最も有効な Databricks-Certified-Professional-Data-Engineer 試験参考書

A data engineer is designing an append-only pipeline that needs to handle both batch and streaming data in Delta Lake. The team wants to ensure that the streaming component can efficiently track which data has already been processed.
Which configuration should be set to enable this?

• A. partitionBy
• B. mergeSchema
• C. checkpointLocation
• D. overwriteSchema

The business intelligence team has a dashboard configured to track various summary metrics for retail stories.
This includes total sales for the previous day alongside totals and averages for a variety of time periods. The fields required to populate this dashboard have the following schema:

For Demand forecasting, the Lakehouse contains a validated table of all itemized sales updated incrementally in near real-time. This table named products_per_order, includes the following fields:

Because reporting on long-term sales trends is less volatile, analysts using the new dashboard only require data to be refreshed once daily. Because the dashboard will be queried interactively by many users throughout a normal business day, it should return results quickly and reduce total compute associated with each materialization.
Which solution meets the expectations of the end users while controlling and limiting possible costs?

• A. Define a view against the products_per_order table and define the dashboard against this view.
• B. Use Structure Streaming to configure a live dashboard against the products_per_order table within a Databricks notebook.
• C. Populate the dashboard by configuring a nightly batch job to save the required to quickly update the dashboard with each query.
• D. Use the Delta Cache to persists the products_per_order table in memory to quickly the dashboard with each query.

A data engineering team uses Databricks Lakehouse Monitoring to track the percent_null metric for a critical column in their Delta table.
The profile metrics table (prod_catalog.prod_schema.customer_data_profile_metrics) stores hourly percent_null values.
The team wants to:
* Trigger an alert when the daily average of percent_null exceeds 5% for three consecutive days .
* Ensure that notifications are not spammed during sustained issues.
Options:

• A. SELECT percent_null
  FROM prod_catalog.prod_schema.customer_data_profile_metrics
  WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 1 ' DAY
  Alert Condition: percent_null > 5
  Notification Frequency: At most every 24 hours
• B. SELECT SUM(CASE WHEN percent_null > 5 THEN 1 ELSE 0 END) AS violation_days FROM prod_catalog.prod_schema.customer_data_profile_metrics WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 3 ' DAY Alert Condition: violation_days > = 3 Notification Frequency: Just once
• C. SELECT AVG(percent_null) AS daily_avg
  FROM prod_catalog.prod_schema.customer_data_profile_metrics
  WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 3 ' DAY
  Alert Condition: daily_avg > 5
  Notification Frequency: Each time alert is evaluated
• D. WITH daily_avg AS (
  SELECT DATE_TRUNC( ' DAY ' , window.end) AS day,
  AVG(percent_null) AS avg_null
  FROM prod_catalog.prod_schema.customer_data_profile_metrics
  GROUP BY DATE_TRUNC( ' DAY ' , window.end)
  )
  SELECT day, avg_null
  FROM daily_avg
  ORDER BY day DESC
  LIMIT 3
  Alert Condition: ALL avg_null > 5 for the latest 3 rows
  Notification Frequency: Just once

The Databricks workspace administrator has configured interactive clusters for each of the data engineering groups. To control costs, clusters are set to terminate after 30 minutes of inactivity. Each user should be able to execute workloads against their assigned clusters at any time of the day.
Assuming users have been added to a workspace but not granted any permissions, which of the following describes the minimal permissions a user would need to start and attach to an already configured cluster.

• A. " Can Manage " privileges on the required cluster
• B. Cluster creation allowed. " Can Attach To " privileges on the required cluster
• C. " Can Restart " privileges on the required cluster
• D. Cluster creation allowed. " Can Restart " privileges on the required cluster
• E. Workspace Admin privileges, cluster creation allowed. " Can Attach To " privileges on the required cluster

A table is registered with the following code:

Both users and orders are Delta Lake tables. Which statement describes the results of querying recent_orders ?

• A. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
• B. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
• C. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
• D. All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
• E. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.