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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
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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.