---
sourceDocument: Australia ServiceNow AI Platform Capabilities
sourceDocumentLink: https://www.servicenow.com/docs/r/servicenow-platform

 Release :

    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia ServiceNow AI Platform Capabilities

ft:clusterId :

    - platcap

bundleId :

    - platcap

workflow :

    - Platform


---

# Create an ETL transform map

# Create an ETL transform map {#ariaid-title1}

* Release version: Australia
* 
* Updated March 12, 2026
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 38 minutes to read

IntegrationHub ETL provides a guided setup which walks you through the completion of all
necessary tasks for creating an ETL transform map for a specific integration.

## Guided setup {#create-etl-transform-map__section_hnx_z3j_lkb}

Guided setup organizes all the tasks in the correct order, tracks the completion of tasks, and
enforces any task dependencies. Tasks that depend on the completion of other tasks, are enabled
or disabled as you step through the tool and complete tasks.

Use guided setup on the ETL Transform Map Assistant page to complete the following tasks.

## Import source data and specify basic details {#ariaid-title2}

Provide basic details for the integration, such as the source of the data that you
want to integrate into CMDB, and import the source data.

### Before you begin

The data source that you plan to select for the ETL Transform Map must exist in the
same application scope as the one being used in the current session.

When you open an ETL transform map, by default the map is
not validated. You can enable this validation step by [adding the system
property](https://www.servicenow.com/docs/access?context=t_AddAPropertyUsingSysPropsList&version=australia&pubname=australia-platform-administration&ft:locale=en-US)
sn_int_studio.validation.enabled to the System Properties
\[sys_properties\] table and then setting it to true. After
validation is complete, you choose how to handle validation errors.

Role required: cmdb_inst_admin

### Procedure

1. Navigate to AllConfigurationIntegrationHub ETL.  
   The landing page of the IntegrationHub ETL lists all integrations that exist in the system, including integrations that were downloaded from the ServiceNow Store. Starting with IntegrationHub ETL v3.2, integrations are grouped by the CMDB Application value, in which case expand the respective group to locate an integration.
2. Click the Name of an integration to view or modify, or click Create new.  
   If the system property sn_int_studio.validation.enabled is set to true, then IntegrationHub ETL validates the ETL transform map that you are loading. If there are any validation errors, the Invalid Mapping Data Detected dialog box appears, listing all the specific errors that were detected. You can choose to delete the invalid mappings and continue with only the valid mappings, or you can choose to keep the invalid mappings. However, notifications about invalid mappings will continue to appear as you continue to work with the integration.  
   The system detects errors such as:
   * Missing source or target fields in corresponding Robust Transform Engine (RTE) field mappings records
   * Missing table columns in an import set  
     Note:  
     In this situation, any corresponding metadata records in RTE are no longer valid and are automatically deleted. Records such as field mappings and transform operations that are associated with the missing table columns in the import set, are deleted.
   * Missing an Identification and Reconciliation Engine (IRE) lookup rule for a lookup class
   {#etl-specify-basic-details__ul_u34_dj3_wpb}
3. On the ETL Transform Map Assistant page, in the Specify Basic Details section of the guided setup, select the Import Source Data and Provide Basic Details task.
4. Fill out the form.  
   {#etl-specify-basic-details__table_u5c_mqc_ckb__entry__2}

   | Field | Description |
   |-|-|
   | CMDB Application | The CMDB application associated with the ETL transform map. You can select Add new, which adds the CMDB Application and the Discovery Source fields for the new CMDB application. |
   | Name | Name of the ETL transform map. |
   | Description | Description of the integration. |
   | Data Source | List of all data sources in the system. Note: Be cautious in subsequently modifying the data source as it can result in substantial changes to the data integration. Aligning to the import set table of the new data source might require the removal of columns and associated transforms, or the addition of new columns. IntegrationHub ETL validation processes will detect any required updates and let you agree or reject these updates. |
   | Sample Import Set | An Import Set that is associated with the specified Data Source. A subset of that Import Set data is used to preview source data. Select the Auto-pull a new import set option to pull a new Import Set of the associated data source. Starting with IntegrationHub ETL v3.2, if no Import Set is specified, then the map is loaded and is automatically set to be in read-only mode. You can review configurations in the map but can't edit mappings or transforms. |
   | Preview Size Override | Number of data records that are loaded and used as sample for the preview for this transform map. If set, this custom setting overrides the value of the sn_int_studio.preview.size system property, and applies only to the current transform map. If Load Complete Schema is disabled, then the nested data structure for the map is generated based only on the specified number of records that are loaded. Field available starting with IntegrationHub ETL v3.2. |
   | Load Complete Schema | Enable or disable loading the entire data schema for generating the data structure for the map. When disabled, the nested data structure for the map is generated based only on the number or records loaded as sample records for preview. The number of records loaded is determined by either the Preview Size Override setting, or by the global system property sn_int_studio.preview.size. Field available starting with IntegrationHub ETL v3.2. |
   | CMDB Application | Name of a new CMDB Application. Appears if you set CMDB Application to Add new. |
   | Discovery Source | Discovery source associated with a new CMDB Application. Appears if you set CMDB Application to Add new. |
   [ ]

   {#etl-specify-basic-details__table_u5c_mqc_ckb}
5. Click Save to save the current changes or Mark as Complete.  
   A time stamp appears in the header when you click
   Save, which remains for the duration of the
   IntegrationHub ETL session for the ETL transform map. When you re-enter the
   session or switch between ETL maps, the time stamp disappears.
**Related topics**   

* [Create an Import Set data source](https://www.servicenow.com/docs/access?context=c_CreateNewDataSource&version=australia&pubname=australia-integrate-applications&ft:locale=en-US)

## Preview and prepare data {#ariaid-title3}

Review sample records of raw source data, which will be integrated into the CMDB.
Transform and prepare data to align with the target classes and attributes, if
needed.

### Before you begin

The number of records in the sample data is globally determined by the system property sn_int_studio.preview.size, which is set to 100 by default. The maximum number of records in
the sample data that IntegrationHub ETL can process is 10,000. If you set that property above the 10,000 limit, then IntegrationHub ETL will only process up to 10,000 records and a message will appear to that effect.

Starting with IntegrationHub ETL v3.2, you can override the value of the sn_int_studio.preview.size property by setting the Preview Size Override field on
the Import Source Data and Provide Basic Details form, per map.

To process nested data from a nested payload, the
respective data source must be set with the Data in single column option.

Role required: cmdb_inst_admin

### About this task

Review the values in the data columns of the sample data and identify columns that do not align with the requirements of the intended target classes and attributes. You can transform data, for example, by converting the data format, replacing values, and concatenating data columns. You can apply transformations one on top of another, creating a chain of data transformations. You can also set a data column to be ignored in the mapping and integration process.  
Note:  
To set a CMDB attribute to be empty, use the string '\<EMPTYֹ_STRING\>'.

Columns for nested data appear alongside the rest of the
data, with a Nested Objects notation in the data column
header. The count of nested data items per object appear with a link which lets you
drill to deeper levels of the nested data. To show the data structure of nested data
in a separate panel, enable the Show data structure
option.

The Data Structure panel has two options for displaying
nested data:  
* Tree: Nested data grouped by objects, where each object node corresponds to a record entry in the source data. Expand object nodes to show all nested data for the record.
* Collection: Nested data grouped by the top-level object (by default) and then by nested data items such as software. Expand a node such as software, to show which software is installed on each computer.
{#etl-prepare-data__ul_p3w_d33_34b}You can navigate through the levels of nested data in the Data Structure panel, the breadcrumbs path, or through number links that appear in the source data itself. Your selections and the data that appears are kept synchronized between all views of the nested data, regardless of navigation.

For a demo about working with nested payload data, watch the [Integration Hub - ETL nested payload feature demo](https://youtu.be/jonkMkFiNaQ) video on
the ServiceNow YouTube channel.

### Procedure

1. Navigate to AllConfigurationIntegrationHub ETL, and click the Name of an integration.  
   The landing page of the IntegrationHub ETL lists all integrations that exist in the system, including integrations that were downloaded from the ServiceNow Store.
2. In the ETL Transform Map Assistant page, in the Prepare Source Data for Mapping section of the guided setup, select Preview and Prepare Data.
3. **Optional:** Select Show data structure to open the Data Structure panel which shows the structure of nested data. In the Data Structure panel, you can drill down through the levels of nested data.
4. **Optional:** Select the action menu for a column and then select a Sort operation.
5. Select the action menu for a column and then select Group by to group the data by the respective column. Select Ungroup to undo the grouping operation.
6. **Optional:** Click New Transform and then select Use Source Column . Or, select the action menu for a column, and then select New Transform to transform the selected column.  
   You can't create new transforms for nested objects at this top-level view of
   the data. A nested object column contains number links which indicate the
   number of nested items for the record. To create a new transform for nested
   objects, click that number link to drill down to the actual nested data.
   Alternatively, navigate in the Data Structure panel to the nested object for
   which you want to create a transform.

   A transform of nested data can reference parent objects of the nested data
   being transformed. Using the [sample payload for nested data](https://www.servicenow.com/docs/_zqPaqbG5vaxHRfrZ6bq7Q "Use the IntegrationHub ETL store app to create and manage ETL transform maps, which integrate third-party data into the CMDB or into non-CMDB tables without compromising the integrity of data. IntegrationHub ETL provides a simplified user interface that guides you through the integration process end-to-end, including a test integration run of sample data.") as an example, a transform for an
   interface object can reference the parent computer object but can't
   reference a software object.
   1. In the New Transform sidebar on the right, select a Transform Type and modify the Transform Description if appropriate.  
      For more details about transform types, see [Transform types in IntegrationHub ETL](https://www.servicenow.com/docs/8lH1LlzsD_kJHWwvWWziFw#integrationhub-etl-transforms "Use various transforms in IntegrationHub ETL to convert and prepare source data for mapping to the CMDB.").
   2. **Optional:** Select Hide initial column used for this transform to hide from the current view all the columns that were used for this transform.  
      This setting is temporary for the current session, and if you refresh the page, the hidden column reappears. To show a hidden column, you can also click the gear icon on the banner frame. Then, move the hidden column from the Available to the Selected list and click OK.
   3. Select or verify the Input Column whose values are being transformed.
   4. **Optional:** Modify the Output Column Name for any of the columns that will be added with the transformed values.
   5. Click Apply.  
      A new column with the transformed values appears, placed in alphabetical order based on the output column name. If you used the suggested output column name, then the new column appears to the right of the input column.
   6. Review the transformed data and adjust any transforms, if needed.
   {#etl-prepare-data__substeps_ddw_1nb_wkb}
7. **Optional:** To apply the 'Set Fixed Value Column' transform:
   1. Click New Transform and then select Set Fixed Value Column.
   2. In the Set Fixed Value Column sidebar, enter a Column Name and a Column Description for the new column. Then, set Assign Column Value to the value that is fixed for the new column.
   3. Click Apply.
   {#etl-prepare-data__substeps_lkr_xlc_blb}
8. **Optional:** Select the action menu for a column, and then select Ignore in Mapping to exclude the column from mapping and integration in the current session.  
   In a subsequent session, the Ignore in Mapping setting
   does not apply, and the column will be included in mapping.

   You can click Include in Mapping to undo the
   Ignore in Mapping setting for the column.
9. **Optional:** Select the action menu for a column, and then select Delete This and Downstream Columns. This delete action deletes the column along with any columns that were added using this column as an input column.
10. **Optional:** Click New Transform and then select Table Lookup which lets you specify a table to look up and extract additional values from. Fill out the fields in the Table Lookup sidebar on the right.  
    Values from the specified lookup table are matched with the mapped data. For the records that match, the specified values from the lookup table, are added as a column, to the data that is being prepared for mapping. {#etl-prepare-data__table_xmg_xt4_rkb__entry__2}

    | Field | Description |
    |-|-|
    | Lookup Table | Table to use for matching with the data that is being mapped. When records from the lookup table and the mapped data satisfy the Look Up Condition, then specified values from the Lookup Table are extracted from the respective record and added to the mapped data. |
    | Lookup Condition | A set of pairs of column conditions. Each pair specifies a column in the lookup table and a column in the mapped data, which are attempted to be matched. * If values of target table column: The column in the target table to match to a column in the mapped data. * Match values of source data table: The column in the mapped data to match to a column in the lookup table. {#etl-prepare-data__ul_pqk_h54_rkb} You can add multiple pairs of columns to match on. |
    | Lookup Condition | Values to extract from the Lookup Table when there is a match with the mapped data. Then output values from the following columns: The lookup table columns to extract values from, when values from the lookup table and the mapped data, satisfy the Lookup Condition. You can specify multiple lookup table columns to extract values from. For every column that you specify, a corresponding Output Column Name field automatically appears. Specify a label for the column that will be added with the extracted values. |
    | Output Column Name | A label for the column that will be added to the mapped data, with the values extracted from the lookup table. An Output Column Name field is automatically added for every column that you specify in Then output values from the following columns. |
    [Table 1. Table Lookup]

    {#etl-prepare-data__table_xmg_xt4_rkb}
11. Review the data and ensure that the intended set of data to be integrated is transformed, correctly formatted and prepared for import.
12. Click Mark as Complete.

### Result

Data is prepared when the set of source data columns and transformed columns that you want to integrate, meet any formatting and other value requirements of the target CMDB classes and attributes. These columns are then ready to be mapped and integrated to CMDB classes and attributes.

## About mapping data columns to CMDB classes and attributes {#ariaid-title4}

There are several requirements and guidelines for mapping source data to target CMDB
classes and attributes. Also, there is an option of deactivating class mappings while preserving
the settings for an easy reactivation. Review these concepts to ensure proper processing by the
Identification and Reconciliation Engine (IRE).

### Required mappings {#etl-about-mapping-to-cmdb-classes__section_kvn_lk1_4pb}

You must map data to all required attributes of the target class in addition to mapping to attributes that are not configured as required. Also, the following two fields appear by default and you cannot delete them:

Source Native Key
:   IRE uses to uniquely identify a record and for building relationships and
    references. Also, improves performance of insert and update operations. When
    processing a payload, IRE generates an error if this field is empty.

Source Recency Timestamp

:   IRE uses to identify records that are older than the current record and therefore
    can be ignored, to help resolve conflicting attribute values. If a value is
    provided, it is used only if it is later than the value that is currently stored in
    the CMDB. If a value is not provided, IRE updates the attribute with the current
    timestamp.

    The following system properties let you modify how IRE uses the source_recency_timestamp value in a payload to update the last_scan attribute in the Source \[sys_object_source\] table:

    * [glide.identification_engine.skip_updating_last_scan_if_older](https://www.servicenow.com/docs/HEqbR2g66O8HVoWp93RQrQ "Use the Identification and Reconciliation properties to configure the identification and reconciliation engine (IRE).")
    * [glide.identification_engine.ire_message_listener_skip_updating_last_scan_to_now](https://www.servicenow.com/docs/HEqbR2g66O8HVoWp93RQrQ "Use the Identification and Reconciliation properties to configure the identification and reconciliation engine (IRE).")
    {#etl-about-mapping-to-cmdb-classes__ul_hl5_ffw_yqb}
For more information about how IRE uses source_native_key and source_recency_timestamp for CI identification, see [Identification and Reconciliation
engine (IRE)](https://www.servicenow.com/docs/7cYVySk8Za0O29HjENzRlw "IRE is an underlying key component in Identification and Reconciliation, providing a centralized framework to perform identification and reconciliation processes across different data sources. IRE uses identification rules, reconciliation rules, and IRE data source rules when processing incoming data before inserting that data to the CMDB.").

### Conditional class {#etl-about-mapping-to-cmdb-classes__section_pvx_p3p_ppb}

A conditional class lets you map different sets of data records to different target classes
according to specific column values, or the status of a specific plugin.

For example, if a display name contains 'Windows', then 'Windows Server' is selected as the
target class. But if the display name contains 'Linux', then 'Linux Server' is selected as
the target class. For records that do not meet any of these conditions (display name does
not contain 'Windows' nor 'Linux'), 'Server' is selected as the target class.

### Associated class {#etl-about-mapping-to-cmdb-classes__section_sqk_r3p_ppb}

An associated class lets you select the CMDB class to be associated with a target non-CMDB
table. Setting an associated class is required for IRE processing if the non-CMDB table is not configured for IRE processing. For a non-CMDB table that is supported and configured for IRE processing, setting an associated class is optional. See [IRE support for non-CMDB tables](https://www.servicenow.com/docs/jwn15Bjb2OWb0~6MUKfDkQ "Apply Identification and Reconciliation Engine (IRE) processes to supported non-CMDB tables to ensure data integrity and health of those tables.") for more information.

The software Instance is a non-CMDB class but it does not have IRE rules associated with
it. So, things we said about it here pre-Utah are still valid. But for non-CMDB classes
with IRE rules it's not mandatory to have an association. For example "If the target
class for mapping is a non-CMDB class with a reference to a CMDB class, you must select the
CMDB class to associate the non-CMDB target class with" non-CMDB class with IRE rules
Instead of "you must" it should be. "You can". Same with the Example it's not valid for
non-CMDB with IRE rules.

If the target class for mapping is a non-CMDB class with a reference to a CMDB class, you
must select the CMDB class to associate the non-CMDB target class with. A non-CMDB class
refers to a class, such Serial Number \[cmdb_serial_number\], that does not extend the
Configuration Item \[cmdb_ci\] class. The Related Entry \[cmdb_related_entry\] class might
contain multiple CMDB class associations for the same non-CMDB class. Therefore, select the
appropriate association to allow IRE processes to update the target non-CMDB class.

For example, the Related Entry \[cmdb_related_entry\] class has a record which associates the
non-CMDB Software Instance \[cmdb_software_instance\] class with the CMDB Software Package
\[cmdb_ci_spkg\] class. If you select Software Instance as a target class, you must associate
the Software Instance class with the Software Package \[cmdb_ci_spkg\] class.

### Deactivating class mappings {#etl-about-mapping-to-cmdb-classes__section_dyl_pl1_4pb}

When you edit an ETL transform map, provided by a Service Graph Connector for example, you can delete a class mapping to prevent the class from being populated when the integration runs. However, if you later decide to populate
that class, you must readd that class and reconfigure all the class mappings. Instead, you can deactivate a class mapping to temporarily ignore the class during the integration run, while preserving all of its mapping
configuration. A class that you choose to deactivate is grayed out in the user interface but you can continue and edit the class mappings. Later, you can reactivate a class mapping to enable populating the class, without needing
to reconfigure the class mappings.  
Some classes that you choose to deactivate, trigger an automatic deactivation of additional classes that you did not directly choose to deactivate. Which classes are automatically deactivated, depends on the class that you chose to deactivate. For example, whether the class has dependent relationships or associated classes. Those automatically deactivated classes:

* Appear in light gray in the user interface and you can't reactivate them.
* Are automatically reactivated when you reactivate:
  * The class that you initially deactivated which triggered the automatic deactivation
  * Any class that the deactivated class depends on
  {#etl-about-mapping-to-cmdb-classes__ul_smt_dv4_rpb}
{#etl-about-mapping-to-cmdb-classes__ul_kxq_1pp_ppb}

All classes that you directly deactivate mappings for and the resulting class mappings that are automatically deactivated, are not populated when the integration runs. Also, any relationships and lookup tables associated with
those classes, are not populated when the integration runs.  
Class mapping and other deactivation scenarios:

* Deactivate a class which no class depends on and which has no associated classes: Triggers an automatic deactivation of any lookup rules and relationships associated
  with the deactivated class.

* Deactivate a lookup rule, such as serial number, within a class mapping: Does not
  trigger any automatic deactivations.

* Deactivate a CMDB class which is associated with a non-CMDB class:
  * Triggers an automatic deactivation of the associated non-CMDB class.
  * Deactivating the non-CMDB class, does not impact the associated CMDB class.
  {#etl-about-mapping-to-cmdb-classes__ul_cjv_nfc_ppb}
* Deactivate a class with dependent relationships (Applies only if the dependent relationship exists in IntegrationHub ETL):
  * Triggers an automatic deactivation of any class that has a single dependent relationship with the deactivated class.
  * If a class has multiple dependent relationships, then it is automatically
    deactivated only when you deactivate all of the dependent on classes.

    For example, a scenario in which the File System class has dependent
    relationships with both, the Computer and a Server class. If you deactivate the
    Computer class, the File System class is not automatically deactivated. Only if
    you also deactivate the Server class, the File System class is automatically
    deactivated.
  {#etl-about-mapping-to-cmdb-classes__ul_qxj_qfc_ppb}
* Deactivate a conditional class or a class mapping within a conditional class:
  * Deactivating or activating a conditional class, triggers an automatic deactivation or activation of all conditional class mappings within the conditional class.
  * Deactivating a class mapping within a conditional class: Prevents the deactivated
    class from getting populated during integration runs. However, the associated
    'If', 'Else if', or 'Else' conditions themselves remain in effect within the
    condition of the conditional class. For example, if you deactivate the following
    class mapping:

    \[If\] \[operating_system\] \[contains\] \[Linux\] Then \[Class\] \[is\] \[Linux Server\].

    Then, the Linux Server class is not populated, but the \[If\] \[operating_system\] \[contains\] \[Linux\] condition is in effect.
  {#etl-about-mapping-to-cmdb-classes__ul_hql_msp_ppb}
{#etl-about-mapping-to-cmdb-classes__ul_xfc_rjn_4pb}

## Map data columns to CMDB classes and attributes {#ariaid-title5}

Choose target classes and attributes in the CMDB to map source data columns to. You
can map a data column to a specific target class, or add conditions so that the choice of
target class depends on specific data values.

### Before you begin

Role required: cmdb_inst_admin

### About this task

Data columns that you map can be either source data columns which were not
transformed, or transformed data columns. For example, to integrate a data column
into the Computer and Software Package classes, select those classes as target
classes and then map data columns into specific attributes in those classes.

When you configure mapping for a class, relationship, or a
lookup rule, those items are always initially set as activated. For details about
the results of deactivating mappings, see [Deactivating class
mappings](https://www.servicenow.com/docs/8lH1LlzsD_kJHWwvWWziFw#etl-about-mapping-to-cmdb-classes "There are several requirements and guidelines for mapping source data to target CMDB classes and attributes. Also, there is an option of deactivating class mappings while preserving the settings for an easy reactivation. Review these concepts to ensure proper processing by the Identification and Reconciliation Engine (IRE).").  
Note:  
Changing a class impacts any mappings that were already configured for the class, sometimes deleting those mappings. Details about the affected mappings and the impact, appear in the Affected mappings dialog box before you proceed with the class change. However, these details appear only when the change is from a CMDB class to another CMDB class or from a non-CMDB class to another non-CMDB class.

### Procedure

1. Navigate to AllConfigurationIntegrationHub ETL, and click the Name of an integration.  
   The landing page of the IntegrationHub ETL lists all integrations that exist in the system, including integrations that were downloaded from the ServiceNow Store.
2. In the ETL Transform Map Assistant page, in the Map Data to CMDB and Add Relationships section of the guided setup, select Select CMDB Classes to Map Source Data.  
   Attributes that are configured as required in the platform, are noted, and you must map a data column to each of those attributes.
3. Click Add Class to add a target class to map to, or click Edit Class to edit a class.
   1. In the Add Class dialog box, select a CMDB Class.
   2. Click Save.
   3. **Optional:** Set the Activate/Deactivate Mapping toggle switch for a class, to on or off. If the Affected class mappings dialog box appears, review the list of affected classes, and then click Proceed.  
      When you add a non-CMDB class, it is initially deactivated and the Activate/Deactivate Mapping toggle switch is disabled, until you add an associated class that is active.
   {#etl-map-to-cmdb__substeps_pny_qct_tlb}
4. Click Add Conditional Class and then in the Add Conditional Class dialog box, specify the conditions that must be met for data to be mapped to different target classes.
   1. Collection is automatically set to the data branch in the hierarchy which is associated with the lowest-level attribute. You can modify the value to the data branch from which you want to map data from, which must be at a higher level in the same data branch of the hierarchy.
   2. In the If drop-down list, select attribute conditions that data values must meet, or enter <kbd class="ph userinput">plugins</kbd> in the search box and specify a plugin condition. You can then specify that the rest of the records, which did not match any conditions, are mapped to yet a different target class. Data records will be mapped to different target classes according to the conditions met.  
      When processing nested data, a prefix
      denotes the first level in the nested hierarchy for attribute
      items.  
      Note:  
      When you select a non-CMDB class, it is initially deactivated and the Activate/Deactivate Mapping toggle switch is disabled, until you add an associated class that is active.
   3. Click Save.
   4. **Optional:** Set the Activate/Deactivate Mapping toggle switch for a conditional class, to on or off. If the Affected class mappings dialog box appears, review the list of affected classes, and then click Proceed.
   5. **Optional:** Click Edit Class to edit the settings of a conditional class. In the Edit Conditional Class dialog box, set the Activate/Deactivate Mapping toggle switch for a class mapping, to on or off. Click Save, and if the Affected class mappings dialog box appears, review the list of affected classes and then click Proceed.  
      * A deactivated class is not populated during integration runs, however, this doesn't affect the associated condition. The 'If', 'Else if', and 'Else' conditions themselves remain in effect within the condition of the conditional class and matching CIs are filtered accordingly.
      * The toggle switch of the conditional class reflects the summary of the states of all the conditional class mappings within the conditional class. If at least one of the conditional class mappings is activated, then the toggle switch of the conditional class appears as activated. Otherwise, the toggle switch of the conditional class appears as deactivated.
      {#etl-map-to-cmdb__ul_tyz_kfg_vpb}
   {#etl-map-to-cmdb__substeps_pmj_hdp_3kb}
5. For a non-CMDB class, click Add Associated Class to associate the non-CMDB class with a CMDB class and to enable the Activate/Deactivate Mapping toggle switch.. Or, click Edit Associated Class to edit an already associated class.
   1. In the Add Associated Class dialog box, select a CMDB class. The list includes all entries in the Related Entry \[cmdb_related_entry\] class for the specified non-CMDB table (deactivated classes are not included).
   2. Click Add.
   3. **Optional:** Set the Activate/Deactivate Mapping toggle switch for an associated class, to on or off.  
      Note:  
      If an associated class was not added or is deactivated, then the Activate/Deactivate Mapping toggle switch is disabled.
   {#etl-map-to-cmdb__substeps_ajr_3ft_tlb}
6. Click Set Up Mapping to configure mapping for a newly added class, or click Edit Mapping to edit a mapping.
   1. To map, drag data columns from the Data sidebar on the right, to CMDB target attribute on the left side of the mapping page. Or, click the ![Select a column in IntegrationHub ETL.]() icon to search and select data columns for the mapping.  
      When mapping nested data:  
      * Data columns in the Data sidebar appear in a tree format that represents the structure of the nested data. Each attribute is associated with sample data for the attribute.
      * Transformed columns are noted by a cyan-shaded dot.
      * All mappings to a specific CMDB class must be from the
        same source branch in the nested data. Only the branch
        from which you selected the first column to map, is
        valid for selecting columns in subsequent mappings.

        This restriction applies differently when mapping to
        attributes in lookup tables. All mappings to attributes
        in a lookup table also must be from the same source
        branch. However, that source branch can be different
        than the source branch you used with non-lookup
        tables.  
        Note:  
        You can work around this restriction by using the [Copy](https://www.servicenow.com/docs/8lH1LlzsD_kJHWwvWWziFw#integrationhub-etl-transforms "Use various transforms in IntegrationHub ETL to convert and prepare source data for mapping to the CMDB.") transform in the data preparation step, to copy attributes from a parent level to a child level. Prepare the data so that all the attributes that you want to map, are at the same level.
      * When you drag a column to map from the Data sidebar, the fields of CMDB target attributes that are valid for the mapping, are highlighted by a green frame. If you attempt to drop a column in an invalid target attribute, the respective field is highlighted by a red frame and an error appears.
      {#etl-map-to-cmdb__ul_sy1_hn5_j4b}
   2. Click Add Attribute. Then, in the Add Attribute dialog box, from the Attribute list, select one or more items as target attributes to map data to. You can also scroll down to the IRE Settings section of the list and select one of the [robust
      import set transformer properties](https://www.servicenow.com/docs/access?context=robust-import-set-xform-props&version=australia&pubname=australia-integrate-applications&ft:locale=en-US) . Click Save.  
      For information about precedence order between robust import set transformer properties defined at the individual item level and at the IRE payload level, see [robust import
      set transformer properties](https://www.servicenow.com/docs/access?context=robust-import-set-xform-props&version=australia&pubname=australia-integrate-applications&ft:locale=en-US) .
   3. Map any lookup rules such as the 'Serial Number Lookup 1' rule.  
      Lookup rules are in a deactivated state until you map them. Click the filter icon for the lookup rule to edit or add any lookup filters. In the lookup filter dialog box, specify attribute or plugin conditions that must be met for data to be mapped to various target classes. Then click Save.

      After mapping a field of a lookup rule, you can set the
      Activate/Deactivate Lookup rule toggle switch for a rule, to on or
      off.
   4. **Optional:** Click View Class Details to view the current class in [CI Class Manager](https://www.servicenow.com/docs/whL8noao8OY8GOqTGBIZdA "Use the CI Class Manager to centrally view, create, or edit basic class definitions, class settings for Identification and Reconciliation Engine (IRE), CMDB Health, and manage some Service Mapping definitions.").
   5. **Optional:** Click the Transform Data tab to navigate to the data preparation page where you can review and further transform data that you want to map.
   6. Return to the Select CMDB Classes to Map Source Data page.
   {#etl-map-to-cmdb__substeps_svb_1ql_4kb}
7. Click Mark as Complete.

## Add Relationships {#ariaid-title6}

Add relationships that exist among the target CMDB classes, for an
integration.

### Before you begin

* A class that you want to add in the relationship, must be in an activated state.
* A base relationship or a relationship within a conditional relationship, that you want to edit, must be in an activated state.
* In a conditional relationship that you want to edit, at least one relationship condition must be in an activated state. Otherwise, the Edit Relationship button is grayed out.
{#etl-add-relationships__ul_dpx_5tp_ppb}

Role required: cmdb_inst_admin

### About this task

When creating relationships with nested data, you can't
create a relationship between sibling objects from the nested data. Using the [sample payload for nested data](https://www.servicenow.com/docs/_zqPaqbG5vaxHRfrZ6bq7Q "Use the IntegrationHub ETL store app to create and manage ETL transform maps, which integrate third-party data into the CMDB or into non-CMDB tables without compromising the integrity of data. IntegrationHub ETL provides a simplified user interface that guides you through the integration process end-to-end, including a test integration run of sample data.")
as an example, you can't create a relationship between interfaces and software.

ITOM Visibility, if available, uses enhanced discovery patterns to
identify and add CI relationships to the Suggested Relationships table in the base
system. When applicable, use the Suggested Relationships table to select
relationships that are in compliance with Common Service Data Model (CSDM) standards.

### Procedure

1. Navigate to AllConfigurationIntegrationHub ETL, and click the Name of an integration.  
   The landing page of the IntegrationHub ETL lists all integrations that exist in the system, including integrations that were downloaded from the ServiceNow Store.
2. In the ETL Transform Map Assistant page, in the Map Data to CMDB and Add Relationships section of the guided setup, select Add Relationships.
3. To add relationships, select Add Relationship or Add Conditional Relationship if you want to specify attribute conditions that must be met before adding a relationship. Then, complete the following actions as needed.

   | Option | Description |
   | Add Relationship | 1. Select the Parent, Child, and Relationship Type values. 2. Click Add. {#etl-add-relationships__ol_zrm_x2s_2nb} |
   | Add Conditional Relationship | 1. In the choose field list, select attribute conditions that the data values must meet. 2. Select the Parent, Child, and Relationship Type values. 3. Click Save. {#etl-add-relationships__ol_wb1_4fs_2nb} When processing nested data, a prefix denotes the first level in the nested hierarchy for attribute items. |
   |-|-|

   {#etl-add-relationships__choicetable_rvq_52s_2nb}  
   The Relationship Type list menu changes based on the selected parent and child class:
   * If there is a dependent relationship, the list is disabled and the relationship type is automatically populated.
   * If there is more than one dependent relationship, the list displays both containment and hosting relationship options and the containment relationship type is automatically populated.
   * If there is no dependent relationship, the list displays Suggested relationships with the first suggested relationship automatically selected, followed by the base system relationship types.
   * If there is no suggested relationship, the list displays No suggested relationships followed by the base system relationship types.
   {#etl-add-relationships__choices_ors_cgs_2nb}
4. Click Save to save the current changes or Mark as Complete.  
   A time stamp appears in the header when you click
   Save, which remains for the duration of the
   Integration Hub ETL session for the ETL transform map. When you re-enter the
   session or switch between ETL maps, the time stamp disappears.

## Preview mapping results {#ariaid-title7}

Preview the results of the sample data integration.

### Before you begin

Role required: cmdb_inst_admin

### About this task

Run an integration test and view a summary of the results, for the sample data (by default, up to 100 records). The summary includes total numbers for relationships that were created, mapped classes, partial and incomplete payloads that IRE couldn't process. You can also view detailed messages from Robust Transform Engine (RTE) and from Identification Reconciliation Engine (IRE).  
Note:  
Most IntegrationHub ETL log messages (from RTE and IRE) are informational. However, even if the com.glide.import_set.importlog_level and the glide.importlog.log_to_table system properties are set to not add INFO log messages, IntegrationHub ETL does render INFO log messages. For more details about these properties, see [Import sets properties](https://www.servicenow.com/docs/access?context=r_ImportSetsProperties&version=australia&pubname=australia-integrate-applications&ft:locale=en-US).

After you view the details in the summary page, you can return to any step to make adjustments and then rerun the integration.

### Procedure

1. Navigate to AllConfigurationIntegrationHub ETL, and click the Name of an integration.  
   The landing page of the IntegrationHub ETL lists all integrations that exist in the system, including integrations that were downloaded from the ServiceNow Store.
2. In the ETL Transform Map Assistant page, in the Preview Sample Integration Results and Schedule Import section of the guided setup, select Test and Rollback Integration Results.
3. On the Test and Rollback Integration Results page, click Run Integration.
4. View the summary page and click the various tabs to see the integration run results for the affected CMDB classes. You can select the preview icon to open CI forms and view information.  
   Note:  
   The order of the attribute columns follows the default columns list for the class in the platform. First, the default columns for the class appear from left to right, followed by the rest of the attribute columns organized in alphabetical order. For example, to see the default columns list for the Computers class, navigate to AllConfigurationComputers.
5. **Optional:** Select any class tab and click Edit Mapping to return to the Select CMDB Classes to Map Source Data page where you can review and change mapping settings.  
   Note:  
   Clicking Edit Mapping rolls back all the changes that were made to the CMDB as a result of this integration run.
6. **Optional:** Click the Relationships tab and review any relationships that were created.
7. **Optional:** Click Edit Relationships to return to the Add Relationships page where you can review and change any relationship configurations.  
   Note:  
   Clicking Edit Relationships rolls back all the changes that were made to the CMDB as a result of this integration run.
8. Click the Error Log, Activity Log, or the Warning Log tabs to see the respective details logged by IRE and RTE during the integration.  
   IRE log records are grouped by categories and further organized by the respective class. For IRE log messages, the Message column contains only the messages themselves which were extracted from the raw log message. The Log
   Message column contains the complete log message, which includes class and category in addition to the message itself. RTE logs appear under the Other category.  
   Use the Verbose toggle switch to change the viewing mode for the Message and the Log Message columns:
   * Verbose on: Shows fully expanded text of log messages.
   * Verbose off: Shows a condensed version of the log messages. The fully expanded text of the log messages appears when you point to a message.
   {#etl-preview-mapping-results__ul_yhh_dcr_drb}
9. Click the Incomplete Payloads and Partial Payloads tabs for details about IRE payloads for the integration run.
10. Select Mark as Complete.  
    The Rollback options dialog box appears and you can choose either of the following options.
    * Retain Data: All the changes to the CMDB resulting from this integration, are retained.
    * Perform Rollback: All the changes to the CMDB resulting from this integration, are rolled back and the CMDB is restored to its state before running the integration.
    {#etl-preview-mapping-results__ul_jvq_c3h_rkb}

## Provide integration schedule {#ariaid-title8}

Configure a schedule for importing data to CMDB using this ETL Transform
Map.

### Before you begin

Role required: cmdb_inst_admin

### Procedure

1. Navigate to AllConfigurationIntegrationHub ETL, and click the Name of an integration.  
   The landing page of the IntegrationHub ETL lists all integrations that exist in the system, including integrations that were downloaded from the ServiceNow Store.
2. In the ETL Transform Map Assistant page, in the Preview Sample Integration Results and Schedule Import section of the guided setup, select Set Import Schedule.
3. On the Provide Schedule page, click Set Schedules.
4. In the Scheduled Data Imports list view (which opens in a new tab), click New.
5. Fill out the Scheduled Data Import form and then click Submit.  
   See [Schedule a data
   import](https://www.servicenow.com/docs/access?context=t_ScheduleADataImport&version=australia&pubname=australia-integrate-applications&ft:locale=en-US) for details about the form fields.
6. Click Mark as Complete.

## Transform types in IntegrationHub ETL {#ariaid-title9}

Use various transforms in IntegrationHub ETL to convert and prepare source data for
mapping to the CMDB.
Transforms from the [Integration Commons for CMDB](https://www.servicenow.com/docs/eNRvwxlXe1MvEh~3MtTKAQ "The Integration Commons for CMDB application contains the CMDB Integrations Dashboard and a set of Robust Transform Engine (RTE) transforms and script includes.") store app, are also
available in IntegrationHub ETL.

### Concatenation {#integrationhub-etl-transforms__section_oqf_ntx_glb}

Combines the values from input fields into a single string, joining them on the optional
joining_string field.  
{#integrationhub-etl-transforms__table_pqf_ntx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_concat_operation |
| Input fields | source_sys_rte_eb_fields |
| Output field | target_sys_rte_eb_field |
| Additional Fields | joining_string (optional) |
[ ]

{#integrationhub-etl-transforms__table_pqf_ntx_glb} {#integrationhub-etl-transforms__table_v33_xpk_hlb__entry__2}

| Example |   |
|-|-|
| Input | "input_1", "input_2", "input_3" |
| Additional Fields | joining_string = ", " |
| Result | "input_1, input_2, input_3" |
[ ]

{#integrationhub-etl-transforms__table_v33_xpk_hlb}

### Convert to Boolean {#integrationhub-etl-transforms__section_klv_2rx_glb}

Converts the incoming value to a boolean. '<kbd class="ph userinput">true</kbd>' and
'<kbd class="ph userinput">1</kbd>' values convert to 'true' (case insensitive), and any other values
convert to 'false'.  
{#integrationhub-etl-transforms__table_llv_2rx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_to_boolean_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
[ ]

{#integrationhub-etl-transforms__table_llv_2rx_glb}Examples:

* All of the following inputs return 'true':
  * true
  * 1
  {#integrationhub-etl-transforms__ul_nsl_rfl_hlb}
* All of the following inputs return 'false':
  * "input_1"
  * ""
  * 0
  * 11
  {#integrationhub-etl-transforms__ul_nzw_sfl_hlb}
{#integrationhub-etl-transforms__ul_yjv_4fl_hlb}

### Convert to Date {#integrationhub-etl-transforms__section_cfx_2rx_glb}

Attempts to convert the incoming value to a GlideDateTime value by
applying the date_format to the incoming value. Attempts to directly
convert using GlideDateTime if the date_format is
incorrect.  
{#integrationhub-etl-transforms__table_dfx_2rx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_to_date_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field Returns an empty value if unable to parse at all. |
| Additional Fields | date_format (Java simple date format) |
[ ]

{#integrationhub-etl-transforms__table_dfx_2rx_glb} {#integrationhub-etl-transforms__table_ezd_drf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "2018/09/20 11:21:00 a.m. EST" |
| Additional Fields | date_format = "yyyy/MM/dd hh:mm:ss a z" |
| Result | "2018-09-20 16:21:00" |
[ ]

{#integrationhub-etl-transforms__table_ezd_drf_hlb} {#integrationhub-etl-transforms__table_qsd_grf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "2018/09/20 01:21:00 PM EST" |
| Additional Fields | date_format = "yyyy/MM/dd hh:mm:ss a z" |
| Result | "2018-09-20 18:21:00" |
[ ]

{#integrationhub-etl-transforms__table_qsd_grf_hlb} {#integrationhub-etl-transforms__table_rtj_jrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "09/20/18" |
| Additional Fields | date_format = "yyyy/MM/dd hh:mm:ss a z" |
| Result | "0018-09-20 00:00:00" |
[ ]

{#integrationhub-etl-transforms__table_rtj_jrf_hlb}

### Convert to Numeric {#integrationhub-etl-transforms__section_ghy_2rx_glb}

Converts the incoming value to a number.  
{#integrationhub-etl-transforms__table_hhy_2rx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_to_numeric_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field If the incoming value is non-numeric, then the output is empty. |
[ ]

{#integrationhub-etl-transforms__table_hhy_2rx_glb} {#integrationhub-etl-transforms__table_asd_rrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | 1.23 |
| Result | 1.23 |
[ ]

{#integrationhub-etl-transforms__table_asd_rrf_hlb} {#integrationhub-etl-transforms__table_gkf_rrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | 1.00 |
| Result | 1 |
[ ]

{#integrationhub-etl-transforms__table_gkf_rrf_hlb} {#integrationhub-etl-transforms__table_gnq_5rf_hlb__entry__2}

| Example |   |
|-|-|
| Input | input_1 |
| Result | null |
[ ]

{#integrationhub-etl-transforms__table_gnq_5rf_hlb} {#integrationhub-etl-transforms__table_njl_yxm_hlb__entry__2}

| Example |   |
|-|-|
| Input | two |
| Result | null |
[ ]

{#integrationhub-etl-transforms__table_njl_yxm_hlb}

### Copy {#integrationhub-etl-transforms__section_qdz_2rx_glb}

Copies the source field's value to all of the target fields.  
{#integrationhub-etl-transforms__table_rdz_2rx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_copy_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_fields |
| Additional Fields | overwrite_existing_value (optional, boolean): If true, then the values of target fields are replaced. Otherwise, any non-empty value is not overwritten. |
[ ]

{#integrationhub-etl-transforms__table_rdz_2rx_glb}

### Extract Leading Numeric {#integrationhub-etl-transforms__section_h11_frx_glb}

Sets the target field to be the first numeric value found in the source field.  
{#integrationhub-etl-transforms__table_i11_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_extract_numeric_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
| Additional Fields | * decimal_places (optional, number): Forces the output to have a specified number of decimal places. * remainder_target_field (optional, reference to a field): Set to the trimmed remainder of the source field, after removing the first numeric value. {#integrationhub-etl-transforms__ul_b1h_k3z_glb} |
[ ]

{#integrationhub-etl-transforms__table_i11_frx_glb} {#integrationhub-etl-transforms__table_m5k_yrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "100 mb" |
| Result | "100" |
[ ]

{#integrationhub-etl-transforms__table_m5k_yrf_hlb} {#integrationhub-etl-transforms__table_jzc_zrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "100.123 mb" |
| Result | "100.123" |
[ ]

{#integrationhub-etl-transforms__table_jzc_zrf_hlb} {#integrationhub-etl-transforms__table_pqd_zrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "100.123 mb" |
| Additional Fields | decimal_places = 2 |
| Result | "100.12" |
[ ]

{#integrationhub-etl-transforms__table_pqd_zrf_hlb} {#integrationhub-etl-transforms__table_il2_zrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "100 mb" |
| Additional Fields | decimal_places = 2 |
| Result | "100.00" |
[ ]

{#integrationhub-etl-transforms__table_il2_zrf_hlb} {#integrationhub-etl-transforms__table_pcf_zrf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "100 mb" |
| Additional Fields | remainder_target_field = \<field\> |
| Result | "100" and \<field\> = "mb" |
[ ]

{#integrationhub-etl-transforms__table_pcf_zrf_hlb}

### Glide Lookup {#integrationhub-etl-transforms__section_sw1_frx_glb}

Performs a lookup in the database on the target_table.  
{#integrationhub-etl-transforms__table_tw1_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_glide_lookup_operation |
| Input fields | source_sys_rte_eb_fields |
| Output field | target_sys_rte_eb_fields |
| Additional Fields | * target_table * glide_matching_fields (string): Comma-separated list of column names in the target table. For each input field in source_sys_rte_eb_fields, there must be an equal number of values in glide_matching_fields * glide_target_fields (string): Comma-separated list of column names in the target table. For each target field in target_sys_rte_eb_fields, there must be an equal number of values in glide_target_fields. {#integrationhub-etl-transforms__ul_pjq_fjz_glb} |
[ ]

{#integrationhub-etl-transforms__table_tw1_frx_glb} {#integrationhub-etl-transforms__table_jlm_xw1_bmb__entry__2}

| Example |   |
|-|-|
| Input | * Input Field 1: 100 South Charles Street, Baltimore * Input Field 2: MD {#integrationhub-etl-transforms__ul_zln_fx1_bmb} |
| Additional Fields | * Target Table: Location (cmn_location) * Glide Matching Fields: street,state * Glide Target Fields: sys_id {#integrationhub-etl-transforms__ul_dbm_hx1_bmb} |
| Result | Output Field 1: 25ab9c4d0a0a0bb300f7dabdc0ca7c1c |
[ ]

{#integrationhub-etl-transforms__table_jlm_xw1_bmb}

### Min/Max {#integrationhub-etl-transforms__section_epb_frx_glb}

Sets the target field to either the maximum or minimum of the values from all input
fields.  
{#integrationhub-etl-transforms__table_fpb_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_min_max_operation |
| Input fields | source_sys_rte_eb_fields |
| Output field | target_sys_rte_eb_field |
| Additional Fields | * data_type (choice list \<STRING,NUMERIC,DATE\>) * min_max (choice list \<MIN,MAX\>) {#integrationhub-etl-transforms__ul_vyk_dkz_glb} |
[ ]

{#integrationhub-etl-transforms__table_fpb_frx_glb} {#integrationhub-etl-transforms__table_pm1_jsf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "2", "-1", "0" |
| Additional Fields | * data_type = NUMERIC * min_max = MAX {#integrationhub-etl-transforms__ul_w3q_4jl_hlb} |
| Result | "2" |
[ ]

{#integrationhub-etl-transforms__table_pm1_jsf_hlb} {#integrationhub-etl-transforms__table_knx_jsf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "a", "b" |
| Additional Fields | * data_type = STRING * min_max = MAX {#integrationhub-etl-transforms__ul_s1w_qjl_hlb} |
| Result | "b" |
[ ]

{#integrationhub-etl-transforms__table_knx_jsf_hlb} {#integrationhub-etl-transforms__table_kl4_psf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "2", "-1", "0" |
| Additional Fields | * data_type = NUMERIC * min_max = MIN {#integrationhub-etl-transforms__ul_fdm_xjl_hlb} |
| Result | "-1" |
[ ]

{#integrationhub-etl-transforms__table_kl4_psf_hlb} {#integrationhub-etl-transforms__table_ll4_psf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "a", "b" |
| Additional Fields | * data_type = STRING * min_max = MIN {#integrationhub-etl-transforms__ul_vdc_yjl_hlb} |
| Result | "a" |
[ ]

{#integrationhub-etl-transforms__table_ll4_psf_hlb}

### Multiple Input Script {#integrationhub-etl-transforms__section_rhc_frx_glb}

Runs a script with multiple inputs, setting the target_field == output
for that script.

Each source field is available inside of the 'batch' variable as JavScript fields. The name of
the JavaScript field is the field attribute of the entity field (looking at
sys_rte_eb_field.field, not
sys_rte_eb_field.name).  
{#integrationhub-etl-transforms__table_shc_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_multi_in_script_operation |
| Input fields | source_sys_rte_eb_fields |
| Output field | target_sys_rte_eb_field |
| Additional Fields | * script (script) * use_unique_input_sets (boolean): When true, only unique input values are included in the data batch for IRE processing. Otherwise, all input object's field values are included. {#integrationhub-etl-transforms__ul_ur4_gmz_glb} |
[ ]

{#integrationhub-etl-transforms__table_shc_frx_glb}Example for using use_unique_input_sets, with a script function that takes record_type and operating_system as input and returns record_with_os:  
{#integrationhub-etl-transforms__table_yj5_5dn_hlb__entry__4}

| Record | record_type | operating_system | record_with_os |
|-|-|-|-|
| 1 | computer | Windows XP |   |
| 2 | computer | Linux |   |
| 3 | computer | Windows XP |   |
[Table 2. Input data]

{#integrationhub-etl-transforms__table_yj5_5dn_hlb}If use_unique_inputs_sets is set to true, then the script processes only two values (computer + Windows XP and computer + Linux). If use_unique_inputs_sets is set to false, then each of the three values is individually processed (computer + Windows XP, computer + Linux, and computer + Windows XP).  
Sample script:

                (function(batch, output) { 
                    for (var i = 0; i < batch.length; i++) { 
                            // batch[i] is the unique set of inputs/individual record 
                            // batch[i].<field> gives access to the field value 
                            var in0 = gs.nil(batch[i].record_type) ? '' : batch[i].record_type;
                            var in1 = gs.nil(batch[i].operating_system) ? '' : batch[i].operating_system;
                            // output[i] is the output for the specific combination of inputs/individual record 
                            output[i] = in0 + "_" + in1; 
                        } 
                    } 
                })(batch, output);

Sample script:

                /* Example Script
                 // In this example the script input fields are 'input_field_1', 'input_field_2' - replace these with the fields used as script inputs // There is a static field 'input' that has all the input field values concatenated with a '|' (function(batch, output) {
                     for (var i = 0; i < batch.length; i++) {
               
                         //step1: access the input variables
                         var a = batch[i].input_field_1; //Value of the first source field.
                         var b = batch[i].input_field_2; //Value of the second source field.
                 
                         //step2: Your script/code goes here.
                         var c = a + b;
               
                         //step3: set the output for each elements
                         output[i] = b;
                     }
               
                 })(batch, output);
                */

### Rexeg Replace {#integrationhub-etl-transforms__section_s1d_frx_glb}

Replaces each substring of the incoming string that matches the specified
match_regex, with the specified replacement_regex
string value.  
{#integrationhub-etl-transforms__table_t1d_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_regex_replace_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
| Additional Fields | * match_regex (string, regular expression) * replacement_regex (string) {#integrationhub-etl-transforms__ul_ihd_wmz_glb} |
[ ]

{#integrationhub-etl-transforms__table_t1d_frx_glb} {#integrationhub-etl-transforms__table_qn3_xsf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "String\&With(Special)$Characters" |
| Additional Fields | * match_regex = "\[\^0-9a-zA-Z\]+" * replacement_regex = " " {#integrationhub-etl-transforms__ul_kmc_fkl_hlb} |
| Result | "String With Special Characters" |
[ ]

{#integrationhub-etl-transforms__table_qn3_xsf_hlb}

### Replace {#integrationhub-etl-transforms__section_fsd_frx_glb}

Replaces each substring in the incoming string that matches the specified
match_string, with the replacement_string string
value.  
{#integrationhub-etl-transforms__table_gsd_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_replace_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
| Additional Fields | * match_string (string) * replacement_string (string) {#integrationhub-etl-transforms__ul_bl2_4nz_glb} |
[ ]

{#integrationhub-etl-transforms__table_gsd_frx_glb} {#integrationhub-etl-transforms__table_czw_1tf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "Original String" |
| Additional Fields | * match_string = "Original" * replacement_string = "Replacement" {#integrationhub-etl-transforms__ul_omr_tll_hlb} |
| Result | "Replacement String" |
[ ]

{#integrationhub-etl-transforms__table_czw_1tf_hlb}

### Round Numeric {#integrationhub-etl-transforms__section_jl2_frx_glb}

Rounds the number value to the nearest whole number. Non-numbers are truncated.  
{#integrationhub-etl-transforms__table_kl2_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_round_numeric_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
[ ]

{#integrationhub-etl-transforms__table_kl2_frx_glb} {#integrationhub-etl-transforms__table_skv_2tf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "1.5" |
| Result | "2" |
[ ]

{#integrationhub-etl-transforms__table_skv_2tf_hlb} {#integrationhub-etl-transforms__table_ewt_ftf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "1.4" |
| Result | "1" |
[ ]

{#integrationhub-etl-transforms__table_ewt_ftf_hlb} {#integrationhub-etl-transforms__table_fr5_ftf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "i'm a string" |
| Result | "" |
[ ]

{#integrationhub-etl-transforms__table_fr5_ftf_hlb}

### Script {#integrationhub-etl-transforms__section_t2f_frx_glb}

Runs a script with input, setting the target_field == output for that script.

This transform has been superseded by the Multi Input Script transform and is included for
backwards compatibility with existing configurations.  
{#integrationhub-etl-transforms__table_u2f_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_script_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
| Additional Fields | * script (script) * use_unique_input_sets (boolean): When true, only unique input values are included in the data batch for IRE processing. Otherwise, all input object's field values are included. For an example and for more details, see the Multiple Input Script transform. {#integrationhub-etl-transforms__ul_ym2_ssl_hlb} |
[ ]

{#integrationhub-etl-transforms__table_u2f_frx_glb}  
The source field is included in the 'batch' variable as the JavaScript field 'input'.

              (function(batch, output) { 
                    for (var i = 0; i < batch.length; i++) { 
                            // batch[i] is the unique set of inputs/individual record 
                            // batch[i].input gives access to the field value 
                            var in0 = gs.nil(batch[i].input) ? '' : batch[i].input; 
                            // output[i] is the output for the specific combination of inputs/individual record 
                            output[i] = in0 + " modified by script"; 
                        } 
                    } 
                })(batch, output); 

Example:

    /* Example Script
     (function(batch, output) {
         for (var i = 0; i < batch.length; i++) {
             //step1: access the input variables
             var a = batch[i].input; //Value of the source field.
     
             //step2: Your script/code goes here.
             var b = a + 1;
             //step3: set the output for each elements
             output[i] = b;
         }
     })(batch, output);
    */ 

### Set {#integrationhub-etl-transforms__section_iqg_frx_glb}

Sets the target field's value to the string specified in set_value.  
{#integrationhub-etl-transforms__table_jqg_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_set_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
| Additional Fields | * set_value (string) * overwrite_existing_value (optional, boolean): When true, the current value of the target field is overwritten. Otherwise, a non-empty value isn't replaced. {#integrationhub-etl-transforms__ul_b2j_h4z_glb} |
[ ]

{#integrationhub-etl-transforms__table_jqg_frx_glb}

### Split {#integrationhub-etl-transforms__section_mxf_frx_glb}

Splits the source field's value on the splitting_string and assigns each
resulting item from the split to the target_sys_rte_eb_fields, in
order.  
{#integrationhub-etl-transforms__table_nxf_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_split_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_fields |
| Additional Fields | splitting_string (string) |
[ ]

{#integrationhub-etl-transforms__table_nxf_frx_glb} {#integrationhub-etl-transforms__table_bl3_ntf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "value1\|\|value2\|\|value3", with target_sys_rte_eb_fields {target1,target2,target3} |
| Additional Fields | splitting_string = "\|\|" |
| Result | target1 : value1, target2 : value2, target3 : value3 |
[ ]

{#integrationhub-etl-transforms__table_bl3_ntf_hlb} {#integrationhub-etl-transforms__table_lvn_ntf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "value1\|\|value2\|\|value3", with target_sys_rte_eb_fields {target1} |
| Additional Fields | splitting_string = "\|\|" |
| Result | target1 : value1 |
[ ]

{#integrationhub-etl-transforms__table_lvn_ntf_hlb} {#integrationhub-etl-transforms__table_k44_ntf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "value1", with target_sys_rte_eb_fields {target1,target2,target3} |
| Additional Fields | splitting_string = "\|\|" |
| Result | target1 : value1, target2 : \<null\>, target3 : \<null\> |
[ ]

{#integrationhub-etl-transforms__table_k44_ntf_hlb}

### Trim {#integrationhub-etl-transforms__section_vjh_frx_glb}

Trims leading and trailing whitespace from the source_sys_rte_eb_field
value and assigns the result to the target_sys_rte_eb_field. This transform
is equivalent to a Java String.trim().  
{#integrationhub-etl-transforms__table_wjh_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_trim_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
[ ]

{#integrationhub-etl-transforms__table_wjh_frx_glb} {#integrationhub-etl-transforms__table_okr_5tf_hlb__entry__2}

| Example |   |
|-|-|
| Input | " value 1 " |
| Result | "value 1" |
[ ]

{#integrationhub-etl-transforms__table_okr_5tf_hlb}

### Uppercase {#integrationhub-etl-transforms__section_xd3_frx_glb}

Uppercases the source_sys_rte_eb_field value and assigns the result to
target_sys_rte_eb_field.  
{#integrationhub-etl-transforms__table_yd3_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_upper_case_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
[ ]

{#integrationhub-etl-transforms__table_yd3_frx_glb} {#integrationhub-etl-transforms__table_xfd_ytf_hlb__entry__2}

| Example |   |
|-|-|
| Input | "value1" |
| Result | "VALUE1" |
[ ]

{#integrationhub-etl-transforms__table_xfd_ytf_hlb}

### Uppercase Trim {#integrationhub-etl-transforms__section_ew3_frx_glb}

Combines both the Uppercase and the Trim transforms.  
{#integrationhub-etl-transforms__table_fw3_frx_glb__entry__2}

| Details |   |
|-|:-:|
| Table | sys_rte_eb_upper_case_trim_operation |
| Input fields | source_sys_rte_eb_field |
| Output field | target_sys_rte_eb_field |
[ ]

{#integrationhub-etl-transforms__table_fw3_frx_glb} {#integrationhub-etl-transforms__table_qzd_b5f_hlb__entry__2}

| Example |   |
|-|-|
| Input | " value1 " |
| Result | "VALUE1" |
[ ]

{#integrationhub-etl-transforms__table_qzd_b5f_hlb}

*[\>]: and then