Adaface Sample Talend Questions

Consider a Talend job that reads rows from a tFileInputDelimited component and intends to process them through a series of transformations. Here's a pseudocode representation of a segment of your Talend job:

You need to implement this logic within your Talend job such that rows with a "columnValue" greater than 100 follow one transformation path and others follow a different transformation path. Which of the following actions would help achieve this desired behavior?

A: Use a tFlowToIterate component after the tFileInputDelimited to iterate over rows and use a Java condition to route the data.
            B: In the tMap component, set filters on the output links to achieve conditional routing based on "columnValue".
            C: Place two tMap components side by side after tFileInputDelimited and use "columnValue" in each to filter rows.
            D: Use a tSplitRow component after tFileInputDelimited to split rows based on the condition and connect to respective tMap components.
            E: Implement a custom code component like tJavaRow to determine the flow of rows.

You're building a Talend job that integrates with an e-commerce platform's Product API. Over time, the platform has added, removed, or changed fields within the API response, making it a challenge to keep up with the schema changes. A typical API response might look like:

However, fields like specs might have additional attributes in the future, or some fields might be deprecated.
            
            The primary goal of your Talend job is:

Given this scenario, how should you best handle the dynamic nature of the Product API schema in your Talend job?

A: Use tExtractJSONFields and adjust the XPath query every time the API changes.
            B: Set a fixed schema in tMap based on the most common fields and ignore new additions.
            C: Define the input schema of tMap as "Dynamic", and map necessary fields to a stable output schema.
            D: Set the tOutputDB schema to "Dynamic" and let the database adjust to incoming changes.
            E: Process the raw JSON strings directly in tMap and use string manipulations for transformations.

You're working with three different data sources in a Talend job: a MySQL table (users), an Oracle table (transactions), and a CSV file (rewards). The goal is to create a report containing the user's name, total transaction amount, and reward points, but only for users who have both made a transaction and earned rewards. Here are the key columns from each source:
            
            - users: user_id, user_name
            - transactions: trans_id, user_id, amount
            - rewards: reward_id, user_id, points
            
            Which of the following sequences best accomplishes this?

A: Use tMySQLInput, tOracleInput, and tFileInputDelimited in parallel -> tDenormalize to combine all results. Filter and aggregate results using tMap and then pass to tOutput.
            B: Use tMySQLInput and tOracleInput in parallel -> tJoin to combine results on user_id. Use tFilterRow to filter transactions and then join the filtered result with tFileInputDelimited using tMap.
            C: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Use another tMap to join the result with tFileInputDelimited. Aggregate results using tAggregateRow based on user_name, and filter using tFilterRow.
            D: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Then, join the result with tFileInputDelimited on user_id. Apply filters in tMap to exclude rows where users neither made a transaction nor earned rewards.
            E: Use tMySQLInput -> tMap to lookup and join with tFileInputDelimited based on user_id. Then, join this result with tOracleInput using another tMap. Apply filters in the final tMap to only include the desired rows.

You're designing a Talend job to process e-commerce transactions. Each record has an "interactionType" field and a lastPurchase date field. For records with "SALE" as the interaction type, you want to calculate the number of days since the lastPurchase. However, the lastPurchase field can be null due to certain circumstances.
            
            Here's the Java code within the tJavaRow component:

Which of the following statements is TRUE regarding the code?

A: If the lastPurchase field is null, the code will throw a runtime exception.
            B: The daysSinceLastPurchase field is set to -1 solely in case of a date parsing error.
            C: All records with "SALE" as the interaction type will invariably have a non-negative daysSinceLastPurchase value.
            D: The code inherently assumes that every transaction of type "SALE" contains a valid lastPurchase date.