Pipelines with Databrick Delta Live Tables Part 2/2

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to Lesson

Podcast

Play an AI-generated podcast conversation about this lesson

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?

<p>The order in which changes will be applied (A)</p> Signup and view all the answers

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

<p>SQL allows for syntax checks while Python does not. (D)</p> Signup and view all the answers

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

<p>Can only apply inserts (C)</p> Signup and view all the answers

How does data transformation differ between Python and SQL?

<p>In Python, multiple transformations can be applied in sequence directly, whereas SQL requires saving intermediate results. (B)</p> Signup and view all the answers

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

<p>Automated optimization for performance and ease of use (B)</p> Signup and view all the answers

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

<p>optimizePerformance (B)</p> Signup and view all the answers

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

<p>Kafka (D)</p> Signup and view all the answers

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

<p>Import the dlt module explicitly. (D)</p> Signup and view all the answers

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

<p>Vacuum and optimize processes (D)</p> Signup and view all the answers

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

<p>customer_id (C)</p> Signup and view all the answers

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

<p>To define transformations and logic of queries. (D)</p> Signup and view all the answers

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

<p>They are applied as deletes (D)</p> Signup and view all the answers

What is an incorrect statement regarding Python and SQL comments?

<p>SQL comments are added with TBLPROPERTIES. (A)</p> Signup and view all the answers

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

<p>Both addition and removal (A)</p> Signup and view all the answers

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

<p>They are ignored if out of sequence (A)</p> Signup and view all the answers

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

<p>Scheduling as part of a pipeline (D)</p> Signup and view all the answers

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

<p>Neither Python nor SQL allows running cells independently in DLT pipelines. (A)</p> Signup and view all the answers

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

<p>Old values are preserved (A)</p> Signup and view all the answers

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

<p>Python employs a proprietary API while SQL has a standard SQL API. (D)</p> Signup and view all the answers

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

<p>Python uses comments in a different format than SQL. (B)</p> Signup and view all the answers

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

<p>CREATE OR REFRESH STREAMING LIVE TABLE orders_silver (C)</p> Signup and view all the answers

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

<p>The update fails without any action (D)</p> Signup and view all the answers

How do transformations get specified in Python versus SQL?

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

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

<p>To filter out specific columns from the selection (A)</p> Signup and view all the answers

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

<p>Snapshot of the data (B)</p> Signup and view all the answers

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

<p>Running vacuum weekly (B)</p> Signup and view all the answers

Flashcards

Python API vs SQL

Python uses a Python API for data transformations, whereas SQL uses SELECT statements for transformations that are saved in temporary tables.

Delta Live Tables

A feature in Databricks that simplifies building data pipelines using SQL.

DLT Best Practices

DLT automatically sets properties like optimizeWrite, autoCompact, and tuneFileSizesForRewrites for better performance and cost efficiency of Delta Lake tables.

APPLY CHANGES INTO

A SQL statement in Delta Live Tables used for streaming ingestion of change data from one table to another.

Signup and view all the flashcards

Syntax Checks SQL

SQL checks for correct syntax in the query, offering instant feedback.

Signup and view all the flashcards

DLT Physical Data Management

DLT automatically manages physical data storage (vacuum and optimize) to minimize costs and optimize performance.

Signup and view all the flashcards

Python DLT Notebooks

DLT Python notebook cells are not designed for individual execution but rather for the DLT pipelines.

Signup and view all the flashcards

DLT Schema Evolution

DLT handles changes to table schemas, such as adding, removing, or renaming columns, automatically in live tables preserving previous values when removing a column.

Signup and view all the flashcards

Primary Key (KEYS)

A field or set of fields that uniquely identifies rows in a table, required in APPLY CHANGES INTO statement to define the unique identifier of the records.

Signup and view all the flashcards

SQL DLT Notebooks

SQL DLT notebook cells aren't meant for individual runs the same way as Python notebooks.

Signup and view all the flashcards

DLT Interactive Execution

DLT syntax is not designed for interactive use in notebooks; it's intended for use within scheduled pipelines.

Signup and view all the flashcards

Streaming ingestion

Incremental loading of data from a source to a destination in real-time.

Signup and view all the flashcards

Sequence BY

Ordering parameter in APPLY CHANGES INTO, specifying how the changes are ordered, e.g., timestamp or log sequence number.

Signup and view all the flashcards

DLT Streaming Table Creation (orders_silver)

Creates a live streaming table (orders_silver) from a bronze table (orders_bronze), adding a constraint and validating order_timestamp according to a condition.

Signup and view all the flashcards

@dlt.table() Python

Python annotations for defining data transformations and table properties.

Signup and view all the flashcards

DLT Aggregate Table (orders_by_date)

Creates a snapshot table (orders_by_date) summarizing data from a silver table (orders_silver) based on daily order counts.

Signup and view all the flashcards

SELECT statement SQL

Crucial SQL part for data transformations and query logic; contained inside.

Signup and view all the flashcards

EXCEPT

A SQL keyword to exclude specific columns from being copied in APPLY CHANGES INTO.

Signup and view all the flashcards

Type 1 SCD

A Slowly Changing Dimension type that stores only the latest value.

Signup and view all the flashcards

Live Table

A table where data is continuously updated; data in the table is added in real-time.

Signup and view all the flashcards

Python DataFrame API

Allows chaining multiple transformations by stringing together calls in code.

Signup and view all the flashcards

Change Data Capture (CDC)

A method to keep a replica of a table updated by tracking changes to the original table in real-time.

Signup and view all the flashcards

Snapshot Table

A table that captures a single moment in time, representing a static or aggregated view of the data.

Signup and view all the flashcards

SQL Data Transformations

Transformations in SQL happen through temporary tables.

Signup and view all the flashcards

SQL Comments

Uses COMMENT keyword to add comments and table properties

Signup and view all the flashcards

Automated data management

Data management tools that optimize data for better performance and ease of use in Databricks.

Signup and view all the flashcards

Python Comments

Python annotations @dlt.table() to add comments and table properties

Signup and view all the flashcards

Streaming source

The source table from where changes are captured and streamed into the target table in APPLY CHANGES INTO.

Signup and view all the flashcards

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.

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Quiz Team

Related Documents

Pipelines with Databricks Delta Live Tables 2 PDF

More Like This

Use Quizgecko on...
Browser
Open
Browser
Browser