Advanced settings for custom fields
eazyBI for Jira

You can use eazyBI advanced settings (available only to Jira system administrators, Jira trusted users, and eazyBI admins) to add support for additional Jira custom fields as well as modify import options for standard custom fields.

eazyBI advanced settings are defined using the TOML format.

On this page:

Additional custom fields

If you would like to import in eazyBI an additional Jira custom field with a custom field type that is not supported by default, then you can add a definition of how this custom field should be imported. Also, if some default custom field settings should be changed, then it can be done by adding the necessary custom field configuration parameters.

If you need to change a default custom field settings in a single eazyBI account, you can edit the custom field import options in the specific account. The option is available in eazyBI for Jira Cloud and starting from version 6.6.0

At first, you need to find out Jira custom field ID. You can see the custom field ID when you hover over the custom field name in the eazyBI import settings. Also, in Jira Data Center you can see a custom field ID in the URL when entering the Configuration screen of this field. For example, if the end of the URL is ...admin/ConfigureCustomField!default.jspa?customFieldId=10100, the field ID is 10100.

Then add the following line to advanced settings:

[jira.customfield_NNNNN]

where NNNNN is the custom field ID. This will start the block of configuration parameters for the NNNNN custom field. After that line, specify the data type of this field:

data_type = "string"

By default, the string maximum length is 255 characters. If there is a need to import longer string values, then use an additional setting limit and specify the maximum length.
Other available types are text, integer, decimal, date, datetime.

If you use the decimal data type, then by default the precision (maximum number of digits) is 15 and the scale (digits after the decimal point) is 2. You can change these defaults with additional precision and scale settings.

If you would like to import a custom field as an additional dimension add the setting dimension. Note you can import only string, integer, and decimal data types as dimensions.

dimension = true

If the custom field can contain multiple values for a single issue, then add

multiple_values = true

If the custom field returns a string with comma-separated values (see example definition of calculated text field) which should be imported as multiple values then add also (note that multiple values can be provided with another delimiter, please, use the appropriate character in this setting):

split_by = ","

If you would like to import a numeric custom field as a measure add the setting measure. Note you can import only integer, decimal, date, and date-time data types as measures.

measure = true

Here is an example of a custom string type dimension definition:

[jira.customfield_10100]
data_type = "string"
dimension = true

Add additional custom field definitions as needed [1] in the advanced settings text area field and then click Update advanced settings [2].

Finally, go to eazyBI import options, tab Custom fields, and select your newly defined custom field for import.

Multi-Level custom field import

For the custom field that is created using the Multi-Level Cascading Select plugin, please add the following advanced options

[jira.customfield_NNNNN]
data_type = "string"
dimension = true
levels = ["Level 1", "Level 2"]

In levels settings, define the number of levels that are used in the multi-level cascading select custom field configuration (you can use custom level names instead of "Level 1", "Level 2"). Level names should be unique and it should cover the maximum depth of the custom field context. For example, if your custom field has values split into 5 levels, you would need to define up to Level 5.

In addition, the following option can be added if the (none) member should be created at all parent levels. By default, this option is set to false and only one (none) member is created at the first highest level.

none_member_all_levels = true

Interval dimension

You can import a numeric custom field as an interval dimension. For example, if you would like to import the "Story Points" dimension that groups issues by story points intervals, then add the following advanced settings (where NNNNN is the Story points custom field ID) :

[jira.customfield_NNNNN]
dimension = true
intervals = "/5"

The above specifies that the "Story Points" custom field should be imported as an interval dimension and should group Story point values in the intervals or ranges of 5. This is the default interval, after import, it can be edited from "All Hierarchy level members" in the new Story Points dimension.

Import Epic name as a dimension

If a text type custom field could be used for grouping data, you can import this custom field as a dimension and also pass its value down to the issue hierarchy.

A good example is an Epic Name that is assigned only to epic issues but is quite handy to group data and aggregate metrics in reports. Add parameter dimension to enable dimension creation and parameter update_from_issue_key to pass down the epic name to issues down the hierarchy.

[jira.customfield_NNNNN]
data_type = "string"
dimension = true
update_from_issue_key = "epic_key"

Import changes of custom field dimensions

By default, you can enable changes of the standard Transition Status and Assignee dimensions as well as the changes of the Jira Agile Sprint dimension to be imported. See the documentation on how to enable and use Issues history and other measures that can be used to get the historical issue status.

Option 'Import issue change history' should be enabled prior to enabling value change import for any custom field dimension.

It is possible to import changes also of other single value custom field dimensions. Please add additional separate_table and changes advanced settings for these custom fields:

[jira.customfield_NNNNN]
data_type = "string"
dimension = true
separate_table = true
changes = true

Here you can't rename the field using name = "new name"as the change history would not work as expected for renamed fields.

When settings are saved, go to eazyBI import options, tab Custom fields, and select Import as dimension and Import value changes option for this custom field. After the import, you can use the Issues history measure with this dimension and Time dimension to see how many issues had the historical custom field value at the end of the corresponding Time period. Or use hidden Transitions to measure to analyze transitions and see the historical value of this custom field at the time when the transition was performed.

Please import value changes only for the custom field dimensions where it is really necessary. Import of each additional custom field dimension value change increases the size of the eazyBI database.

Value change import of scripted custom fields (i.e. Jira Misc, ScriptRunner scripted custom fields) is not available in eazyBI because value changes of those custom fields are not represented in issues history.

Import changelog string value

Some additional custom field types store just an ID of the selected value and then use additional lookup functionality to show a display value that corresponds to this ID value. If you have added such a custom field in the advanced settings and after the import, in the eazyBI, you see just an ID value, then this could be the cause for that. In this case please check in the Jira issue page History tab if you see the display value of this custom field when the change is made. If yes, then add get_changelog_string option in the advanced settings and re-import this custom field in eazyBI and now the custom field display values should be imported in eazyBI.

[jira.customfield_NNNNN]
data_type = "string"
dimension = true
get_changelog_string = true

Troubleshooting

Whenever you change the advanced settings for a custom field, it is recommended to perform double data import for the field to ensure the correct outcome of changes.

First, run the import with the custom field un-checked to clear the previously loaded custom field configuration. The second time, run the import with the custom field checked to load it again.

List of all settings

Here is the list of all available custom field advanced settings:

Setting	Available values	Default value	Description
changes	`true` or `false`	`false`	Specify `true` for the single value string data type separate table dimensions (see `separate_table` below) if you would like to see the historical custom field value with Issues history measure. Please also select the Import issue change history option when doing the Jira import.
check_calculated_value	`true` or `false`	`false`	Can be used for the import of Jira scripted custom fields (for example, Jira MISC, ScriptRunner) which can return a different value even when the `updated` date and time of the issue have not changed. By default, the incremental import will re-import only those issues which are created or updated since the last import. If you set this setting to `true`, then for all issues this custom field value will be checked if it has not changed since the last import and will re-import this field value if it is changed. Enabling this setting for scripted custom fields can make the import slower as during the import the calculation will be performed for all issues. This parameter `check_calculated_value` does not work for calculated JavaScript custom fields
csv_dimension	`true` or `false`	`false`	Can be used with custom fields that have `dimension` and `multiple_values` enabled. If enabled then additional Custom field CSV dimension will be created where used combinations of values (as comma-separated string) will be imported. For example, if an issue has a custom field with values one and two, then in the multiple values dimension Custom field two separate members (one and two) will be created and the corresponding measure values for this issue will be stored for each of these members. If `csv_dimension` is enabled, then in the Custom field CSV dimension one member with comma-separated values (one, two) will be created and the corresponding measure values will be stored for this member. You can use this additional CSV dimension if you want to filter measure values for issues that have both values in the custom field.
data_type	`"string"` `"text"` `"integer"` `"decimal"` `"date"` `"datetime"`		Specify the data type of the custom field value and that should be stored in eazyBI. Use `string` for limited length strings (the default `limit` is 255) or `text` for large text properties (do not use `text` when enabling `dimension`). Use `integer` and `decimal` for numeric values. Specify `precision` (default 15) and `scale` (default 2) for decimals, if you want to change the defaults. Use `date` for date values without the time and `datetime` for dates with time.
dimension	`true` or `false`	`false`	Enable custom field import as a dimension. Enable only for list-of-values custom field types and not for custom fields that have unique values for each issue. This setting is supported only for data type `string`, `integer`, or `decimal`.
get_changelog_string	`true` or `false`	`false`	Some custom fields return numeric ID values as their default values, but you would like to import the corresponding string display value in eazyBI. In these cases quite often custom fields also provide string representation which is stored in the issue changelog (check Jira if you see the string values in the issue history when you change this custom field value). If the changelog string value is available for this custom field then enable import of this string value in eazyBI.
intervals	String with default interval ranges		If you want to import ranges of numeric values as an interval dimension, then specify the default intervals (for example, `"/10"`).
interval_unit	`"seconds"` `"minutes"` `"hours"` `"days"`		If the custom field returns a time interval value, then specify the default time unit for the `intervals` range (for example, if `"days"` is specified then `intervals` with the value `"/10"` means that time intervals for every 10 days should be created).
javascript_code			If you create a new JavaScript calculated custom field, then specify the JavaScript code in this setting.
json_fields	["customfieldID"]		This line is mandatory if you use Javascript to calculate the field with a reference to another custom field that is not being selected for import itself. This parameter `json_fields` works on eazyBI for Jira Cloud and starting with eazyBI for Jira Data Center 7.1. version
levels	Array with strings		If the custom field should be imported as a multi-level dimension then specify an array with level names (for example, `["Level 1", "Level 2"]`). The custom field value should be an array with values for each level. If the custom field value is a concatenated string, then specify `split_by` that should be used to split a string into an array of strings. See also the `none_member_all_levels` setting. See the Advanced settings for custom fields example above as well as the Scripted field example.
limit	Integer limit value	`255` for strings	Increase the `string` datatype limit if needed.
measure	`true` or `false`	`false`	Enable custom field import as a measure. Please enable only for `integer`, `decimal`, `date`, or `datetime` data types. See Jira custom fields for more information about numeric and date custom fields import as measures.
multiple_dates	`true` or `false`	`false`	Enable custom measure import with numeric values for several dates. The custom field should return multiple lines where each line is in the format `YYYY-MM-DD,numeric_value`. See the numeric measure with multiple dates example.
multiple_dimensions	Array with dimension names.		Enable custom measure import with numeric values for several dimension combinations. Specify the list of dimension names that each line will return (for example, `["Time", "Assignee"]`). Each line of the custom field value should be in the format `dimension1_key,...,dimensionN_key,numeric_value` (for example, `2015-09-27,john.smith,123` for the previous dimension names list example). If you want to use custom field dimensions then only single-value `separate_table` dimensions (see below) can be used. Multi-level and cascading field dimensions are not supported.
multiple_values	`true` or `false`	`false`	Enable if the custom field returns several values for one issue (an array of values) instead of a single value. If the custom field value is a concatenated string, then specify `split_by` that should be used to split a string into an array of strings. Works for custom fields with string data type. The parameter is not supported for custom fields with decimal or integer data.
name	String with a custom field name		Specify the custom field name when defining a new JavaScript calculated custom field.
none_member_all_levels	`true` or `false`	`false`	Enable the (none) member creation at all parent levels of a custom dimension with several `levels`. By default, only one (none) member is created at the first highest level.
precision	Integer precision value	`15` for decimals	Specify the precision (total max number of digits) of the decimal data type.
properties_from_dimension	`"Issue"`		imports all properties from "Issue" dimension to field that contains issue-key (for example single-issue picker field imported in eazyBI as dimension). See example All Links.
scale	Integer scale value	`2` for decimals	Specify the scale (max number of digits after the decimal point) of the decimal data type.
separate_table	`true` or `false`	`false`	By default, single-value custom dimensions are stored in the Jira issues table in the eazyBI database. If you want to upload additional measures for these custom dimensions or if you want to use it in the list of `multiple_dimensions` names, then enable this setting and re-import Jira issues into eazyBI. After that, a separate dimension table with the dimension members' values will be created in the eazyBI database. Works for single-value custom fields only. The parameter is not supported for custom fields with decimal or integer data.
split_by	String separator value		When `levels` or `multiple_values` settings are enabled, but the custom field returns a concatenated string then specify the separator that should be used to split the string value into an array. For example, if `split_by` is set to `","` then the custom field value `"a,b,c"` is split into the array `["a","b","c"]`.
time_interval	`"age"` `"duration"`		If the interval dimension is for a duration, then specify `"duration"` and the custom field value should be the difference between two dates in `time_unit`. If the interval dimension is for an age, then specify `"age"` and the custom field value should be a Unix timestamp (number of `time_unit` since January 1, 1970).
time_unit	`"seconds"` `"minutes"` `"hours"` `"days"`		If the custom field returns a time interval value, then specify the time unit for this value. This time unit will be used to convert the time value into the corresponding `interval_unit` and then to find the corresponding `intervals` range. See the example of a custom calculated field as an interval dimension.
update_from_issue_key	String, a reference to the field with issue key value		Specify what field (default fields, link custom field, etc) containing a single issue key should be used to pass down the custom field value to other issues. Works for single value custom fields only. The reference custom field should also contain only one single issue key for any issue.

Advanced settings for custom fields eazyBI for Jira