Exam Newest 2026-2027 Microsoft Fabric Analytics

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Microsoft Fabric Analytics Engineer Associate Actual Exam Newest 2026-2027 / Microsoft Fabric Analytics Engineer Associate Practice Exam /Microsoft Fabric Analytics Engineer Associate Preparation With 250 Questions And Correct Answers | Already Graded A+

What is time travel in the context of delta tables? - ANSWER-The ability to retrieve older versions of the data and view the history of changes made to the table.

Which SQL command is used to see the history of a delta table? - ANSWER-DESCRIBE HISTORY products

What information does the DESCRIBE HISTORY command provide? - ANSWER-It shows the transactions that have been applied to the table, including version, timestamp, and operation.

How can you retrieve data from a specific version of a delta table? -

ANSWER-By using: df =

spark.read.format("delta").option("versionAsOf", 0).load(delta_path)

What option can you use to specify a timestamp when retrieving data from a delta table? - ANSWER-timestampAsOf option 1 / 4

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How do you specify a timestamp to retrieve data in Python? -

ANSWER-Using: df =

spark.read.format("delta").option("timestampAsOf", '2022-01- 01').load(delta_path)

What is the purpose of the transaction log in delta tables? - ANSWER- To log modifications made to the delta tables, allowing for time travel and history tracking.

What is the typical format for writing SQL commands in a notebook? - ANSWER-Using the %%sql magic command.

What does the Delta Lake API simplify when working with delta files? - ANSWER-It simplifies the process of modifying data in delta format files.

What type of data does Spark Structured Streaming process? - ANSWER-Streaming data in near real-time.

What is a typical stream processing solution's workflow? - ANSWER- Constantly reading data from a source, processing it, and writing results to a sink.

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What API does Spark Structured Streaming use? - ANSWER-An API based on a boundless dataframe.

What are some sources from which Spark Structured Streaming can read data? - ANSWER-Network ports, real-time message brokering services (like Azure Event Hubs or Kafka), and file system locations.

How can Delta tables be used in Spark Structured Streaming? - ANSWER-As a source or a sink for streaming data.

What SQL command is used to create a Delta table for storing internet sales orders? - ANSWER-CREATE TABLE orders_in (...) USING

DELTA;

What happens when a data stream of internet orders is inserted into the orders_in table? - ANSWER-It captures real-time data for processing.

How can you verify data from the input Delta table? - ANSWER-By reading and displaying the data using spark.read.format('delta').

What is the purpose of the ignoreChanges option when loading a streaming DataFrame from a Delta table? - ANSWER-It allows only append operations in the stream to avoid errors.

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How can you check if a DataFrame is streaming? - ANSWER-By using the isStreaming property, which should return True.

What transformation can be applied to filter out rows with NULL in the Price column? - ANSWER-Using the filter method with col('Price').isNotNull().

What new columns can be added during the transformation of a streaming DataFrame? - ANSWER-IsBike and Total.

What is the purpose of the checkpointLocation option in streaming writes? - ANSWER-To track the state of the stream processing and enable recovery from failures.

What SQL command can be used to query the output Delta table after streaming? - ANSWER-SELECT * FROM orders_processed ORDER BY OrderID;

What happens to order 3005 in the output query results? - ANSWER-It is excluded because it had NULL in the Price column.

How can you stop the streaming data process? - ANSWER-By using the stop method on the streaming DataFrame.

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