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| Section | Objectives |
|---|---|
| Topic 1: Data Governance and Quality | - Unity Catalog basics - Data quality concepts and management - Data access control and governance |
| Topic 2: Data Ingestion and ELT Development | - Handling structured and semi-structured data - Data ingestion using Spark SQL and PySpark - ETL patterns and transformations |
| Topic 3: Data Processing and Transformations | - Delta Lake fundamentals (tables, transactions, optimization) - Apache Spark SQL operations (joins, aggregations, filtering) - PySpark DataFrame transformations - User-defined functions (UDFs) |
| Topic 4: Productionizing Data Pipelines | - Scheduling and monitoring jobs - Databricks Workflows / Jobs orchestration - Pipeline deployment and operationalization |
| Topic 5: Databricks Lakehouse Platform Fundamentals | - Workspace, architecture, and core platform concepts - Clusters, notebooks, and basic Databricks environment usage |
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NEW QUESTION # 201
What is the structure of an Asset Bundle?
Answer: A
Explanation:
An Asset Bundle in Databricks is structured as a YAML configuration file that defines the project's artifacts, resources, and configurations. This format allows reproducibility, automation, and portability of projects across workspaces, making it the standard approach for production pipelines.
NEW QUESTION # 202
A data engineer investigates a slow stage in the Databricks Spark UI. The engineer scrolls down to the Summary Metrics section for task durations, and they observe for that stage:
25th percentile duration: 40 seconds
Median duration: 45 seconds
75th percentile duration: 50 seconds
Max duration: 80 seconds
What is the interpretation of these metrics?
Answer: A
Explanation:
The maximum task duration is 60% higher than the 75th percentile (80s versus 50s). Databricks identifies this pattern as a likely indication that a small number of tasks process disproportionately large partitions-data skew.
NEW QUESTION # 203
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?
Answer: D
Explanation:
https://www.databricks.com/blog/2021/10/20/introducing-sql-user-defined-functions.html
NEW QUESTION # 204
A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to a data analytics dashboard for a retail use case. The job has a Databricks SQL query that returns the number of store-level records where sales is equal to zero. The data engineer wants their entire team to be notified via a messaging webhook whenever this value is greater than 0.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of stores with $0 in sales is greater than zero?
Answer: A
Explanation:
A webhook alert destination is a notification destination that allows Databricks to send HTTP POST requests to a third-party endpoint when an alert is triggered. This enables the data engineer to integrate Databricks alerts with their preferred messaging or collaboration platform, such as Slack, Microsoft Teams, or PagerDuty.
To set up a webhook alert destination, the data engineer needs to create and configure a webhook connector in their messaging platform, and then add the webhook URL to the Databricks notification destination. After that, the data engineer can create an alert for their Databricks SQL query, and select the webhook alert destination as the notification destination. The alert can be configured with a custom condition, such as when the number of stores with $0 in sales is greater than zero, and a custom message template, such as "Alert:
{number_of_stores} stores have $0 in sales". The alert can also be configured with a recurrence interval, such as every hour, to check the query result periodically. When the alert condition is met, the data engineer and their team will receive a notification via the messaging webhook, with the custom message and a link to the Databricks SQL query. The other options are either not suitable for sending notifications via a messaging webhook (A, B, E), or not suitable for sending recurring notifications . References: Databricks Documentation -Manage notification destinations, Databricks Documentation - Create alerts for Databricks SQL queries, Databricks Documentation - Configure alert conditions and messages.
NEW QUESTION # 205
A data engineer needs to ingest streaming data from Kafka into a Delta Lake table using Databricks. The pipeline must guarantee exactly-once processing semantics and maintain checkpoint information to recover from failures. Which Spark Structured Streaming feature ensures reliable processing and fault tolerance?
Answer: C
NEW QUESTION # 206
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