Child Jobs

If new to Generic Extractor, learn about jobs in our tutorial first. Use Parameter Map to help you navigate among various configuration options.

Child jobs allow you to iterate/traverse over sub-resources of an API resource. Because child jobs may contain other child jobs, you may query for sub-sub-resources in a virtually unlimited depth.

For instance, when downloading a list of users, you can download details of each user or a list of orders for each user. See the Generic Extractor tutorial for a basic example of using child jobs.

Apart from two additional fields, placeholders and recursionFilter, configuring a child job is no different than configuring any other job.

Click to see a sample job configuration.

{
    ...,
    "config": {
        "jobs": [
            {
                "endpoint": "users",
                "method": "get",
                "dataField": "items",
                "dataType": "users",
                "params": {
                    "type": "active"
                },
                "responseFilter": "additional.address/details",
                "responseFilterDelimiter": "/",
                "children": [
                    {
                        "endpoint": "users/{user_id}/orders",
                        "dataField": "items",
                        "recursionFilter": "id>20",
                        "placeholders": {
                            "user_id": "id"
                        }
                    }
                ]
            }
        ]
    }
}

Placeholders

In a child job, the endpoint configuration must contain a placeholder enclosed in curly braces {}. For example, the following endpoint defines the placeholder user-id:

{
    ...,
    "endpoint": "user/{user-id}"
}

The placeholder name is rather arbitrary (it should not contain any special characters though). To assign it a value, use the placeholders configuration. It is an object whose properties are placeholder names. The value of each placeholders object property is a property path in the parent job response. The placeholder in the child endpoint will be replaced by the value of that parent property. The property path is configured relative to the extracted object (see an example). The child endpoint is configured relative to the api.baseUrl configuration, not relative to the parent endpoint.

The following configuration:

{
    ...,
    "endpoint": "user/{user-id}",
    "placeholders": {
        "user-id": "userId"
    }
}

means that Generic Extractor sends as many requests to the /user/XXX endpoint as there are result objects in the parent API response. The XXX will be replaced by the userId value of each individual response. Placeholders must be used in child jobs so that each child job sends a different API request.

Note

It is technically possible to define a child job without using placeholders configuration or without having a placeholder in the endpoint. But then all the child requests would be the same and that is usually not what you intend to do.

Placeholder Level

Optionally, the placeholder name may be prefixed by a nesting level. Nesting allows you to refer to properties in other objects than the direct parent. The level is written as the placeholder name prefix, delimited by a colon :. For example, 2:user-id.

The default level is 1, meaning that the placeholder user-id is equivalent to 1:user-id and that the property path will be searched in the direct parent of the child job. The level is counted from the child ‘upwards’. Therefore a placeholder 2:user-id means that the property path will be searched in the parent of the child parent (two levels up). See the corresponding examples.

Filter

The configuration option recursionFilter allows you to skip some child jobs. This can be useful in these cases:

• Some resources are not accessible to you and querying them would cause an error in the extraction.
• Some resources return inconsistent or incomplete responses.
• You are not interested in some of the resources and want to speed up the extraction.

The responseFilter configuration contains a string expression with a filter condition composed of the following:

• Name of a property from the parent response
• Comparison operator: <, >, <=, >=, == (equal), != (not equal), ~~ (like), !~ (unlike)
• Value to compare
• Logical operators: | (or), & (and); optionally, they may be used to join multiple conditions.

An example response filter may be type!=employee or product.value>150. To test for an empty value (null, false, "", 0) do not use any value — e.g. type!= filter matches an empty value.

Caution

The expression is whitespace sensitive. Therefore type != employee filters the "type " property to not contain the value " employee" (which is probably not what you intended to do). String comparisons are always case sensitive.

Examples

This section contains a number of examples using child jobs.

Basic Example

Let’s say that you have an API with two endpoints:

• /users/ --- Returns a list of users.
• /user/? --- Returns user details with a given user ID.

The users endpoint returns a response like this:

[
    {
        "id": 123,
        "name": "John Doe"
    },
    {
        "id": 234,
        "name": "Jane Doe"
    }
]

The user/123 endpoint returns a response like this:

{
    "id": 123,
    "name": "John Doe",
    "address": {
        "city": "London",
        "country": "UK",
        "street": "Whitehaven Mansions"
    }
}

Now use the following configuration, retrieving the user list and user details for each user:

{
    "parameters": {
        "api": {
            "baseUrl": "http://example.com/"
        },
        "config": {
            "outputBucket": "mock-server",
            "jobs": [
                {
                    "endpoint": "users",
                    "children": [
                        {
                            "endpoint": "user/{user-id}",
                            "dataField": ".",
                            "placeholders": {
                                "user-id": "id"
                            }
                        }
                    ]
                }
            ]
        }
    }
}

The jobs section defines a single job for the users resource. This job has child jobs for the users/{user-id} resource. The user-id placeholder in the endpoint URL is replaced by the value of the id property of each user in the parent job response. This means that Generic Extractor makes three API calls:

• users
• users/123
• users/234

The dataField is set to a dot to retrieve the entire response as a single object. Running Generic Extractor produces the following tables:

users:

id	name
123	John Doe
234	Jane Doe

user__user-id:

id	name	address_city	address_country	address_street	parent_id
123	John Doe	London	UK	Whitehaven Mansions	123
234	Jane Doe	St Mary Mead	UK	High Street	234

Notice that the table representing child resources contains all the responses merged into a single table; the usual merging rules apply.

Also notice that a new column --- parent_id was added, containing the placeholder value used to retrieve the resource. The parent_id column is not always named parent_id. Its name is created by joining the parent_ prefix to the placeholder path.

To create a friendly name for the table, it is good to use the dataType property (see the next example). The auto-generated name is rather ugly.

See example [EX021].

Basic Job With Data Type

To avoid automatic table names, it is advisable to always use the dataType property for child jobs:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "user-id": "id"
                }
            }
        ]
    }
]

In the above configuration, dataType is set to user-detail, hence you will obtain the following tables:

users:

id	name
123	John Doe
234	Jane Doe

user-detail:

id	name	address_city	address_country	address_street	parent_id
123	John Doe	London	UK	Whitehaven Mansions	123
234	Jane Doe	St Mary Mead	UK	High Street	234

See example [EX022].

Basic Job With Array Values

It is also possible that the main job returns objects which contain direct references to the children:

[
    {
        "id": 123,
        "name": "John Doe",
        "children": ["a1", "a2"]
    },
    {
        "id": 234,
        "name": "Jane Doe",
        "children": ["a3"]
    }
]

The following configuration is the same as in the previous example:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{child-id}",
                "dataField": ".",
                "placeholders": {
                    "child-id": "children"
                }
            }
        ]
    }
]

The child jobs will iterate both over the returned array of objects and the array of each children. Therefore the following tables will be extracted:

users:

id	name
123	John Doe
234	Jane Doe

user-child:

id	name	address_city	address_country	address_street	parent_children
a1	John Doe	London	UK	Whitehaven Mansions	a1
a2	Jane Doe	St Mary Mead	UK	High Street	a2
a3	Jimmy Doe	Scaryville	Nowhere	Cemetery Lane	a3

See example [EX135].

Accessing Nested ID

If the placeholder value is nested within the response object, you can use dot notation to access child properties of the response object. For instance, if the parent response with a list of users returns a response similar to this:

[
    {
        "name": "John Doe",
        "user-info": {
            "id": 123,
            "active": true
        }
    },
    {
        "name": "Jane Doe",
        "user-info": {
            "id": 234,
            "active": false
        }
    }
]

you have to modify the placeholders definition:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "user-id": "user-info.id"
                }
            }
        ]
    }
]

Setting the placeholder to "user-id": "user-info.id" means that the user-id placeholder will be replaced by the value of the id property inside the user-info object in the parent response. If you fail to set a correct path for the placeholder, you will receive an error:

`No value found for user-id in the parent result. (level: 1)`

When you set the correct path, you will get the following tables:

users:

name	user-info_id	user-info_active
John Doe	123	1
Jane Doe	234

user detail:

id	name	address_city	address_country	address_street	parent_user-info_id
123	John Doe	London	UK	Whitehaven Mansions	123
234	Jane Doe	St Mary Mead	UK	High Street	234

Notice that the parent reference column name is the concatenation of the parent prefix and user-info_id placeholder path (with special characters replaced by the underscore _).

See example [EX023].

Accessing Deeply Nested Id

The placeholder path is configured relative to the extracted object. Assume that the parent endpoint returns a complicated response like this:

{
    "active-users": {
        "items": [
            {
                "name": "John Doe",
                "user-info": {
                    "id": 123,
                    "active": true
                }
            },
            {
                "name": "Jane Doe",
                "user-info": {
                    "id": 234,
                    "active": true
                }
            }
        ],
        "description": "Active Users"
    },
    "inactive-users": {
        "items": [
            {
                "name": "Jimmy Doe",
                "user-info": {
                    "id": 345,
                    "active": false
                }
            }
        ],
        "description": "Inactive Users"
    }
}

The following job definition extracts the active-users array together with the details for each user:

"jobs": [
    {
        "endpoint": "users",
        "dataField": "active-users.items",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "user-id": "user-info.id"
                }
            }
        ]
    }
]

Notice that the placeholder path remains set to user-info.id because it is relative to the parent object, which itself is located at the path active-users.items. This may be confusing because the endpoint property in that child job is set relative to the api.baseUrl and not to the parent URL.

See example [EX024].

Naming Conflict

Because a new column is added to the table representing child properties, it is possible that you run into a naming conflict. That is, if the child response with user details looks like this:

{
    "id": 123,
    "name": "John Doe",
    "parent_id": "admins",
    "address": {
        "city": "London",
        "country": "UK",
        "street": "Whitehaven Mansions"
    }
}

and you use the following job configuration:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "placeholders": {
                    "user-id": "id"
                }
            }
        ]
    }
]

the output for the child job will contain the column parent_id. At the same time, Generic Extractor will attempt to create the column parent_id with the placeholder value, overwriting the original column. That column will be lost.

See example [EX025].

Nesting Level

By default, the placeholder value is taken from the object retrieved in the parent job. As long as the child jobs are nested only one level deep, there is no other option anyway. Let’s see what happens with a deeper nesting.

Assume that you have an API with the following endpoints:

• /users/ --- Returns a list of users.
• /user/? --- Returns user details with given user ID.
• /user/?/orders --- Returns a list of user orders.
• /user/?/orders/? --- Returns order detail with given user and order ID.

The users endpoint returns a response like this:

[
    {
        "userId": 123,
        "name": "John Doe"
    },
    {
        "userId": 234,
        "name": "Jane Doe"
    }
]

The user/123 endpoint returns a response like this:

{
    "userId": 123,
    "name": "John Doe",
    "description": "Good ol' father John"
}

The user/123/orders endpoint returns a response like this:

[
    {
        "orderId": "1234",
        "price": "$12"
    },
    {
        "orderId": "1345",
        "price": "$1212"
    }
]

The user/123/order/1234 endpoint returns a response like this:

{
    "orderId": 1234,
    "price": "$12",
    "timestamp": "2017-05-06 8:21:45",
    "state": "cancelled"
}

Then you can create a job configuration with three nested children to retrieve all the API resources:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{1:user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "1:user-id": "userId"
                },
                "children": [
                    {
                        "endpoint": "user/{2:user-id}/orders",
                        "dataType": "orders",
                        "placeholders": {
                            "2:user-id": "userId"
                        },
                        "children": [
                            {
                                "endpoint": "user/{3:user-id}/order/{1:order-id}",
                                "dataType": "order-detail",
                                "dataField": ".",
                                "placeholders": {
                                    "3:user-id": "userId",
                                    "1:order-id": "orderId"
                                }
                            }
                        ]
                    }
                ]
            }
        ]
    }
]

The jobs configuration retrieves all users from the users API endpoint. The first child retrieves details for each user (from user/? endpoint) and stores them in the user-detail table. The second child retrieves each user orders (from user/?/orders endpoint) and stores them in the orders table. Finally, the deepest nested child returns details of each order (for each user) from the user/?/order/? endpoint and stores them in the order-detail table. Therefore the following four tables will be produced:

users:

userId	name
123	John Doe
234	Jane Doe

user-detail:

userId	name	description	parent_userId
123	John Doe	Good ol’ father John	123
234	Jane Doe	Good young mommy Jenny	234

orders:

orderId	price	parent_userId
1234	$12	123
1345	$1212	123
2345	$42	234

order-detail:

orderId	price	timestamp	state	parent_userId	parent_orderId
1234	$12	2017-05-06 8:21:45	cancelled	123	1234
1345	$1212	2017-12-24 12:30:53	delivered	123	1345
2345	$42	2017-01-12 2:12:43	cancelled	234	2345

Notice that each table contains additional columns with the placeholder property path prefixed with parent_.

See example [EX026].

Nesting Level Alternative

Because the required user and order IDs are present in multiple requests (in the list and in the detail), there are multiple ways how the jobs may be configured. For example, the following configuration produces the exact same result as the above configuration:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "user-id": "userId"
                },
                "children": [
                    {
                        "endpoint": "user/{user-id}/orders",
                        "dataType": "orders",
                        "children": [
                            {
                                "endpoint": "user/{user-id}/order/{order-id}",
                                "dataType": "order-detail",
                                "dataField": ".",
                                "placeholders": {
                                    "order-id": "orderId"
                                }
                            }
                        ]
                    }
                ]
            }
        ]
    }
]

Even though the above configuration is less explicit and not really recommended, it is still acceptable. Placeholders are defined globally, which means that the second nested child job to user/{user-id}/orders does not define any because it relies on those defined by its parent job (which happen to be correct). Also the deepest child defines only the order-id placeholder because, again, the user-id placeholder was defined in some of its parents.

Although the placeholders are defined globally, the ones defined in child jobs override the ones in the parent jobs. For example, in the following (probably very incorrect) configuration, the 1:user-id placeholder in the deepest child will really contain the orderId value.

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{1:user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "1:user-id": "userId"
                },
                "children": [
                    {
                        "endpoint": "user/{2:user-id}/orders",
                        "dataType": "orders",
                        "placeholders": {
                            "2:user-id": "userId"
                        },
                        "children": [
                            {
                                "endpoint": "user/{1:user-id}/order/{2:order-id}",
                                "dataType": "order-detail",
                                "dataField": ".",
                                "placeholders": {
                                    "1:user-id": "orderId",
                                    "2:order-id": "userId"
                                }
                            }
                        ]
                    }
                ]
            }
        ]
    }
]

See example [EX027].

Deep Job Nesting

Let’s look at how to retrieve more nested API resources:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{1:user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "1:user-id": "id"
                },
                "children": [
                    {
                        "endpoint": "user/{2:user-id}/orders",
                        "dataType": "orders",
                        "placeholders": {
                            "2-user-id": "id"
                        },
                        "children": [
                            {
                                "endpoint": "user/{3:user-id}/order/{1:order-id}",
                                "dataType": "order-detail",
                                "dataField": ".",
                                "placeholders": {
                                    "3:user-id": "id",
                                    "1:order-id": "id"
                                },
                                "children": [
                                    {
                                        "endpoint": "user/{4:user-id}/order/{2:order-id}/items",
                                        "dataType": "order-items",
                                        "placeholders": {
                                            "4:user-id": "id",
                                            "2:order-id": "id"
                                        },
                                        "children": [
                                            {
                                                "endpoint": "user/{5:user-id}/order/{3:order-id}/item/{1:item-id}",
                                                "dataType": "item-detail",
                                                "dataField": ".",
                                                "placeholders": {
                                                    "5:user-id": "id",
                                                    "3:order-id": "id",
                                                    "1:item-id": "id"
                                                }
                                            }
                                        ]
                                    }
                                ]
                            }
                        ]
                    }
                ]
            }
        ]
    }
]

The above configuration assumes that all API resources simply have an id property (unlike in the previous example, where the users had userId and the orders had orderId). This makes the configuration look rather cryptic. Read the deepest child placeholder configuration

"5:user-id": "id",
"3:order-id": "id",
"1:item-id": "id"

as:

• Go five levels up, pick the id property from the response and put it in place of the user-id in the endpoint URL.
• Go three levels up, pick the id property from the response and put it in place of the order-id in the endpoint URL.
• Go one level up, pick the id property from the response and put it in place of the item-id in the endpoint URL.

Caution

Once you run into using placeholders with the same property path, their order becomes important. This is because the property path is used as the name of an additional column in the extracted table. Because the property path is id in all cases, it will lead to the column parent_id in all cases, and therefore it will get overwritten. With the above configuration, the following item-detail table will be produced:

id	code	name	parent_id
345	PA10	Pick Axe	345
456	TB20	Tooth Brush	456

where the parent_id column refers to the 1:item-id placeholder. If you used this placeholder configuration:

"placeholders": {
    "1:item-id": "id",
    "3:order-id": "id",
    "5:user-id": "id"
}

you would obtain the following item-detail table:

id	code	name	parent_id
345	PA10	Pick Axe	123
456	TB20	Tooth Brush	123

where the parent_id column refers the 5:user-id placeholder.

See example [EX028].

Nested Array

Suppose now that the endpoint /users returns a more complicated response:

{
    "members": {
        "description": "Active System Members",
        "tags": [
            "active",
            "crm"
        ],
        "count": "2",
        "items": [
            {
                "name": "John Doe",
                "user-info": {
                    "id": 123,
                    "active": true
                }
            },
            {
                "name": "Jane Doe",
                "user-info": {
                    "id": 234,
                    "active": false
                }
            }
        ]
    }
}

The API also has an endpoint /user/{userId} which returns details about a specific user. If you want to obtain all the fields from the above response and also the details about each user, you have to create a rather tricky configuration. Even though you may be tempted to start with the following job configuration:

{
    "endpoint": "users",
    "dataField": "."
}

this is not possible because the root of the response in the members field is not an array and therefore it cannot create child jobs. For that reason the job configuration must start with:

{
    "endpoint": "users",
    "dataField": "members.items",
}

The members.items is an array which now can be used as a source for child jobs:

{
    "endpoint": "users",
    "dataField": "members.items",
    "dataType": "users",
    "children": [
        {
            "endpoint": "user/{user-id}",
            "dataField": ".",
            "dataType": "user-detail",
            "placeholders": {
                "user-id": "user-info.id"
            }
        }
    ]
}

Notice that the placeholder path (user-info.id) is entered relative to the dataField setting (members.items). Now, to extract the other fields from the /users response (other than member.items), create another job:

{
    "endpoint": "users",
    "dataField": ".",
    "dataType": "users-2"
}

Note that the dataType must be different than in the first job because the structure of the response is different. You will receive a number of tables:

users (first job):

name	user-info_id	user-info_active
John Doe	123	1
Jane Doe	234

user-detail (first job children):

id	name	address_city	address_country	address_street	parent_user-info_id
123	John Doe	London	UK	Whitehaven Mansions	123
234	Jane Doe	St Mary Mead	UK	High Street	234

users-2 (second job):

members_description	members_tags	members_count	members_items
Active System Members	users-2.members_c6eb0647a7f2fb2cbe02ba62d56e3312	2	users-2.members_c6eb0647a7f2fb2cbe02ba62d56e3312

users-2_members_items (second job, generated from array node items):

name	user-info_id	user-info_active	JSON_parentId
John Doe	123	1	users-2.members_c6eb0647a7f2fb2cbe02ba62d56e3312
Jane Doe	234		users-2.members_c6eb0647a7f2fb2cbe02ba62d56e3312

The users-2\_members\_items contains the same results as the users table, but it also contains the JSON\_parentId column which allows you to link the user list to the list description in the users-2 table. This makes the response in the users table quite useless, but the job is still required to generate the child jobs to obtain the user-detail table. See example [EX106].

Simple Filter

Let’s assume that you have an API which has two endpoints:

• users --- Returns a list of users.
• users/? --- Returns a user detail.

The users endpoint returns a response like this:

[
    {
        "id": 123,
        "name": "John Doe",
        "role": "parent",
        "type": "admin"
    },
    {
        "id": 234,
        "name": "Jane Doe",
        "role": "parent",
        "type": "administrator"
    },
    {
      "id": 345,
      "name": "Jimmy Doe",
      "role": "child",
      "type": "user"
    },
    {
      "id": 456,
      "name": "Janet Doe",
      "role": "child",
      "type": "user"
    }
]

The user/123 endpoint returns a response like this:

{
    "id": 123,
    "name": "John Doe",
    "userRole": "parent",
    "userType": "admin",
    "description": "Father John"
}

A simple child filter can be then set up using the following jobs configuration:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "placeholders": {
                    "user-id": "id"
                },
                "recursionFilter": "role==parent"
            }
        ]
    }
]

The recursionFilter setting will cause Generic Extractor to query only the sub-resources for which the filter evaluates to true. The filter property name type refers to the parent response, but it filters only the children. So, the following tables will be returned:

users:

id	name	role	type
123	John Doe	parent	admin
234	Jane Doe	parent	administrator
345	Jimmy Doe	child	user
456	Janet Doe	child	user

user-detail:

id	name	userRole	userType	description	parent_id
123	John Doe	parent	admin	Father John	123
234	Jane Doe	parent	administrator	Mother Jane	234

You can see from the above tables that the filter is applied to the child results only so that the details are retrieved only for the desired users.

See example [EX029].

Not Like Filter

Apart from the standard comparison operators, the recursive filter allows to use a like comparison operator ~. It expects that the value contains a placeholder %, which matches any number of characters. The following configuration:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "recursionFilter": "type!~%min%",
                "dataType": "user-detail",
                "placeholders": {
                    "user-id": "id"
                }
            }
        ]
    }
]

filters out all child resources not containing the string min in their parent type property. The expression %min% matches any string which contains any number of characters (including none) before and after the string min. The operator !~ is negative like, therefore the following user-detail table will be extracted:

id	name	userRole	userType	description	parent_id
345	Jimmy Doe	child	user	Sonny Jimmy	345
456	Janet Doe	child	user	Missy Jennie	456

See example [EX030].

Combining Filters

Multiple filters can be combined using the logical & (and) and | (or) operators. For example, the following configuration retrieves details for users who have both id < 400 and role = child:

"jobs": [
    {
        "endpoint": "users",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "dataType": "user-detail",
                "recursionFilter": "id<400&role==child",
                "placeholders": {
                    "user-id": "id"
                }
            }
        ]
    }
]

The following user-detail will be produced:

id	name	userRole	userType	description	parent_id
345	Jimmy Doe	child	user	Sonny Jimmy	345

See example [EX031].

Multiple Filter Combinations

Although you can join a multiple filter expression with logical operators as in the above example, there is no support for parentheses. The following configuration combines multiple filters:

"jobs": [
    {
        "endpoint": "users",
        "recursionFilter": "role=parent|id>300&id<400",
        "children": [
            {
                "endpoint": "user/{user-id}",
                "dataField": ".",
                "placeholders": {
                    "user-id": "id"
                }
            }
        ]
    }
]

The precedence of logical operators is defined so that the first operator occurring in the expression takes precedence over the second. That is to say that the condition role=parent|id>300&id<400 is interpreted as role=parent|(id>300&id<400) because the operator | takes precedence over the & operator. The condition id>300&id<400|role==parent is interpreted as id>300&(id<400|role==parent) because the & operator takes precedence over the | operator.

With the above configuration, the following user-detail table will be produced:

id	name	userRole	userType	description	parent_id
123	John Doe	parent	admin	Father John	123
234	Jane Doe	parent	administrator	Mother Jane	234
345	Jimmy Doe	child	user	Sonny Jimmy	345

Because the described system of operator precedence may lead to rather unusual behaviour, we recommend that you keep the recursive filter simple.

See example [EX032].