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Databricks-Certified-Data-Engineer-Associate Free Vce Dumps: Databricks Certified Data Engineer Associate Exam - The Best Databricks Standard Databricks-Certified-Data-Engineer-Associate Answers
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Databricks Certified Data Engineer Associate certification is an essential certification for individuals who want to pursue a career in data engineering. Databricks Certified Data Engineer Associate Exam certification exam covers a range of topics and is designed to ensure that candidates have the necessary skills and knowledge to build and maintain large-scale data pipelines. By earning this certification, candidates can demonstrate their expertise in data engineering and increase their chances of getting hired by top companies in the data and AI industry.
Databricks Certified Data Engineer Associate Exam Sample Questions (Q44-Q49):
NEW QUESTION # 44
In which of the following scenarios should a data engineer select a Task in the Depends On field of a new Databricks Job Task?
- A. When another task needs to use as little compute resources as possible
- B. When another task needs to be replaced by the new task
- C. When another task needs to successfully complete before the new task begins
- D. When another task needs to fail before the new task begins
- E. When another task has the same dependency libraries as the new task
Answer: C
NEW QUESTION # 45
A data engineer is using the following code block as part of a batch ingestion pipeline to read from a composable table:
Which of the following changes needs to be made so this code block will work when the transactions table is a stream source?
- A. Replace predict with a stream-friendly prediction function
- B. Replace "transactions" with the path to the location of the Delta table
- C. Replace format("delta") with format("stream")
- D. Replace spark.read with spark.readStream
- E. Replace schema(schema) with option ("maxFilesPerTrigger", 1)
Answer: D
Explanation:
To read from a stream source, the data engineer needs to use the spark.readStream method instead of the spark.read method. The spark.readStream method returns a DataStreamReader object that can be used to specify the details of the input source, such as the format, the schema, the path, and the options. The spark.read method is only suitable for batch processing, not streaming processing. The other changes are not necessary or correct for reading from a stream source. Reference: Structured Streaming Programming Guide, Read a stream, Databricks Data Sources
NEW QUESTION # 46
A data engineer is designing a data pipeline. The source system generates files in a shared directory that is also used by other processes. As a result, the files should be kept as is and will accumulate in the directory. The data engineer needs to identify which files are new since the previous run in the pipeline, and set up the pipeline to only ingest those new files with each run.
Which of the following tools can the data engineer use to solve this problem?
- A. Data Explorer
- B. Databricks SQL
- C. Unity Catalog
- D. Delta Lake
- E. Auto Loader
Answer: E
Explanation:
Explanation
Auto Loader incrementally and efficiently processes new data files as they arrive in cloud storage without any additional setup.https://docs.databricks.com/en/ingestion/auto-loader/index.html
NEW QUESTION # 47
A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:
After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?
- A. The COPY INTO statement requires the table to be refreshed to view the copied rows.
- B. The previous day's file has already been copied into the table.
- C. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
- D. The PARQUET file format does not support COPY INTO.
- E. The names of the files to be copied were not included with the FILES keyword.
Answer: B
Explanation:
The COPY INTO statement is an idempotent operation, which means that it will skip any files that have already been loaded into the target table1. This ensures that the data is not duplicated or corrupted by multiple attempts to load the same file. Therefore, if the data engineer runs the same command every day without specifying the names of the files to be copied with the FILES keyword or a glob pattern with the PATTERN keyword, the statement will only copy the first file that matches the source location and ignore the rest. To avoid this problem, the data engineer should either use the FILES or PATTERN keywords to filter the files to be copied based on the date or some other criteria, or delete the files from the source location after they are copied into the table2. Reference: 1: COPY INTO | Databricks on AWS 2: Get started using COPY INTO to load data | Databricks on AWS
NEW QUESTION # 48
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:
Which of the following lines of code fills in the above blank to successfully complete the task?
- A. DELTA
- B. sqlite
- C. autoloader
- D. org.apache.spark.sql.sqlite
- E. org.apache.spark.sql.jdbc
Answer: E
Explanation:
CREATE TABLE new_employees_table
USING JDBC
OPTIONS (
url "<jdbc_url>",
dbtable "<table_name>",
user '<username>',
password '<password>'
) AS
SELECT * FROM employees_table_vw
https://docs.databricks.com/external-data/jdbc.html#language-sql
NEW QUESTION # 49
......
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