최신 Databricks-Certified-Data-Engineer-Associate 무료덤프 - Databricks Certified Data Engineer Associate

문제1

A data engineer has developed a data pipeline to ingest data from a JSON source using Auto Loader, but the engineer has not provided any type inference or schema hints in their pipeline. Upon reviewing the data, the data engineer has noticed that all of the columns in the target table are of the string type despite some of the fields only including float or boolean values.
Which of the following describes why Auto Loader inferred all of the columns to be of the string type?

A. JSON data is a text-based format

B. All of the fields had at least one null value

C. Auto Loader only works with string data

D. Auto Loader cannot infer the schema of ingested data

E. There was a type mismatch between the specific schema and the inferred schema

정답: A

설명: (DumpTOP 회원만 볼 수 있음)

문제2

Which tool is used by Auto Loader to process data incrementally?

A. Spark Structured Streaming

B. Databricks SQL

C. Checkpointing

D. Unity Catalog

정답: A

설명: (DumpTOP 회원만 볼 수 있음)

문제3

A data analyst has developed a query that runs against Delta table. They want help from the data engineering team to implement a series of tests to ensure the data returned by the query is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following operations could the data engineering team use to run the query and operate with the results in PySpark?

A. There is no way to share data between PySpark and SQL.

B. spark.delta.table

C. spark.table

D. spark.sql

E. SELECT * FROM sales

정답: D

설명: (DumpTOP 회원만 볼 수 있음)

문제4

A data engineer is attempting to drop a Spark SQL table my_table and runs the following command:
DROP TABLE IF EXISTS my_table;
After running this command, the engineer notices that the data files and metadata files have been deleted from the file system.
Which of the following describes why all of these files were deleted?

A. The table was external

B. The table was managed

C. The table's data was smaller than 10 GB

D. The table's data was larger than 10 GB

E. The table did not have a location

정답: B

설명: (DumpTOP 회원만 볼 수 있음)

문제5

A data engineer has been given a new record of data:
id STRING = 'a1'
rank INTEGER = 6
rating FLOAT = 9.4
Which of the following SQL commands can be used to append the new record to an existing Delta table my_table?

A. UPDATE VALUES ('a1', 6, 9.4) my_table

B. INSERT VALUES ( 'a1' , 6, 9.4) INTO my_table

C. INSERT INTO my_table VALUES ('a1', 6, 9.4)

D. UPDATE my_table VALUES ('a1', 6, 9.4)

E. my_table UNION VALUES ('a1', 6, 9.4)

정답: C

설명: (DumpTOP 회원만 볼 수 있음)

문제6

In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?

A. Write-ahead Logs and Idempotent Sinks

B. Replayable Sources and Idempotent Sinks

C. Structured Streaming cannot record the offset range of the data being processed in each trigger.

D. Checkpointing and Idempotent Sinks

E. Checkpointing and Write-ahead Logs

정답: E

설명: (DumpTOP 회원만 볼 수 있음)

문제7

A data engineer and data analyst are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables.
Which change will need to be made to the pipeline when migrating to Delta Live Tables?

A. The pipeline will need to be written entirely in Python.

B. The pipeline can have different notebook sources in SQL & Python.

C. The pipeline will need to use a batch source in place of a streaming source.

D. The pipeline will need to be written entirely in SQL.

정답: B

설명: (DumpTOP 회원만 볼 수 있음)

문제8

A dataset has been defined using Delta Live Tables and includes an expectations clause:
CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01') ON VIOLATION FAIL UPDATE What is the expected behavior when a batch of data containing data that violates these constraints is processed?

A. Records that violate the expectation are added to the target dataset and recorded as invalid in the event log.

B. Records that violate the expectation cause the job to fail.

C. Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log.

D. Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.

E. Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.

정답: B

설명: (DumpTOP 회원만 볼 수 있음)

문제9

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 names of the files to be copied were not included with the FILES keyword.

B. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.

C. The previous day's file has already been copied into the table.

D. The PARQUET file format does not support COPY INTO.

E. The COPY INTO statement requires the table to be refreshed to view the copied rows.

정답: C

설명: (DumpTOP 회원만 볼 수 있음)

문제10

A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?

A. spark.delta.table("sales")

B. There is no way to share data between PySpark and SQL.

C. spark.sql("sales")

D. SELECT * FROM sales

E. spark.table("sales")

정답: E

설명: (DumpTOP 회원만 볼 수 있음)

최신 Databricks-Certified-Data-Engineer-Associate 무료덤프 - Databricks Certified Data Engineer Associate

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