MB-820 Practice Questions

Code Segment Analysis:

The AL code is trying to read JSON data from a response and process it to extract subcontracting order numbers. It uses JsonToken, JsonObject, and JsonArray to work with the JSON data.

JToken.ReadFrom(Data): This line reads the incoming JSON data and converts it into a token. It processes the full JSON body so you can start working with it.

JToken.SelectToken("results"): This line selects the part of the JSON containing the results array. The key "results" is where the JSON response data is expected to be found.

JsonArray: Once the results are extracted, they are stored as an array, and each element in the array (which is expected to contain subcontracting order numbers) is processed.

SubcontractingOrderNo: The extracted order_no from the JSON is stored in this variable.

Breakdown of Steps:

JToken.ReadFrom(Data): This step reads the entire JSON response.

JToken.SelectToken("results"): This step selects the results array from the JSON response.

JArray.AsArray(): This step converts the selected results token into a JSON array that can be iterated over.

GetValueAsText(JToken, 'order_no'): This step retrieves the order_no from each element in the array.

Correct Code Completion:

JToken.ReadFrom(Data): This is the correct method to read the incoming JSON response, as it will convert the string into a JsonToken that can be further processed.

JToken.SelectToken("results"): This is the correct method to extract the results array from the token. This method looks for the key "results" in the JSON and retrieves the relevant array.

Final Code Segment:

al

Copy code

procedure ReadJsonData(Data: text)

var

JToken: JsonToken;

JObject: JsonObject;

JArray: JsonArray;

SubcontractingOrderNo: Code[20];

begin

if Data = '' then

exit;

JToken := JToken.ReadFrom(Data); // Step 1: Read the JSON response data.

JToken := JToken.SelectToken('results'); // Step 2: Select the "results" array.

JArray := JToken.AsArray(); // Convert the token into a JSON array.

foreach JToken in JArray do begin

SubcontractingOrderNo := GetValueAsText(JToken, 'order_no'); // Retrieve the order number.

end;

end;

JToken.ReadFrom(Data): This reads the raw JSON data string and converts it into a JSON token that can be processed.

JToken.SelectToken("results"): This extracts the results array from the JSON data.

JArray.AsArray(): Converts the token into an array so we can iterate over it.

GetValueAsText(JToken, 'order_no'): Extracts the order_no value from each item in the array.

 Verbosity::Critical: This ensures that the telemetry logs the failure as a critical event.

 DataClassification::CustomerContent: This helps classify the error as related to customer data.

 TelemetryScope::All: This ensures that the error is visible across all relevant telemetry scopes, making it easier to monitor the issue in real-time.

The task is to identify unwanted incoming web service calls during the last seven days. To do this, we need to look at KQL (Kusto Query Language) queries that would filter out web service calls based on the timestamp (to ensure the calls are within the last seven days) and by certain characteristics that would indicate they are unwanted, such as the wrong type of protocol (SOAP in this case, as Contoso Ltd. plans to dismiss using it).

Looking at the options:

Option A: This query selects all traces where the timestamp is within the last 7 days and where the custom dimension has a value of 'RT0008', and where the category is either 'ODataV4', 'ODataV3', or 'Api'. This query would show all API calls except SOAP, so it does not directly answer the question about unwanted calls.

Option B: This query filters for traces with a timestamp within the last 7 days, where 'RT0008' is present, and specifically looks for the category 'SOAP'. This query is correct because it directly targets SOAP calls, which are the unwanted calls according to Contoso Ltd.'s plans.

Option C: Similar to option B, this query filters for traces within the last 7 days and looks for 'RT0008' but uses the equality operator for the category 'SOAP'. This would also correctly return the unwanted SOAP calls.

Option D: This query also filters for traces within the last 7 days, but it excludes the 'ODataV4' category, which doesn't necessarily target the unwanted SOAP calls.

Option E: This query selects traces where the timestamp is within the last 7 days and the custom dimension has 'RT0008'. However, it filters out categories 'ODataV4' and 'Api', which does not directly help in identifying the unwanted SOAP calls.

Therefore, the queries that should be used to determine if there are unwanted incoming web service calls (SOAP calls) in the tenant during the last seven days are Options B and

C.  

Here is the most logical sequence of actions for implementing the Issue Management module in Business Central and exposing the PostIssue method:

Correct Order:

Create a codeunit named "Issue Management Impl." and set the value of Access property to Internal.

This is the first step because Issue Management Impl. is the implementation layer where the actual business logic resides, and setting it to Internal ensures that it is only accessible from within the module, following best practices in encapsulation.

Create a local procedure named PostIssueImpl in the "Issue Management Impl." codeunit.

This step adds the actual PostIssueImpl method, which contains the core logic of posting an issue.

Create a codeunit named "Issue Management" and set the value of Access property to Public.

After defining the implementation logic, you need to create a public-facing Issue Management codeunit to expose the service externally.

Create a PostIssue procedure in the "Issue Management" codeunit, and in it call the PostIssueImpl method.

Lastly, expose the PostIssue method in the Issue Management codeunit, which will internally call the PostIssueImpl method, completing the chain.

 Upgrade codeunit trigger: OnValidateUpgradePerDatabase

Since the question specifies that you are handling data upgrades, and you need to use validation before upgrading at the database level, the correct choice is OnValidateUpgradePerDatabase. This method ensures that the upgrade process is validated before applying to the entire database, making it more efficient when data affects multiple companies or structures.

 DataTransfer method to use: CopyRows

CopyRows is the appropriate method when you are handling large data transfers between tables, especially in an upgrade scenario where you are migrating or transferring data from one table to another. It copies entire rows of data and is optimal for bulk data operations during upgrades.

 Add Clear(PurchaseLine); as a line before line 01 of the code: No

 Add PurchaseLine.SetFilter("Line No."; '>0') as a line after line 06: Yes

 Change the filter on line 06 from a "No." field to a "Document No." field: No

 Remove "not" in line 07: No

 Add Clear(PurchaseLine); as a line before line 01 of the code.

No

You do not need to clear the PurchaseLine record before running the query, because the SetRange filters will take care of setting the correct context.

 Add PurchaseLine.SetFilter("Line No."; '>0') as a line after line 06.

Yes

Adding a SetFilter on the "Line No." field ensures that you're checking for actual purchase lines greater than 0, which are valid lines. This would fix the issue where the check might return false even when lines exist.

 Change the filter on line 06 from a "No." field to a "Document No." field.

No

The filter on the No. field is correct, as it's filtering based on the purchase order number. Changing this to Document No. is unnecessary.

 Remove "not" in line 07.

No

The not in line 07 is necessary because IsEmpty() returns true when no lines are found. To correctly return a boolean indicating whether the purchase order has lines, you need to negate the result of IsEmpty().

KQL Code Segment:

First command (traces):

The query begins with traces to analyze telemetry data logs. The next command determines how the results are filtered or displayed.

take 100: This is the correct option to retrieve the top 100 rows from the traces table.

Command for selecting fields:

project: This command is used to select specific fields from the telemetry data, allowing you to retrieve and display only the fields relevant to the job queue telemetry.

The correct answer is project, as it allows you to choose fields like jobQueueObjectId, jobQueueObjectType, etc., from the customDimensions table.