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Section 5 (Production Pipelines) 32. Processing CDC Feed with DLT
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Section 5 (Production Pipelines) 32. Processing CDC Feed with DLT

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@EnrapturedElf

Questions and Answers

The DLT view created in the DLT pipeline is a permanent view saved to the metastore.

False

For a table to be a streaming source in DLT, it must be an append-only table.

True

Views created in the DLT pipeline cannot be used to enforce data equality.

False

Code in any notebook can reference tables and views created in another notebook within the same DLT pipeline.

<p>True</p> Signup and view all the answers

A DLT pipeline can reference only one notebook at a time.

<p>False</p> Signup and view all the answers

To run the updated DLT pipeline successfully, one might need to do a full refresh to clear all data.

<p>True</p> Signup and view all the answers

The CDC data for books operations includes Insert, Update, and Delete statuses.

<p>True</p> Signup and view all the answers

The delete operations in the CDC feed contain null values for all fields except book_id.

<p>True</p> Signup and view all the answers

A DLT pipeline allows only one notebook to be integrated into its process.

<p>False</p> Signup and view all the answers

The Apply Changes Into command is used without declaring a target table.

<p>False</p> Signup and view all the answers

Auto loader is used to load JSON files incrementally into the bronze table.

<p>True</p> Signup and view all the answers

The main branch must be selected to pull the latest version of the course materials from GitHub.

<p>True</p> Signup and view all the answers

What defines a DLT view in contrast to a table within a DLT pipeline?

<p>It can be used for data enforcement and is temporary.</p> Signup and view all the answers

Which of the following is TRUE regarding the use of the LIVE keyword in a DLT pipeline?

<p>It allows referencing tables and views across notebooks within the same DLT pipeline.</p> Signup and view all the answers

What happens when a DLT pipeline is run with the new configurations after adding a notebook?

<p>It references and integrates both notebooks for processing.</p> Signup and view all the answers

In what situation is a streaming source considered invalid in the context of DLT?

<p>If it supports both updates and deletions of records.</p> Signup and view all the answers

What is the first step to integrate a new notebook into a DLT pipeline after creation?

<p>Access the Settings option and add the notebook.</p> Signup and view all the answers

Which statement accurately describes the operational column row_status in the CDC data?

<p>It contains entries indicating record status such as Insert, Update, or Delete.</p> Signup and view all the answers

What operation is performed if a book_id exists in the target table during an Apply Changes Into command?

<p>The existing record is updated.</p> Signup and view all the answers

When creating the silver table in the DLT pipeline, what is the first step that needs to be taken?

<p>Declare the target table before applying changes.</p> Signup and view all the answers

What happens to records in the target table where the row_status is marked as 'delete'?

<p>They are deleted from the target table.</p> Signup and view all the answers

What is the functionality of the auto loader in this context?

<p>It loads JSON files incrementally into the bronze table.</p> Signup and view all the answers

Why must the table book_silver be declared separately in the DLT pipeline?

<p>To comply with the requirements of the Apply Changes Into command.</p> Signup and view all the answers

What do the delete operations in the CDC feed contain?

<p>Null values for all fields except book_id.</p> Signup and view all the answers

Match the operational column in the CDC data with its description:

<p>row_status = Indicates whether the record was inserted, updated, or deleted row_time = Indicates when the change happened book_id = Unique identifier for each book record fields = Holds data about book attributes in the CDC data</p> Signup and view all the answers

Match the steps in processing the CDC data with their respective actions:

<p>Creating bronze table = Ingesting the book CDC feed Declaring target table = Facilitating Apply Changes Into command Applying changes = Updating or inserting records based on primary key Handling delete operations = Removing records where row_status is marked as 'delete'</p> Signup and view all the answers

Match the type of operation with its corresponding behavior in the CDC feed:

<p>Insert = New record is added to the target table Update = Existing record in the target table is modified Delete = Record is removed from the target table Null values = Present fields in delete operations except book_id</p> Signup and view all the answers

Match the table hierarchy in the DLT pipeline with their purpose:

<p>Bronze table = Initial storage for raw CDC feed data Silver table = Target storage for processed CDC data CDC feed = Data source that contains change operations Apply Changes Into command = Fundamental for data manipulation in the pipeline</p> Signup and view all the answers

Match the JSON file processing steps with their outcomes:

<p>Load new file = Increments the dataset with new information Check existing records = Determines insert or update action Delete marked records = Cleans up the target table as per row_status Accessing file content = Displays the structure of CDC data entries</p> Signup and view all the answers

Match the command in DLT with its corresponding requirement:

<p>Apply Changes Into = Requires target table declaration Auto loader = Facilitates incremental data loading CDC data = Requires valid JSON file format Row_time = Used as a sequence key for operations</p> Signup and view all the answers

Match the component of the DLT pipeline with its functionality:

<p>Notebook = Contains code for data processing Pipeline = Manages flow of data transformation Branch on GitHub = Specifies the source for course materials Repos tab = Interface for accessing version-controlled code</p> Signup and view all the answers

Match the types of records with their characteristics in the context of CDC data:

<p>Insert records = Contain new valid entries for all fields Update records = Modify existing data entries in the target table Delete records = Only book_id is retained, all other fields are null New JSON file = Loaded to reflect the latest CDC changes</p> Signup and view all the answers

Match the following terms related to DLT with their definitions:

<p>DLT view = Temporary views scoped to the DLT pipeline Streaming source = Must be an append-only table Target table = Destination for the applied changes from CDC Book_silver table = Source for creating a live table</p> Signup and view all the answers

Match the operations with their effects in DLT pipelines:

<p>Insert operation = Adds new records to the target table Update operation = Modifies existing records in the target table Delete operation = Removes records marked as 'delete' from the target table CDC data = Tracks changes in the source data</p> Signup and view all the answers

Match the actions to their descriptions in the context of a DLT pipeline:

<p>Adding a notebook = Integrates new code into the existing pipeline Running a full refresh = Clears and reloads all data from scratch Merging tables = Combining data from two or more sources Creating a live table = Defines an aggregate query from a source table</p> Signup and view all the answers

Match the components of the DLT pipeline with their respective characteristics:

<p>Views = Not persisted to the metastore Tables = Persistent structures for storing data Notebooks = Can reference tables and views across multiple libraries Metrics = Collected and reported similar to tables</p> Signup and view all the answers

Match the statements about DLT pipelines with their truth values:

<p>DLT pipelines can use multiple notebooks = True Views are permanent in DLT = False Streaming sources can include update operations = False Data must be appended only for valid streaming sources = True</p> Signup and view all the answers

Match the operations in CDC data with their specific field characteristics:

<p>Insert = Includes all fields with valid data Update = May include partial or all fields depending on the change Delete = Contains null values for all fields except book_id Row_status = Indicates the state of the record in the pipeline</p> Signup and view all the answers

Match the characteristics of a DLT pipeline with their roles:

<p>Live keyword = References schema at the Delta pipeline level Books Pipeline = Specific DLT project for managing book data Pipeline settings = Configures which notebooks are included CDC feeds = Provides the data operations for processing changes</p> Signup and view all the answers

Study Notes

Change Data Capture (CDC) Process with Delta Live Tables (DLT)

  • Utilizes Delta Live Tables (DLT) for processing CDC feeds sourced from JSON files.
  • Pull the latest course materials from GitHub and load new CDC files into the source directory.

CDC Data Structure

  • Each CDC data JSON file includes operational columns:
    • row_status: Indicates the operation type (Insert, Update, Delete).
    • row_time: Timestamp of the operation, used as a sequence key during processing.
  • Update and insert operations contain values for all fields; delete operations have null values except for book_id.

DLT Pipeline Overview

  • Consists of creating and managing tables for CDC data.
  • Bronze table: Ingests the CDC feed using auto loader for incremental loading.
  • Silver table: Target table where changes are applied.

Table Operations

  • Declare the target silver table before applying changes.
  • The Apply Changes Into command specifies:
    • Target: book_silver.
    • Source: books_bronze.
    • Primary key: book_id determines whether to update or insert records.
    • Delete records where row_status is "delete".
    • Use row_time for operation ordering.
    • Include all fields except operational columns (row_status, row_time).

Gold Layer and Views

  • The gold layer involves creating an aggregate query to form a non-streaming live table from book_silver.
  • DLT views can be defined by replacing TABLE with VIEW; scoped to the DLT pipeline, and not persisted to the metastore.
  • Views enable data equality enforcement, and metrics for views are collected similarly to tables.

Notebook Interaction

  • DLT allows referencing tables and views across multiple notebooks within a single pipeline.
  • Expandability of DLT pipelines by adding new notebooks to enhance functionality.

Updating the Pipeline

  • To add a new notebook to an existing pipeline:
    • Access pipeline settings and select the notebook to integrate.
  • Start the updated pipeline; refreshing may be required to clear and reload data successfully.

Final Observations

  • The updated pipeline includes both the newly referenced books tables and the view book_sales, which joins tables from different notebooks in the DLT context.

Change Data Capture (CDC) Process with Delta Live Tables (DLT)

  • Utilizes Delta Live Tables (DLT) for processing CDC feeds sourced from JSON files.
  • Pull the latest course materials from GitHub and load new CDC files into the source directory.

CDC Data Structure

  • Each CDC data JSON file includes operational columns:
    • row_status: Indicates the operation type (Insert, Update, Delete).
    • row_time: Timestamp of the operation, used as a sequence key during processing.
  • Update and insert operations contain values for all fields; delete operations have null values except for book_id.

DLT Pipeline Overview

  • Consists of creating and managing tables for CDC data.
  • Bronze table: Ingests the CDC feed using auto loader for incremental loading.
  • Silver table: Target table where changes are applied.

Table Operations

  • Declare the target silver table before applying changes.
  • The Apply Changes Into command specifies:
    • Target: book_silver.
    • Source: books_bronze.
    • Primary key: book_id determines whether to update or insert records.
    • Delete records where row_status is "delete".
    • Use row_time for operation ordering.
    • Include all fields except operational columns (row_status, row_time).

Gold Layer and Views

  • The gold layer involves creating an aggregate query to form a non-streaming live table from book_silver.
  • DLT views can be defined by replacing TABLE with VIEW; scoped to the DLT pipeline, and not persisted to the metastore.
  • Views enable data equality enforcement, and metrics for views are collected similarly to tables.

Notebook Interaction

  • DLT allows referencing tables and views across multiple notebooks within a single pipeline.
  • Expandability of DLT pipelines by adding new notebooks to enhance functionality.

Updating the Pipeline

  • To add a new notebook to an existing pipeline:
    • Access pipeline settings and select the notebook to integrate.
  • Start the updated pipeline; refreshing may be required to clear and reload data successfully.

Final Observations

  • The updated pipeline includes both the newly referenced books tables and the view book_sales, which joins tables from different notebooks in the DLT context.

Change Data Capture (CDC) Process with Delta Live Tables (DLT)

  • Utilizes Delta Live Tables (DLT) for processing CDC feeds sourced from JSON files.
  • Pull the latest course materials from GitHub and load new CDC files into the source directory.

CDC Data Structure

  • Each CDC data JSON file includes operational columns:
    • row_status: Indicates the operation type (Insert, Update, Delete).
    • row_time: Timestamp of the operation, used as a sequence key during processing.
  • Update and insert operations contain values for all fields; delete operations have null values except for book_id.

DLT Pipeline Overview

  • Consists of creating and managing tables for CDC data.
  • Bronze table: Ingests the CDC feed using auto loader for incremental loading.
  • Silver table: Target table where changes are applied.

Table Operations

  • Declare the target silver table before applying changes.
  • The Apply Changes Into command specifies:
    • Target: book_silver.
    • Source: books_bronze.
    • Primary key: book_id determines whether to update or insert records.
    • Delete records where row_status is "delete".
    • Use row_time for operation ordering.
    • Include all fields except operational columns (row_status, row_time).

Gold Layer and Views

  • The gold layer involves creating an aggregate query to form a non-streaming live table from book_silver.
  • DLT views can be defined by replacing TABLE with VIEW; scoped to the DLT pipeline, and not persisted to the metastore.
  • Views enable data equality enforcement, and metrics for views are collected similarly to tables.

Notebook Interaction

  • DLT allows referencing tables and views across multiple notebooks within a single pipeline.
  • Expandability of DLT pipelines by adding new notebooks to enhance functionality.

Updating the Pipeline

  • To add a new notebook to an existing pipeline:
    • Access pipeline settings and select the notebook to integrate.
  • Start the updated pipeline; refreshing may be required to clear and reload data successfully.

Final Observations

  • The updated pipeline includes both the newly referenced books tables and the view book_sales, which joins tables from different notebooks in the DLT context.

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Description

In this quiz, we will explore the process of change data capture (CDC) with Delta Live Tables. Learn how to pull course materials and work with JSON files effectively as we set up a pipeline for real-time data processing. This hands-on demo will guide you through essential steps and functions needed for a successful data operation.

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