Pipelines with Databrick Delta Live Tables Part 2/2

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Questions and Answers

What is the primary purpose of the APPLY CHANGES INTO statement?

To create new tables automatically

To summarize data from multiple tables

To perform incremental ingestion of CDC data (correct)

To delete records from a table

Which keyword is used to specify which columns should be ignored during the APPLY CHANGES INTO operation?

EXCLUDE

EXCEPT (correct)

IGNORE

IGNORE_COLUMNS

What are the default assumptions regarding rows during the APPLY CHANGES INTO operation?

Only updated rows will be processed

Rows will contain only deletes

All rows must be manually specified

Rows will contain inserts and updates (correct)

What is indicated by the sequence part in the APPLY CHANGES INTO statement?

The order in which changes will be applied Signup and view all the answers

What is a key feature of SQL that differs from Python in terms of error handling?

SQL allows for syntax checks while Python does not. Signup and view all the answers

Which of the following is NOT a guarantee of the APPLY CHANGES INTO statement?

Can only apply inserts Signup and view all the answers

How does data transformation differ between Python and SQL?

In Python, multiple transformations can be applied in sequence directly, whereas SQL requires saving intermediate results. Signup and view all the answers

What data management feature does Delta Live Tables (DLT) provide?

Automated optimization for performance and ease of use Signup and view all the answers

Which property is not automatically encoded by DLT when creating a DLT setting?

optimizePerformance Signup and view all the answers

Which of the following streaming platforms can be used to provide a streaming change feed?

Kafka Signup and view all the answers

What must be done in Python to use the DLT module?

Import the dlt module explicitly. Signup and view all the answers

What does DLT automatically manage to minimize cost and optimize performance?

Vacuum and optimize processes Signup and view all the answers

In the SQL code provided, which field is specified as the primary key for the target table?

customer_id Signup and view all the answers

What is the primary purpose of the SELECT statement in SQL?

To define transformations and logic of queries. Signup and view all the answers

What happens to records with the operation field set to 'DELETE' in the provided SQL code?

They are applied as deletes Signup and view all the answers

What is an incorrect statement regarding Python and SQL comments?

SQL comments are added with TBLPROPERTIES. Signup and view all the answers

Which feature allows schema evolution by modifying a live table transformation?

Both addition and removal Signup and view all the answers

Which aspect does NOT relate to late-arriving records in the APPLY CHANGES INTO functionality?

They are ignored if out of sequence Signup and view all the answers

What is required for proper execution of DLT syntax in a notebook?

Scheduling as part of a pipeline Signup and view all the answers

Which statement correctly describes the handling of notebook cells in Python and SQL?

Neither Python nor SQL allows running cells independently in DLT pipelines. Signup and view all the answers

When modifying a column in a streaming live table, what happens to old values?

Old values are preserved Signup and view all the answers

Which of the following is true regarding the use of APIs in Python and SQL?

Python employs a proprietary API while SQL has a standard SQL API. Signup and view all the answers

In terms of documentation, how do Python and SQL differ?

Python uses comments in a different format than SQL. Signup and view all the answers

What SQL command creates a new orders_silver table from an orders_bronze table?

CREATE OR REFRESH STREAMING LIVE TABLE orders_silver Signup and view all the answers

In the example provided, what happens if the order_timestamp condition is violated?

The update fails without any action Signup and view all the answers

How do transformations get specified in Python versus SQL?

Transformations in SQL are handled within the SELECT statement while Python uses @dlt.table(). Signup and view all the answers

What is the purpose of the SQL `EXCEPT` clause used in the creation of orders_silver?

To filter out specific columns from the selection Signup and view all the answers

What type of data is produced by the orders_by_date table creation?

Snapshot of the data Signup and view all the answers

Which of the following is not a recognized DLT best practice?

Running vacuum weekly Signup and view all the answers

Study Notes

Pipelines with Databricks Delta Live Tables 2

Change Data Capture (CDC) is used to maintain a current replica of a table.
APPLY CHANGES INTO statement is used.
Performs incremental/streaming ingestion of CDC data.
Simple syntax to specify primary key fields.
Defaults to inserts and updates.
Optionally applies deletes.
Automatically orders late data.
Ignores specified columns using EXCEPT.
Defaults to type 1 SCD.

Applying Changes

Syntax example:

APPLY CHANGES INTO LIVE.table_name
FROM STREAM(live.another_table)
KEYS (columns)
SEQUENCE BY timestamp_column;

Sequence indicates the order of applied changes (e.g., log sequence number, timestamp, ingestion time).

Third-Party Tools for Streaming Change Feeds

Kafka
Kinesis

Creating Customers_Silver Table

Creating the customers_silver table requires a separate statement.
customers_bronze_clean table is the streaming source.
customer_id is the primary key.
DELETE operations are identified.
timestamp field orders operations.
Excludes operation, source_file, and rescued_data from the target table.
Example code:

CREATE OR REFRESH STREAMING TABLE customers_silver;
APPLY CHANGES INTO LIVE.customers_silver
FROM STREAM(LIVE.customers_bronze_clean)
KEYS (customer_id)
APPLY AS DELETE WHEN operation = "DELETE"
SEQUENCE BY timestamp
COLUMNS * EXCEPT (operation, source_file, _rescued_data)

Automated Data Management

DLT (Databricks Delta Live Tables) automatically optimizes data for performance and ease of use.
Best practices encoded, e.g., optimizeWrite, autoCompact, tuneFileSizesForRewrites.
Physical data management (e.g., daily vacuum, optimize).
Schema evolution handled automatically (e.g., add, remove, rename columns).
Removing a column preserves old values.
NOT suitable for interactive execution in notebooks.
Requires scheduling within a pipeline for execution.

DLT Example

Creates a orders_silver table from orders_bronze.
Includes TBLPROPERTIES and validation of order_timestamp.
Update fails if conditions aren't met.

SQL vs. Python

Python API lacks syntax checks.
SQL API has syntax checks.
Python (DLT notebooks) errors show when running a cell, while SQL will check for invalid commands and display results.

Remarks on Imports

In both Python and SQL, individual notebook cells aren't suitable for DLT pipelines.
Importing the DLT module is explicit in Python, but not in SQL.

Tables as DataFrames and Queries

Python DataFrame API supports multiple transformations of datasets through API calls.
SQL transformations saved in temporary tables as transformations occur.

Comments and Table Properties

Python adds comments and table properties within the @dlt.table() function.
SQL utilizes COMMENT and TBLPROPERTIES.

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Description

This quiz covers the use of Change Data Capture (CDC) with Databricks Delta Live Tables, focusing on the APPLY CHANGES INTO statement and its syntax for streaming ingestion. Learn the details about table creation, primary key specification, and integration with third-party tools like Kafka and Kinesis.