the model contains only one scenario, there is no need to specify the scenario ID.  

Click here to view the example

"contextids" : ["10",”12”], 

Optional

Yes

migration.fromerid

The erid of the SQL datamart that is being migrated.

Click here to view the code sample
  "migration.fromerid": 1100253

Optional

Yes

entitystatus

List of the statuses of the entity to be included in the data mart summary. You can decide whether to include or exclude entities with all statuses or with selected statuses.

Available status IDs are:

  • 1 - active
  • 2  - unassigned
  • 3 - newly discovered
  • 4 - dismissed


Click here to view the example

"entitystatus": [
    1,
    2,
    3,
    4
  ],

Optional


Metrics for SUPPORTED GROWTH

Metric

Description

SG_ABS_VAL

The absolute value of supported growth that is expressed in units SG_ABS_VAL_UNIT.

SG_ABS_VAL_CONF_LOW

The absolute value of the lower bound of the confidence band that is calculated for the supported growth.

SG_ABS_VAL_CONF_HIGH

The absolute value of the upper bound of the confidence band that is calculated for the supported growth.

SG_ABS_VAL_UNIT

The units in which the absolute value of SG_METRIC is expressed.

SG_REL_VAL

The relative value of the supported growth.

SG_REL_VAL_CONF_LOW

The relative value of the lower bound of the confidence band calculated for the supported growth.

SG_REL_VAL_CONF_HIGH

The relative value of the upper bound of the confidence band calculated for the supported growth.

SG_REL_VAL_UNIT

The units in which the relative value of SG_METRIC is expressed.

SG_BOTTLENECK_RESOURCE

The most constraining resource for the predicted value of supported growth.

Capacity metrics

SG_CAPACITY_VAL

Total capacity of the business driver metric that includes the supported growth.

SG_CAPACITY_UNIT

The units for the SG_CAPACITY_VAL metric.

SG_CAPACITY_OPERATOR

The value can be equal to or greater than indicating the meaning for the value specified in SG_CAPACITY_VAL.

Byentity metrics

SG_BYENTITY_ID

The entity ID of the service pool or deployment that is associated with the business service.

SG_BYENTITY_BOTTLENECK_RESOURCE

The most constraining resource by service pool or deployment for the predicted value of supported growth.

SG_BYENTITY_ABS_VAL

The absolute value of supported growth of a service pool or deployment that is expressed in units SG_BYENTITY_ABS_VAL_UNIT.

SG_BYENTITY_ABS_VAL_CONF_LOW

The absolute value of the lower bound of the confidence band of a service pool or deployment that is calculated for the supported growth.

SG_BYENTITY_ABS_VAL_CONF_HIGH

The absolute value of the upper bound of the confidence band of a service pool or deployment that is calculated for the supported growth.

SG_BYENTITY_ABS_VAL_UNIT

The units in which the absolute value of SG_BYENTITY_METRIC is expressed.

SG_BYENTITY_REL_VAL

The relative value of the supported growth for a service pool or deployment.

SG_BYENTITY_REL_VAL_CONF_LOW

The relative value of the lower bound of the confidence band calculated for the supported growth.

SG_BYENTITY_REL_VAL_CONF_HIGH

The relative value of the upper bound of the confidence band calculated for the supported growth.

SG_BYENTITY_REL_VAL_UNIT

The units in which the relative value of SG_BYENTITY_METRIC is expressed.

GM_BYENTITY metrics for golden models

The BYENTITY values are relative to the metrics, therefore, to use GM_BYENTITY_* one or more metric columns of type FORECAST_RESULTS must be defined and the statistics attribute must be set accordingly.

  • GM_BYENTITY_ID
  • GM_BYENTITY_RELIABILITY_RATIO
  • GM_BYENTITY_VAL
  • GM_BYENTITY_OPERATOR
  • GM_BYENTITY_UNIT
  • GM_FORECASTABLE
  • GM_REFERENCE_VAL
  • GM_BYENTITY_ABS_VAL
  • GM_BYENTITY_ABS_VAL_CONF_LOW
  • GM_BYENTITY_ABS_VAL_CONF_HIGH
  • GM_BYENTITY_ABS_VAL_UNIT
  • GM_BYENTITY_ABS_VAL_OPERATOR
  • GM_BYENTITY_REL_VAL
  • GM_BYENTITY_REL_VAL_CONF_LOW
  • GM_BYENTITY_REL_VAL_CONF_HIGH
  • GM_BYENTITY_REL_VAL_UNIT
  • GM_BYENTITY_REL_VAL_OPERATOR

Statistics for models

Model type

Type in Summary data mart

Name/Resname in Summary data mart column

Statistics

Are byEntity statistics supported?

Time Forecasting model

FORECAST_RESULTS

Select the metric(s) for which golden model has been created

  • DAYS_TO_SATURATION
  • DAYS_TO_SATURATION_UPPER_BOUND
  • SATURATION_VALUE
  • TREND
  • PEAK_VALUE
  • VALUE_30D
  • VALUE_60D
  • VALUE_90D
  • VALUE_120D
  • VALUE_180D
  • INPUT_SIZE
  • INPUT_VALID_SIZE
  • INPUT_SINCE_DAYS_AGO
  • INPUT_TO_DAYS_AGO

These statistics are associated with the metric specified in the data mart column.  It applies to all systems that are selected through summary data mart.

Four result columns (Value, Unit, Description, and Resolution) are generated per statistic selected. The names of the output columns are auto generated by adding appropriate suffixes.

No

Extrapolation model

FORECAST_RESULTS

Select the metric(s) for which golden model has been created

  • SUPPORTED_GROWTH
  • CAPACITY

These statistics are associated with the metric specified in the data mart column.  It applies to all systems that are selected through summary data mart.

Four result columns (Value, Unit , Description, Resolution) will be generated per statistic selected. The names of the output columns are auto generated by adding appropriate suffixes

Yes

Queuing Network model

FORECAST_RESULTS

Select the metric(s) for which golden model has been created

  • SUPPORTED_GROWTH
  • CAPACITY

These statistics are associated with the metric specified in the data mart column.  It applies to all systems that are selected through summary data mart.

Four result columns (Value, Unit , Description, Resolution) will be generated per statistic selected. The names of the output columns are auto generated by adding appropriate suffixes

No

Golden model



  • SUPPORTED_GROWTH: Residual capacity of a business driver related to correlated system utilization.
  • DAYS_TO_SATURATION: Estimated days to saturation.
  • DAYS_TO_SATURATION_UPPER_BOUND: Estimated days to saturation pessimistic.
  • CAPACITY: Estimated capacity (at different resolutions)
  • SATURATION_VALUE: Forecasted value at the saturation date
  • TREND: Estimated trend
  • PEAK_VALUE: Forecasted peak value
  • VALUE_30D: Forecasted value for 30 days from now.
  • VALUE_60D: Forecasted value for 60 days from now.
  • VALUE_90D: Forecasted value for 90 days from now
  • VALUE_120D: Forecasted value for 120 days from now.
  • VALUE_180D: Forecasted value for 180 days from now.
  • INPUT_SIZE: Input total size.
  • INPUT_VALID_SIZE: Input size of valid samples.
  • INPUT_SINCE_DAYS_AGO: Start date for input data as a difference from today.
  • INPUT_TO_DAYS_AGO: End date for input data as a difference from today.


 

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