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  1. Home
  2. GAQM Certification
  3. Databricks-Certified-Data-Engineer-Associate Exam
  4. GAQM.Databricks-Certified-Data-Engineer-Associate.v2024-04-02.q80 Dumps
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Question 46

Which of the following tools is used by Auto Loader process data incrementally?

Correct Answer: B
Explanation
The Auto Loader process in Databricks is typically used in conjunction with Spark Structured Streaming to process data incrementally. Spark Structured Streaming is a real-time data processing framework that allows you to process data streams incrementally as new data arrives. The Auto Loader is a feature in Databricks that works with Structured Streaming to automatically detect and process new data files as they are added to a specified data source location. It allows for incremental data processing without the need for manual intervention.
How does Auto Loader track ingestion progress? As files are discovered, their metadata is persisted in a scalable key-value store (RocksDB) in the checkpoint location of your Auto Loader pipeline. This key-value store ensures that data is processed exactly once. In case of failures, Auto Loader can resume from where it left off by information stored in the checkpoint location and continue to provide exactly-once guarantees when writing data into Delta Lake. You don't need to maintain or manage any state yourself to achieve fault tolerance or exactly-once semantics.https://docs.databricks.com/ingestion/auto-loader/index.html
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Question 47

Which of the following commands will return the number of null values in the member_id column?

Correct Answer: C
To return the number of null values in the member_id column, the best option is to use the count_if function, which counts the number of rows that satisfy a given condition. In this case, the condition is that the member_id column is null. The other options are either incorrect or not supported by Spark SQL. Option A will return the number of non-null values in the member_id column. Option B will not work because there is no count_null function in Spark SQL. Option D will not work because there is no null function in Spark SQL.
Option E will not work because there is no count_null function in Spark SQL. References:
* Built-in Functions - Spark SQL, Built-in Functions
* count_if - Spark SQL, Built-in Functions
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Question 48

A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for help. The data engineering team notices that each of the team's queries uses the same SQL endpoint.
Which of the following approaches can the data engineering team use to improve the latency of the team's queries?

Correct Answer: B
https://community.databricks.com/t5/data-engineering/sequential-vs-concurrency-optimization-questions-from-q
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Question 49

A data engineer is running code in a Databricks Repo that is cloned from a central Git repository. A colleague of the data engineer informs them that changes have been made and synced to the central Git repository. The data engineer now needs to sync their Databricks Repo to get the changes from the central Git repository.
Which of the following Git operations does the data engineer need to run to accomplish this task?

Correct Answer: C
To sync a Databricks Repo with the changes from a central Git repository, the data engineer needs to run the Git pull operation. This operation fetches the latest updates from the remote repository and merges them with the local repository. The data engineer can use the Pull button in the Databricks Repos UI, or use the git pull command in a terminal session. The other options are not relevant for this task, as they either push changes to the remote repository (Push), combine two branches (Merge), save changes to the local repository (Commit), or create a new local repository from a remote one (Clone). References:
* Run Git operations on Databricks Repos
* Git pull
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Question 50

A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to an ELT job. The ELT job has its Databricks SQL query that returns the number of input records containing unexpected NULL values. The data engineer wants their entire team to be notified via a messaging webhook whenever this value reaches 100.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of NULL values reaches 100?

Correct Answer: D
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