All About DCVS Ingestion Errors

[Barry_Mann]

Adobe AEP — Solving DCVS ingestion errors

Updating Media

Barry Mann

17 min read

•  

1 day ago

Updating Media

What are ingestion errors?

In Adobe Experience Platform (AEP), ingestion errors can occur while importing data, either in batches or streamed. There is no special reason to give the two ingestion methods different treatments.

Any dataset can be affected, here we shall consider only the Web Event Dataset, as this is where problems are concentrated in day-to-day operations. The current client has 62 datasets.

The dataset “prod — Web Event Data’ is associated with our schema constructed from field groups: Adobe Analytics ExperienceEvent Template, Adobe & Full extension, plus several other field groups added in a cumulative ad-hoc fashion.

Ingestion errors should not be confused with dataflow run errors:

Updating Media

INGEST-1554–400 Errors — Within datflow

Dataflow error preview.

These are also ingestion errors, but not of a type relevant here. Dataflow errors are documented.

This article covers DCVS errors which are completely undocumented.

Mismatch

Which Adobe products are affected?

RT-CDP & CJA are principally affected since CJA is an application on the platform. Looking at the overview diagram, AJO ought to be afflicted too.

Adobe Analytics which is much more forgiving, its data is unaffected.

In AA, minor data errors or inconsistencies can be handled, in RT-CDP entire batches can be rejected!

What is the consequence of failure to ingest?

Missing data will result in:

• Incomplete customer profiles
• Impaired segmentation and targeting
• Reduced personalisation effectiveness
• Delayed or inaccurate analytics (within CJA or RT-CDP Audience sizes)
• Activation issues
• Compliance and governance risks (if consent information is included)
• Reduced ROI
• Impaired ML & AI Capabilities
• Operational Difficulties

In simple layman's terms:

• The customer may be treated as abandoned when they have purchased.
• Guests may be nudged to re-engage to complete an action which they have already completed
• Nudging fans to complete post-event surveys which they have already completed
• Retargeting those via display advertising for actions already completed
• Sending emails eg abandoned cart emails for actions already complete
• Treating the customer as opt-in when they are opted out

…. All because the data points were not ingested into the platform!

Ingestion error codes

There are many codes, however, the vast bulk of error codes seen are of type DCVS. There is no mention of these codes on Experience League, only some chatter in communities, one of which is mine! Google/Perplexity reveal no hits!

DCVS-1101–400 (null found) (rarer)

DCVS-1101–400

This appears to mainly around null values:

Examples:

The message cannot be validated: [#/_clientnamespace/product/0/businessGroup: expected type: JSONArray, found: String]. The message cannot be validated:

[#/_clientnamespace/product/0/businessGroup/0: expected type: String, found: Null]. The message cannot be validated:

[#/_clientnamespace/product/0/businessGroup/0: expected type: String, found: Null]. The message cannot be validated:

[#/_clientnamespace/product/2/businessGroup/0: expected type: String, found: Null]. The message cannot be validated:

[#/_clientnamespace/product/2/businessGroup/0: expected type: String, found: Null]. The message cannot be validated:

[#/_clientnamespace/product/0/businessGroup: expected type: JSONArray, found: String]. The message cannot be validated:

[#/_clientnamespace/product/1/businessGroup/0: expected type: String, found: Null]. The message cannot be validated:

[#/_clientnamespace/product/1/businessGroup/0: expected type: String, found: Null]. The message cannot be validated:

[#/_clientnamespace/product/1/businessGroup/0: expected type: String, found: Null].

We will refer to these as ‘Type 1’

DCVS-1103–400 (pattern mismatch)

Very rarely seen.

The message cannot be validated due to the pattern mismatch error:

#/commerce/order/currencyCode: string [????] does not match pattern ^[A-Z]{3}$.

We will refer to this as ‘Type 3’

DCVS-1104–400 (mismatch)

This error indicates that there’s a mismatch between the data type of a field in your incoming data and the data type defined in the XDM schema.

DCVS-1104–400 The message cannot be validated due to the data type error: #/commerce/order/priceTotal: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems: expected type: JSONArray, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_clientnamespace/product/0/businessGroup/0: expected type: String, found: Null.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_experience/analytics/event101to200/event184/value: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_clientnamespace/product/0/businessGroup: expected type: JSONArray, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_clientnamespace/product/0/businessGroup/0: expected type: String, found: Null.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_experience/analytics/customDimensions/eVars/eVar57: expected type: String, found: Integer.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_clientnamespace/product/0/businessGroup/0: expected type: String, found: Null.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/0/quantity: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/0/quantity: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_clientnamespace/product/0/businessGroup/0: expected type: String, found: Null.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_experience/analytics/event101to200/event182/value: expected type: Number, found: Null.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_experience/analytics/customDimensions/eVars/eVar57: expected type: String, found: Integer.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/0/quantity: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_experience/analytics/customDimensions/eVars/eVar89: expected type: String, found: JSONObject.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/0/quantity: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/marketing/trackingCode: expected type: String, found: JSONArray.

DCVS-1104–400 The message cannot be validated due to the data type error: #/_clientnamespace/product/0/businessGroup/0: expected type: String, found: Null.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/5/quantity: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/1/quantity: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/1/quantity: expected type: Number, found: String.

DCVS-1104–400 The message cannot be validated due to the data type error: #/productListItems/5/quantity: expected type: Number, found: String.

We will call this ‘Type 4’

DCVS-1106–400 (required field missing)

This error suggests that a required field in the XDM schema is missing from your incoming data.

The message cannot be validated because a required property is missing: #/_experience/analytics/event101to200/event110: required key [value] not found.

The message cannot be validated because a required property is missing: #/productListItems/0: required key [SKU] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event80: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event25: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event26: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event19: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event18: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event101to200/event114: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event19: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event25: required key [value] not found.

The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event18: required key [value] not found.

We will refer to these as ‘Type 6’

Datatype Basics — a refresher

Integers

{ "productPrice": 199.99 }

Strings

{ "productName": "Smartphone" }

dateTime

{ "purchaseDate": "2024-09-19T15:30:00Z" }

Boolean

{ "isAvailable": true }

Ok that's the simple stuff, now it gets involved:

array of strings

{ "ProductMarkets": ["US", "EU", "Asia"] }

Object

{ "product": { "SKU": "12345", "description": "High-quality smartphone" } }

Datatypes II — now it is getting hairy

This is where we experienced difficulty.

An array of strings found in our JSON sample file (see next section)

{
  "businessGroup": ["Sample value"]
}

Objects

{
  "product": {
    "SKU": "Sample value",
    "businessGroup": ["Sample value"],
    "description": "Sample value"
  }
}

JSON Nested Objects

{
  "webInteraction": {
    "URL": "Sample value",
    "linkClicks": {
      "id": "Sample value",
      "value": 29138.61
    }
  }
}

Array of objects, An array of objects is found in fields like product, where each object contains multiple properties:

{
  "product": [
    {
      "SKU": "Sample value",
      "business": [
        {
          "businessID": "Sample value",
          "businessName": "Sample value"
        }
      ],
      "businessGroup": ["Sample value"],
      "description": "Sample value"
    }
  ]
}

Using the sample file

This will allow for experimentation and testing of files and formats, seeing which errors are generated.

Processing times on an empty sandbox are <1 minute

Download Sample file in UI

 "_experience": {
    "analytics": {
      "contextData": {
        "key": "Sample value"
      },
      "customDimensions": {
        "eVars": {
          "eVar1": "Sample value",
          "eVar10": "Sample value",
          "eVar100": "Sample value",
          "eVar101": "Sample value",
          "eVar102": "Sample value",
          // ... (other eVars omitted for brevity)
          "eVar159": "Sample value"
        }
      }
    }

eVars expect strings and cannot be altered:

window.adobeDataLayer = window.adobeDataLayer || [];
window.adobeDataLayer.push({
  "event": "eVar1Update",
  "_experience": {
    "analytics": {
      "customDimensions": {
        "eVars": {
          "eVar1": "Example eVar1 value" // this is CORRECT
        }
      }
    }
  }
});
    }

window.adobeDataLayer = window.adobeDataLayer || [];
window.adobeDataLayer.push({
  "event": "eVar1Update",
  "_experience": {
    "analytics": {
      "customDimensions": {
        "eVars": {
          "eVar1": 1234 // This will FAIL
        }
      }
    }
  }
});

events expect integers, and are locked…

{
  "_experience": {
    "analytics": {
      "event101to200": {
        "event101": {
          "id": "Sample value",
          "value": 813.52
        },
        "event102": {
          "id": "Sample value",
          "value": 25240.48
        },
        "event103": {
          "id": "Sample value",
          "value": 6329.62
        },
        "event104": {
          "id": "Sample value",
          "value": 5819.11
        },
        "event105": {
          "id": "Sample value",
          "value": 5811.46
        },
        // ... (other events omitted for brevity)
        "event135": {
          "id": "Sample value",
          "value": 28647.86
        }
      }
    }
  }
}

Testing Methodology

Workflow:

• Create a new schema
• Create a new dataset from that schema
• After schema alteration, download the sample file
• Deliberately break the sample file and upload:

enabling error diagnostics

Note the odd UI, enable Error diagnostics then move upward to select the file. Press 1 then upward to 2, as you will need error diagnostics.

A successful file ingest will look like this:

If you don’t enable error diagnostics, you will get:

If successful, the API will show you the batch file location:

https://platform.adobe.io/data/foundation/catalog/batches/:BATCH_ID

{
    "01J8J0H2YJDH794W7RE7R5T51T": {
        "status": "success",
        "tags": {
            "acp_stagePath": [
                "acp_foundation_push/stage/01J8J0H2YJDH794W7RE7R5T51T"
            ],
            "acp_sloPolicyName": [
                "live10Mb"
            ],
            "aep/siphon/partitions/paths": [],
            "acp_finalized_time": [
                "1727181410455"
            ],
            "acp_workflow": [
                "ValveWorkflow"
            ],
            "numberOfDSFs": [
                "0"
            ],
            "acp_requestType": [
                "user"
            ],
            "acp_enableErrorDiagnostics": [
                "true"
            ],
            "acp_latencyTargetInMillis": [
                "300000"
            ],
            "acp_dataSetViewId": [
                "66f2b241a985222aedc14c00"
            ],
            "acp_type": [
                "ingest"
            ],
            "siphon/valve/stage/ingest": [
                "{\"id\":\"2d7555521a224148bfd1db94df326f25\",\"status\":\"created\",\"createdAt\":1727181396912,\"batchId\":\"01J8J0H2YJDH794W7RE7R5T51T\",\"imsOrg\":\"988D095F54BD18520A4C98A5@AdobeOrg\",\"bulkHead\":\"live\",\"service\":\"platform.siphon.ingest\",\"properties\":{}}"
            ],
            "siphon/valve/ingest/status": [
                "{\"id\":\"2d7555521a224148bfd1db94df326f25\",\"status\":\"finished\",\"createdAt\":1727181408642,\"batchId\":\"01J8J0H2YJDH794W7RE7R5T51T\",\"imsOrg\":\"988D095F54BD18520A4C98A5@AdobeOrg\",\"bulkHead\":\"live\",\"output\":\"/acp_foundation_push/stage/01J8J0H2YJDH794W7RE7R5T51T-staged/attempt-01J8J0HH9H8WN4RBJ10D0NCS23\",\"sandbox\":{\"sandboxId\":\"84b47ce0-4d40-4137-b47c-e04d40b137ea\",\"sandboxName\":\"inspire-ucp\"},\"properties\":{\"tableCommit\":{\"masterSnapshotId\":\"1\"}}}"
            ],
            "acp_bulkHead": [
                "live"
            ],
            "acp_producer": [
                "exc_app",
                "aep/siphon/bi/uploadMode::"
            ],
            "acp_requestId": [
                "qLeHBnphtczpTmRtkA8W1nbIpfsZbuyD"
            ],
            "acp_finalized": [
                "finalized"
            ],
            "acp_buffered": [
                "false"
            ],
            "acp_latencyMaxInMillis": [
                "10800000"
            ]
        },
        "relatedObjects": [
            {
                "type": "dataSet",
                "id": "66f2b241a985222aedc14bff"
            }
        ],
        "id": "01J8J0H2YJDH794W7RE7R5T51T",
        "externalId": "01J8J0H2YJDH794W7RE7R5T51T",
        "inputFormat": {
            "format": "json",
            "isMultiLineJson": false
        },
        "imsOrg": "988D095F54BD18520A4C98A5@AdobeOrg",
        "sandboxId": "84b47ce0-4d40-4137-b47c-e04d40b137ea",
        "createdUser": "40770A6762E59BEF0A495ED8@3ce86b6a62e59be9495ef9.e",
        "started": 1727181395892,
        "metrics": {
            "failedRecordCount": 0,
            "partitionCount": 0,
            "outputByteSize": 8218,
            "inputFileCount": 1,
            "inputByteSize": 349,
            "outputRecordCount": 1,
            "outputFileCount": 1,
            "inputRecordCount": 1
        },
        "completed": 1727181409894,
        "errors": [],
        "created": 1727181393108,
        "createdClient": "acp_foundation_push",
        "updatedUser": "acp_foundation_dataTracker@AdobeID",
        "updated": 1727181410468,
        "version": "1.0.6"
    }
}

If you didn't enable diagnostics , The API will not show the ndjson (newline delimited json) path:

{
    "data": [
        {
            "name": "66f2b241a985222aedc14c00",
            "length": "0",
            "_links": {
                "self": {
                    "href": "https://platform.adobe.io:443/data/foundation/export/batches/01J8J324F5MFTHE5JX48P4QM5N/failed?path=..." // The NDjson path is missing
                }
            }
        }
    ],
    "_page": {
        "limit": 100,
        "count": 1
    }
}

Uploading the sample file with deliberately bad data will generate an error.

{
    "_clientnamespace":
    {
        "documentation test - 23 Sept 2024 - 12:42 GMT": "Sample value", // bad
        "test2": 9540,
        "test3": false,
        "test4":
        {
            "key": "Sample value"
        }
    },
    "_id": "/uri-reference",
    "eventMergeId": "Sample value",
    "eventType": "advertising.completes",
    "identityMap":
    {
        "key":
        [
            {
                "authenticatedState": "ambiguous",
                "id": "Sample value",
                "primary": false
            }
        ]
    },
    "producedBy": "self",
    "timestamp": "2018-11-12T20:20:39+00:00"
}

The field: _clientnamespace. documentation test — 23 Sept 2024–12:42 GMT does not exist in the target schema. Please remove the field and try again.

Testing results & many real-world failure examples:

By looking at failed batches:

Error:

_errors": {
            "_streamingValidation": [
                {
                    "path": "#/_dow/product",
                    "code": "DCVS-1104-400",
                    "message": "The message cannot be validated due to the data type error: #/_dow/product: expected type: JSONArray, found: JSONObject.",
                    "errorType": 0
                }
            ]
        }

Payload:

    "_dow": {
                    "product": {
                        "pdpBannerImage": "/content/dam/images/public-images/web/pdp/pdppgheader/dow_54812013514-pdppgbanner-red-molecules-2000x160.jpg",
                        "description": "A general purpose rigid foam silicone surfactant surfactant for production of rigid polyurethane foam.",
                        "products": [
                            {
                                "businessGroup": [
                                    "CONSUMER SOLUTIONS"
                                ],
                                "business": [
                                    {
                                        "businessID": "DCS",
                                        "businessName": "Consumer Solutions"
                                    }
                                ],
                                "SKU": "497615z"
                            }
                        ]
                    }
                },

Bug: The data snippet you’ve provided is a JSON object, not an array.

Here’s why:

• It uses curly braces {} at the outermost level, which is the syntax for a JSON object.
• The structure contains key-value pairs, where each key (e.g., "_dow", "product", "description") is associated with a value. This is characteristic of an object.

In contrast, a JSON array would be enclosed in square brackets [] and consist of a list of values.

.. ah ha!!!

Error:

   "_errors": {
            "_streamingValidation": [
                {
                    "path": "#/_experience/analytics/event1to100/event80",
                    "code": "DCVS-1106-400",
                    "message": "The message cannot be validated because a required property is missing: #/_experience/analytics/event1to100/event80: required key [value] not found.",
                    "errorType": 0
                }
            ]

 "analytics": {
                        "event1to100": {
                            "event80": {
                                "id": "1"
                            }

Bug: XDM doesn't have value specified. It looks like somebody filled out the XDM incorrectly.

error:

 {
                    "path": "#/commerce/order/priceTotal",
                    "code": "DCVS-1104-400",
                    "message": "The message cannot be validated due to the data type error: #/commerce/order/priceTotal: expected type: Number, found: String.",
                    "errorType": 0
                },

Payload:

 "order": {
                        "priceTotal": "62251.2",
                        "purchaseID": "116676690",
                        "purchaseOrderNumber": "S100264-9",
                        "currencyCode": "USD"

[kautuk_sahni]

@Danny-Miller @SatheeskannaK @brekrut @Rite18 @Sneha-Parmar @abhinavbalooni Curious to hear SMEs perspectives on this question. Do you all mind sharing your thoughts?