Enable and Detail Data Ingestion Patterns, Including Batch, Streaming, and Incremental Loading, and Import Data from Sources Such as Local Files, Lakeflow Connect Standard Connectors, and Lakeflow Connect Managed Connectors. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   A data engineer wants to upload a local file to DBFS as part of an automated script. Which Databricks tool is most appropriate for this task?

   • AThe Databricks CLI
   • BThe Databricks notebook editor
   • CThe Databricks UI's data import feature
   • DThe Databricks SQL warehouse
   Reveal Solution Discussion Select an answer first
2. 7application · medium

   A logistics company maintains a large Parcels table that is updated throughout the day. Each night, a batch job must load only the parcels whose status changed since the previous run. The source system provides a last_updated timestamp for each record. Which strategy should the team use to implement this requirement?

   • AUse a streaming ingestion pipeline to continuously read changes from the source database.
   • BUse the last_updated timestamp as a watermark to filter records where last_updated > last_run_time.
   • CPerform a full load of the entire Parcels table every night and overwrite the Databricks table.
   • DLoad all records and use a Delta table merge to update existing rows and insert new ones.
   Reveal Solution Discussion Select an answer first
4. 8application · easy

   A social media analytics company needs to track user interactions (likes, shares, comments) in real time to provide immediate insights to their clients. The data is generated as a continuous stream of events. Which ingestion pattern is most appropriate?

   • AIncremental loading using a watermark to load new events every hour.
   • BBatch ingestion with a scheduled job every 15 minutes.
   • CManual file uploads of event logs at the end of each day.
   • DStreaming ingestion that processes events as they arrive and writes to a Delta table.
   Reveal Solution Discussion Select an answer first
5. 9expert · hard

   A company uses a Lakeflow Connect standard connector to ingest data from a SaaS application into Databricks on a daily schedule. The source system does not provide a last_modified timestamp for all records, but it does provide a full export of all records each day. The team wants to avoid loading duplicate data into the target Delta table. Which strategy should they use?

   • ALoad the full export into a staging table and use a MERGE operation to upsert records into the final table.
   • BUse a watermark column on the target table to filter out records that have not changed.
   • CAppend the full export directly to the final table each day.
   • DUse a Lakeflow Connect managed connector to enable incremental loading from the source.
   Reveal Solution Discussion Select an answer first
6. 10application · easy

   A data analyst has a CSV file on their local machine and needs to import it into a Databricks table for a one-time analysis. They do not have access to the Databricks CLI or API. Which method should they use?

   • AUse the Databricks REST API to upload the file directly to a Delta table.
   • BUse the Databricks CLI to run a 'dbfs cp' command to copy the file to DBFS.
   • CAsk a colleague to mount the local file as a data source using a Lakeflow Connect standard connector.
   • DUse the Databricks UI to upload the file to DBFS, then create a table from the uploaded file.
   Reveal Solution Discussion Select an answer first