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Jan Kettenis

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Jan Kettenishttp://www.blogger.com/profile/14146264706360751350noreply@blogger.comBlogger103125
Updated: 3 hours 42 min ago

Oracle BPM 12c: Browsing the SOAINFRA

Thu, 2016-05-12 11:17
In this article I discuss some tables from the SOAINFRA schema that might be most interesting to use when trying to find out why you don't see in Enterprise Manager what you expect.

Going from 11g to 12c, some things have significantly changed in the SOAINFRA schema. For example, your normal partners in helping with "what happened with my process?" type of queries, like the component_instance, and bpm_process tables, have become obsolete. On the other hand you have new friends with tables like sca_flow_instance, and sca_entity.

The following discusses some tables that you might want to look into when digging in the dirt of the SOA/BPM engine's intestines.

The tables I would like to discuss in more detail are:
- sca_flow_instance
- cube_instance
- wftask
- sca_entity
- bpm_cube_process
- bpm_cube_activity

Given that there is no official documentation on these tables, this is based on my observations an interpretations. No guarantee that these are flawless, so if you have anything to improve or add, let me know!

To better understand the data in the SOAINFRA in relation to an actual process, I used 1 composite with the following processes, that has two subprocesses (another BPM process and a BPEL process). The BPM subprocess has not been implemented as a reusable process (with a Call activity) but instead as a process-as-a-service.






As a side note: originally I created this process to be able to verify how the different states a process and its children can have, are represented in Enterprise Manager. The reason being that on one of my projects there were some doubts if this is always correct, given some issues in the past with 11g. With 12c I could find none. However, as the test case does not concern inter-composite interaction, nor does it include all types of technologies, you could argue that the test case is too limited to conclude anything from it. Also worth to mention is that the instances are ran on a server in development mode, and without in-memory optimization. I have heard rumors that you will observer different behavior when you disabled auditing completely. In some next posting I hope to discuss that as well.

I initiated several instances, for each possible state one:


sca_flow_instanceAs the name already suggests, this table contains 1 entry for each flow instance. You might be interested in the following columns:
  •   flow_id
  •   title
  •   active_component_instances
  •   recoverable_faults
  •   created_time
  •   updated_time

When queried this looks similar to this:

    The query used is like this:
    select sfi.flow_id
    ,      sfi.title
    ,      sfi.active_component_instances
    ,      sfi.recoverable_faults
    ,      sfi.created_time
    ,      sfi.updated_time
    from  sca_flow_instance sfi
    order by sfi.created_time

    cube_instanceThis table contains 1 entry for each component instance in the flow (e.g. bpmn, bpel). You might be interested in the following columns:
    • flow_id
    • composite_label (*)
    • cpst_inst_created_time (**)
    • composite_name
    • composite_revision
    • component_name
    • componenttype
    • state (of the component <== mention)
    • creation_date (incl time)
    • modify_date (incl time)
    • conversation_id

    (*) corresponds with the bpm_cube_process.scalabel
    (**) equals sca_flow_instance.created_time
    When queried this looks similar to this:
    The query used is like this:

    select cis.flow_id,      cis.componenttype,      cis.component_name,      cis.statefrom   cube_instance cisorder by cis.flow_id

    wftask
    This table contains an entry for each open process activity and open or closed human activity. You might be interested in the following columns:
    • flow_id
    • instanceid
    • processname
    • accesskey (not for human tasks) (*)
    • createddate
    • updateddate
    • (only in case of human tasks, the flex fields)
    • componentname
    • compositename (not for human tasks)
    • conversationid
    • componenttype (***)
    • activityname
    • activityid (****)
    • component_instance_id (only for human tasks)
    • state (*****)

    (*) : the type of activity, e.g. USER_TASK, INCLUSIVE_GATEWAY, END_EVENT
    (**) not for human tasks
    (***) e.g. Workflow, BPMN
    (****) Corresponds with the activityid of bpm_cube_activity. The user activity and its corresponding human task appear to have the same activityid. After the human task is completed, the user activity disappears but the human task is kept with an null state.
    (*****) e.g. OPEN for running activities, ASSIGNED for running human tasks. Other states are ABORTED, PENDING_MIGRATION_SUSPENDED, ERRORED, etc.

    When queried this looks similar to this:


    The query used is like this:

    select wft.instanceid,      wft.processname,      wft.accesskey,      wft.createddate,      wft.updateddate,      wft.componentname,      wft.compositename,      wft.conversationid,      wft.componenttype,      wft.activityname,      wft.activityid,      wft.component_instance_id,      wft.statefrom   wftask wftwhere  wft.flow_id = 130001order by wft.updateddate
    sca_entity This table contains an entry for each SCA entity (e.g. service, wire). The following column might be of use:
    •  id
    •  composite (name)
    •  label (corresponds with the scalabel of bpm_cube_process)

    When queried this looks similar to this:


    The query used is like this:

    select sen.composite
    ,      sen.id
    ,      sen.label
    from   sca_entity sen
    where  sen.composite = 'FlowState'
    order by sen.composite

    bpm_cube_processThis table contains metadata. For each deployed composite it contains an entry for each BPM process. If 2 BPM processes in once composite: 2 entries. The following columns might be of use:
    • domainname
    • compositename
    • revision
    • processid
    • processname
    • scalabel
    • compositedn
    • creationdate  (incl time)
    • undeploydate
    • migrationstatus (*)
    (*) Values are LATEST, MIGRATED.

    When queried this looks similar to this:
     

    The query used is like this:


    select bcp.domainname,      bcp.compositename,      bcp.revision,      bcp.processname,      bcp.processid,      bcp.scalabel,      bcp.compositedn,      bcp.creationdate,      bcp.undeploydate,      bcp.migrationstatusfrom   bpm_cube_process bcpwhere  bcp.compositename = 'FlowState'order by bcp.processname,        bcp.creationdate

    bpm_cube_activityThis table contains metadata, There is an entry for each individual activity, event, and gateway of a bpmn process. The following column might be of use:
    • processid (corresponds with the bpm_cube_process.processid)
    • activityid
    • activityname (technical, internal name can be found in the .bpmn source)
    • activitytype (e.g. START_EVENT, SCRIPT_TASK, CALL_ACTIVITY, etc.)
    • label (name as in the BPMN diagram)
    The rows in the example below have been queried by a join with the bpm_cube_process table on processid, where undeploydate is not null and migrationstatus is 'LATEST' to get only the activities of the last revision of one particular process:


    The query used is like this:

    select cbi.flow_id,      cbi.composite_label,      cbi.cpst_inst_created_time,      cbi.composite_name,      cbi.composite_revision,      cbi.component_name,      cbi.componenttype,      cbi.state,      cbi.creation_date,      cbi.modify_date,      cbi.conversation_idfrom   cube_instance cbiorder by cbi.creation_date
    Obsolete TablesThe following table have become obsolete:
    • bpm_activity
    • bpm_activity_instance
    • bpm_cube_activity_instance
    • bpm_process
    • component_instance
    The composite_instance is still used, but more or less superseded by the sca_flow_instance (although the number of instances are not the same). I do not longer find it useful to query.

    Oracle BPM 11g: Mapping Empty Elements

    Mon, 2016-03-21 12:39
    In this blog article I explain what happens with mappings for which the source is empty, and you map it to an optional or mandatory element. The scenarios described in this article are based on SOA / BPEL 11g. In some next article I will describe what happens when you do the same in SOA 12c (which is not the same).

    Let's assume we have a data structure like this:


    And let's assume we have a BPEL that takes a message of the above type as input, and - using a couple of different scenarios - maps it to another element of the same type as output.

    The table below shows what happens when you map empty data to a mandatory or optional element (i.e. minOccurs="0"), taking payload validation into consideration, as well as making use of the "ignoreMissingFromData" and "insertMissingToData" features of XPath mappings (only available in BPEL and not in BPM). In the below "null" means that the element is not there at all, "empty" means that the element is there but has no value. As you can see from the XSD an emtpy value is nowhere allowed (otherwise it should have an attribute xsi:nill with value "true").



    As you can see, disabling payload validation will lead to corrupt data. But even with payload validation on you may get a result that might not be valid in the context of usage, like an empty mandatory or optional element. Unless empty is a valid value, you should make sure that optional elements are not there when they have no value.

    To set "ignoreMissingFrom" and "insertMissingToData", right-mouse click the mapping and toggle the values:


    When using the "ignoreMissingFromData" feature with a null optional element mapped to itself, the result is as on the left below. When also the "insertMissingToData" feature is used, the result is as on the right:


    Mind that the "insertMissingToData" feature also leads to namespace prefixes for each element.