Databricks Data Engineering with Delta Lake

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 does the _delta_log folder contain in managed tables?

  • Backup copies of the data
  • Compressed version of the data files
  • Temporary staging files for uploads
  • JSON files with transaction history (correct)

How can a previous version of a table be restored in Delta Lake?

  • Using the RESTORE command with table name (correct)
  • Using the VACUUM command with a timestamp
  • With the OPTIMIZE command specifying version number
  • By executing the DROP command first

What SQL command is used to reduce the size of log files in Delta Lake by combining records?

  • VACUUM
  • CREATE TABLE
  • OPTIMIZE (correct)
  • RESTORE

What is the purpose of the VACUUM command in Delta Lake?

<p>To clean up unused and old files (D)</p> Signup and view all the answers

What does the ZORDER option do when optimizing a table in Delta Lake?

<p>It creates indexes based on specified columns (D)</p> Signup and view all the answers

Which command will prevent the deletion of files older than 7 days during the VACUUM process?

<p>SET spark.databricks.delta.retentionDurationCheck.enable = true; (B)</p> Signup and view all the answers

What is required to view the transaction history of a Delta table?

<p>Running DESCRIBE HISTORY on the table (A)</p> Signup and view all the answers

What happens when the RESTORE command is executed in Delta Lake?

<p>It adds a new version to the table's history (D)</p> Signup and view all the answers

What is the main difference between 'Create or replace as' (CRAS) and 'Insert Overwrite'?

<p>CRAS can create a new table while Insert Overwrite cannot. (D)</p> Signup and view all the answers

Which of the following statements is true regarding the Insert Overwrite operation?

<p>It can only substitute existing records that match the table's schema. (D)</p> Signup and view all the answers

What is a notable benefit of using the merge or upsert statement?

<p>It allows multiple conditions to be enforced in one transaction. (A)</p> Signup and view all the answers

How can duplication be avoided when using the merge operation?

<p>By providing only an insert in the 'when not matched' clause. (A)</p> Signup and view all the answers

What are the expectations for the Copy Into operation in Databricks?

<p>The data schema should be consistent, and duplicates should be handled appropriately. (B)</p> Signup and view all the answers

Which operation is potentially cheaper for incrementally ingesting data according to the expected behaviors?

<p>Copy Into operations. (C)</p> Signup and view all the answers

What is a key feature of the merge statement in terms of database operations?

<p>It allows batch processing of multiple records. (C)</p> Signup and view all the answers

Which statement accurately reflects the limitations of Insert Overwrite?

<p>It can only overwrite existing tables with records of the same schema. (C)</p> Signup and view all the answers

Which command can be used to check the metadata of an external table?

<p>DESCRIBE EXTENDED external_table; (D)</p> Signup and view all the answers

What is a key characteristic of User-Defined Functions (UDFs) in Databricks?

<p>UDFs introduce interprocess communication overhead in Python. (B)</p> Signup and view all the answers

To drop duplicates from a DataFrame, which Python command is correct?

<p>dataFrame.dropDuplicates().count() (C)</p> Signup and view all the answers

Which statement correctly formats a date from a timestamp column in SQL?

<p>SELECT date_format(datetime_col, 'MMM d, yyyy') AS date_col; (D)</p> Signup and view all the answers

When reading a CSV file into Databricks, which option can specify that the CSV has a header?

<p>header='true' (A)</p> Signup and view all the answers

What aspect of Delta Lake ensures that all transactions are atomic?

<p>ACID Transactions (A)</p> Signup and view all the answers

In Databricks, which of the following is NOT a method of dealing with null values?

<p>delete from table_name where col is NULL; (C)</p> Signup and view all the answers

Which of the following SQL commands can create an external table with CSV data?

<p>CREATE TABLE table_name USING CSV OPTIONS(header='true', delimiter='|') LOCATION 'path'; (C)</p> Signup and view all the answers

In the context of Delta Lake, what does cloning refer to?

<p>Taking a snapshot of the data at a specific point in time. (B)</p> Signup and view all the answers

When formatting date and time in Python using DataFrame, which command correctly formats the time column?

<p>dataFrame.withColumn('time_col', date_format('datetime_col', 'HH:mm:ss')) (C)</p> Signup and view all the answers

Flashcards

Delta Lake Versioning

Delta Lake stores table versions in the '_delta_log' folder, each with a timestamp and version number, enabling time travel.

Time Travel in Delta

Querying a specific table version using TIMESTAMP AS OF or VERSION AS OF clauses and restoring to a prior version with RESTORE TABLE.

Optimize Delta Table

Combining and rewriting records to speed up retrieval using the OPTIMIZE command, optionally with ZORDER for indexing.

Delta Lake Vacuum

Removes unused, old files from the table using VACUUM, improving storage and enforcing retention policies.

Signup and view all the flashcards

CRAS Overwrite

Creates or replaces a table; a new table if it's the first time or a replacement with the new data.

Signup and view all the flashcards

Insert Overwrite

Overwrites an existing table using a new dataset while requiring matching schema.

Signup and view all the flashcards

Merge Statement

Inserts, updates, or deletes records in a single transaction in a table, enabling custom logic using WHEN MATCHED and WHEN NOT MATCHED clauses.

Signup and view all the flashcards

Querying Files Directly

SQL queries can directly access files in various formats like TEXT, JSON, CSV, and BINARY.

Signup and view all the flashcards

External Tables

Accesses external data sources without copying the data, defined via CREATE TABLE.

Signup and view all the flashcards

Data Cleaning Techniques

Techniques like COUNT_IF, COUNT, DISTINCT, date formatting (date_format, regexp_extract) and custom UDFs for data transformation.

Signup and view all the flashcards

User-Defined Functions (UDFs)

Custom data manipulation or transformation logic that enhances data processing in Databricks.

Signup and view all the flashcards

Study Notes

Databricks Delta Lake

  • Delta Lake allows for versioning of data in a table.
  • Versions are stored in a folder called _delta_log
  • Each version has a specific timestamp and version number.
  • You can query a specific version of a table using the TIMESTAMP AS OF and VERSION AS OF clauses.
  • You can restore a table to a previous version using RESTORE TABLE and specifying the timestamp or version number.
  • This process is known as time-traveling.
  • Restore creates a new version in the table's history.
  • For improved retrieval, you can optimize a table by combining records and rewriting the results.
  • The OPTIMIZE command can be used for this.
  • You can also include a ZORDER clause to create an index for fast retrieval.
  • Delta Lake uses a vacuum process to clean unused and old files .
  • This helps reduce storage costs and enforce retention policies.
  • The VACUUM command deletes files older than a specified time.
  • The RETAIN option can be used to specify a retention period, default is 7 days.
  • Premature deletion can be prevented by disabling the retention duration check.
  • DRY RUN option is used to print all records to be deleted without performing the vacuum operation.

Overwriting Tables

  • Two methods for overwriting tables: Create or Replace as (CRAS) and Insert Overwrite.
  • The CREATE OR REPLACE TABLE statement creates a new table if one doesn't exist or replaces the existing table.
  • Insert overwrite overwrites an existing table using a new data source.
  • Insert overwrite can only overwrite existing tables, not create new tables.
  • Insert overwrite requires new records to match the table's schema.
  • It can overwrite individual partitions, enforcing the same schema.

Merge

  • The MERGE statement supports inserting, updating, and deleting records using a single transaction.
  • Enables the implementation of custom logic with extensive options.
  • Syntax includes WHEN MATCHED and WHEN NOT MATCHED clauses for applying update and insert operations.
  • Merge can be used to avoid duplicate records by only inserting new records using a single transaction, using WHEN NOT MATCHED.
  • For incremental data ingestion, the COPY INTO command is used, making it efficient for large datasets.
  • Data schema consistency and handling of duplicates are essential considerations.

Query Files

  • Data files can be queried directly in SQL.
  • Supported file formats include: FILE_FORMAT, TEXT, JSON, CSV, and BINARY_FILE.
  • Each format can be specified in the SQL statement.

External Tables

  • External tables allow access to external data sources without copying it into Databricks.
  • They are defined using a CREATE TABLE statement with the specific file format and options.
  • External tables can be described using DESCRIBE EXTENDED and refreshed using REFRESH TABLE.
  • External tables can be created using different methods (e.g., CSV, JDBC, JSON).

Data Cleaning

  • COUNT_IF and COUNT with WHERE conditions can be used to identify null values.
  • DISTINCT can be used to remove duplicate records.
  • Date formatting can be achieved with date_format and regexp_extract functions.
  • Custom column transformations can be achieved using user-defined functions (UDFs).

User-Defined Functions

  • UDFs provide a way to create custom logic for transforming data.
  • UDFs cannot be optimized by the Spark Catalyst Optimizer.
  • UDFs are serialized and sent to executors, resulting in overhead.
  • udf() function registers a UDF for use in DataFrame transformations.
  • UDFs are a powerful tool for custom data manipulation and transformations.

Studying That Suits You

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

Quiz Team

Related Documents

Data Engineering with Databricks.pdf

More Like This

Use Quizgecko on...
Browser
Open
Browser
Browser