(Delta) Ch 8 Operations on Streaming Data (Multple Choice)

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Questions and Answers

What does a 'readstream' do differently than a standard 'read'?

ignores deleted data

Reads data from a single file

Allows for real-time data processing (correct)

Streams data from multiple tables

What type of DataFrame is returned by the 'readstream' function?

Standard DataFrame

Streaming DataFrame (correct)

Real-Time DataFrame

Delta DataFrame

What is the purpose of the 'load' function?

To save data to a file

To load data from a file (correct)

To read data from a source

To stream data from a table

What is similar between a Streaming DataFrame and a standard DataFrame?

They can both be used with the Spark API Signup and view all the answers

What is unique about the 'readstream' function compared to a standard 'read' function?

It streams data from a table Signup and view all the answers

What is the purpose of the 'DESCRIBE HISTORY' query?

To view the version history of the table Signup and view all the answers

What is the type of source in the 'sources' section?

DeltaSource Signup and view all the answers

What type of sequence of data is a streaming DataFrame?

Unbounded Signup and view all the answers

Why can't we perform a count() operation on a streaming DataFrame?

Because it's unbounded Signup and view all the answers

What is the purpose of adding a 'RecordStreamTime' column to the streaming DataFrame?

To know when we read each record from the source table Signup and view all the answers

What is the purpose of selecting columns in the streaming DataFrame?

To exclude unnecessary columns in the source DataFrame Signup and view all the answers

Why can't we perform a sort() operation on a streaming DataFrame?

Because it's an unbounded sequence of data Signup and view all the answers

What is the purpose of the target location in writing the stream to an output table?

To define the output location Signup and view all the answers

What is the purpose of the checkpoint location in writing the stream to an output table?

To maintain the state in the checkpoint location Signup and view all the answers

What happens when we write the stream to an output table?

The stream is written to the output table Signup and view all the answers

What is the default value for maxBytesPerTrigger?

1,000 Signup and view all the answers

What happens when you use Trigger.Once?

maxBytesPerTrigger is ignored Signup and view all the answers

What is the purpose of the rate limit options?

To avoid overloading processing resources Signup and view all the answers

What does the ignoreDeletes option do?

Ignores transactions that delete data at partition boundaries Signup and view all the answers

What is the effect of the ignoreChanges option?

It ignores updates to files and deleted data Signup and view all the answers

What is the purpose of controlling micro-batch size?

To achieve a more balanced processing experience Signup and view all the answers

How can you control rate limits in a streaming query?

By specifying the maxBytesPerTrigger option Signup and view all the answers

What is the effect of the readChangeFeed option?

It reads the CDF stream Signup and view all the answers

What is the purpose of the checkpoint file in a streaming query?

To maintain metadata and state of the streaming query Signup and view all the answers

What happens if a trigger is not specified in a streaming query?

The query will run indefinitely Signup and view all the answers

What information does the checkpoint file maintain about the transaction log entries?

Which transaction log entries were already processed Signup and view all the answers

What is displayed in the streaming dashboard?

Various metrics, statistics, and insights about the stream applications performance, throughput, and latency Signup and view all the answers

What is the purpose of the query progress log (QPL)?

To provide execution details on the micro-batch Signup and view all the answers

How many tabs are displayed in the streaming dashboard?

Two Signup and view all the answers

Study Notes

Streaming Queries

A streaming query is created by reading a stream from a source table using readstream instead of read
The readstream function is similar to a standard Delta table read, but returns a streaming DataFrame
A streaming DataFrame is similar to a standard Spark DataFrame, but is unbounded and cannot be used with certain operations like count() or sort()

Adding a Timestamp Column

A RecordStreamTime column can be added to the streaming DataFrame using withColumn and current_timestamp()
This column captures the timestamp when each record is read from the source table

Selecting Columns

The select function is used to select specific columns from the streaming DataFrame
The select_columns list specifies the columns to be selected

Writing to an Output Table

The streaming DataFrame is written to an output table using writeStream
A target location and checkpoint location are specified
The checkpoint file maintains metadata and state of the streaming query, ensuring fault tolerance and enabling query recovery in case of failure

Query Progress Log

When the streaming query is started, a query progress log (QPL) is displayed
The QPL provides execution details on each micro-batch and is used to display a streaming dashboard in the notebook cell
The dashboard provides metrics, statistics, and insights about the stream application's performance, throughput, and latency

Trigger Options

Trigger options can be used to control the rate at which data is processed in each micro-batch
Options include maxBytesPerTrigger, ignoreDeletes, and ignoreChanges
These options can be used to control rate limits and avoid overloading processing resources

Reading a CDF Stream

A CDF (Change Data Feed) stream can be read using readstream with readChangeFeed option
This allows for capturing changes made to the source table, such as inserts, updates, and deletes
Rate limit options and ignore deletes can be specified to control the processing of the stream

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