Data Extraction in Apache Spark

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Questions and Answers

Which method is used to extract data from a single file in Apache Spark?

  • spark.extract
  • spark.create
  • spark.load
  • spark.read (correct)

What is the correct way to read all CSV files from a directory in Apache Spark?

  • spark.read.csv('path/to/your/directory') (correct)
  • spark.load.csv('path/to/your/directory')
  • spark.read.files('path/to/your/directory')
  • spark.read.directory('path/to/your/directory')

What does the prefix in the FROM clause indicate in Apache Spark SQL?

  • The SQL function to use
  • The name of the database
  • The format/source of the data (correct)
  • The table schema

Which of the following prefixes is used for reading JSON files in Apache Spark SQL?

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

Which command would you use to select data from a Hive table in Apache Spark SQL?

<p>SELECT * FROM hive.<code>database_name.table_name</code> (D)</p> Signup and view all the answers

What type of view is created in Apache Spark for temporary usage and is dropped after the session ends?

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

In the context of Apache Spark, which option correctly describes a view?

<p>It is a named logical schema representing a query. (A)</p> Signup and view all the answers

To read data from a JDBC source, what is the required syntax for the FROM clause?

<p>SELECT * FROM jdbc.<code>jdbc:postgresql://host:port/database_name?user=user&amp;password=password</code> (D)</p> Signup and view all the answers

What is the main purpose of creating views in Apache Spark?

<p>To encapsulate and reuse complex queries. (A)</p> Signup and view all the answers

How long does a temporary view persist in a Spark session?

<p>It is available only during the current session. (D)</p> Signup and view all the answers

What does a Common Table Expression (CTE) allow you to do in a SQL query?

<p>Reference a temporary result set within the query. (B)</p> Signup and view all the answers

Which of the following methods can be used to identify external source tables that are not Delta Lake tables?

<p>Listing tables and checking their format or using metadata. (A)</p> Signup and view all the answers

What is a disadvantage of using temporary views?

<p>They are not available in other sessions or after the current session ends. (C)</p> Signup and view all the answers

To check the format of a specific table in Spark, which command would you use?

<p>DESCRIBE DETAIL table_name. (B)</p> Signup and view all the answers

Using Python, which command initializes a Spark session?

<p>SparkSession.builder.appName() (A)</p> Signup and view all the answers

What would be the result of executing the command 'SHOW TABLES IN database_name'?

<p>It shows all tables present in the specified database. (B)</p> Signup and view all the answers

What should you do to avoid retrieving Delta Lake tables when querying?

<p>Filter tables by excluding specific patterns. (A)</p> Signup and view all the answers

What is an example of using metadata to identify non-Delta Lake tables?

<p>Accessing catalog metadata to filter by table type. (D)</p> Signup and view all the answers

Which of the following is true about the command 'CREATE OR REPLACE TEMP VIEW'?

<p>It creates a temporary view that can be queried during the session. (D)</p> Signup and view all the answers

In Spark, why might one need to filter out Delta Lake tables?

<p>To focus on processing tables from external sources. (C)</p> Signup and view all the answers

When defining a CTE, where is it utilized in SQL statements?

<p>Within SELECT, INSERT, UPDATE, or DELETE statements. (B)</p> Signup and view all the answers

What is a common outcome of using the spark.read method on a directory containing files?

<p>It creates a single DataFrame containing data from all files in the directory. (C)</p> Signup and view all the answers

When specifying a data source in Spark SQL, which prefix indicates data sourced from a JSON file?

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

In Apache Spark, when would you use a temporary view instead of a permanent view?

<p>When the view is needed only for the duration of a single session. (B)</p> Signup and view all the answers

How does Spark interpret the prefix included after the FROM keyword in a SQL query?

<p>It controls how Spark reads the data and its format. (B)</p> Signup and view all the answers

Which SQL command is used to reference a Hive table in Spark SQL?

<p>SELECT * FROM hive.<code>database_name.table_name</code> (D)</p> Signup and view all the answers

What does the command 'spark.read.csv' return when reading multiple CSV files from a directory?

<p>A single DataFrame containing concatenated data from all files. (C)</p> Signup and view all the answers

In which scenario would you use a Common Table Expression (CTE) in Spark SQL?

<p>To temporarily store results for reference within a single query. (D)</p> Signup and view all the answers

Which command is used to read data from Parquet files in Spark SQL?

<p>SELECT * FROM parquet.<code>/path/to/parquet/files</code> (C)</p> Signup and view all the answers

What happens to temporary views after the Spark session ends?

<p>They are dropped and cannot be accessed again. (C)</p> Signup and view all the answers

Which SQL command is used to define a Common Table Expression (CTE)?

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

When filtering out Delta Lake tables, what is the key characteristic of Delta tables?

<p>They often have a '.delta' suffix in their names. (C)</p> Signup and view all the answers

Which method allows you to check the format of a specific table in Spark SQL?

<p>DESCRIBE DETAIL (A)</p> Signup and view all the answers

How can you create a temporary view from a DataFrame in Spark?

<p>df.createOrReplaceTempView('my_temp_view') (A)</p> Signup and view all the answers

What would you expect from the command 'spark.sql("SELECT * FROM my_view").show()'?

<p>It will display all records from the my_view. (C)</p> Signup and view all the answers

In which scenario would you choose to use metadata to identify non-Delta Lake tables?

<p>When you have a catalog that stores table metadata. (C)</p> Signup and view all the answers

What is the primary purpose of creating views in Apache Spark?

<p>To encapsulate and reuse complex queries. (D)</p> Signup and view all the answers

What is a unique feature of Common Table Expressions (CTEs) compared to regular views?

<p>CTEs are defined within the same SQL statement they are used. (A)</p> Signup and view all the answers

What is one limitation of using temporary views in Spark SQL?

<p>They can only be used in the same session and are not persisted. (D)</p> Signup and view all the answers

What is the purpose of the command 'spark.read.csv' when creating views in Spark?

<p>To read data from the file and create a DataFrame. (A)</p> Signup and view all the answers

Which of the following statements is NOT true about temporary views?

<p>They can be shared across different Spark sessions. (A)</p> Signup and view all the answers

In the filtering process to exclude Delta Lake tables, what method is used to obtain a list of tables?

<p>SHOW TABLES IN database_name (D)</p> Signup and view all the answers

Flashcards

Reading data from a single file using Spark

Use spark.read.csv("path/to/file") for CSV, or equivalent for other formats like JSON or Parquet, to create a Spark DataFrame from a single file.

Reading data from a directory in Spark

Use spark.read.csv("path/to/directory") to read all files in a directory. Spark automatically processes multiple files.

Data type prefix in Spark SQL (FROM clause)

The prefix after FROM in Spark SQL specifies the data source (e.g., csv, parquet, json, hive, jdbc) telling Spark how to read data.

CSV file type in Spark SQL

Use csv after FROM when querying CSV files in Spark SQL, as in SELECT * FROM csv./path/to/file`.

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Parquet file type in Spark SQL

Use parquet after FROM when querying Parquet files in Spark SQL as in SELECT * FROM parquet./path/to/file`

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JSON file type in Spark SQL

Use json after FROM when querying JSON files in Spark SQL to specify processing of JSON data

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Hive table in Spark SQL

Use hive after FROM when querying Hive tables in Spark SQL as in SELECT * FROM hive.database_name.table_name`

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JDBC table in Spark SQL

Use jdbc after FROM when querying data from an external database, specifying connection details.

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Spark View

A named, logical representation of the data.

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Spark Temporary View

A short-lived view, only usable within the current Spark session.

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Spark CTE (Common Table Expression)

A temporary, named expression used within queries.

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Views in Spark

Views in Spark are saved queries that encapsulate and reuse complex queries on data. This simplifies accessing data.

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Temporary View

A temporary view in Spark is a view that exists only during the current Spark session. It's not stored permanently.

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Common Table Expression (CTE)

A CTE is a temporary result set defined within a query. It's helpful for breaking down complex queries.

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ELT Workflow

Extract, Load, Transform (ELT) is a data processing technique where data is loaded from various sources, transformed, and then stored in the target data warehouse.

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Delta Lake tables

Delta Lake tables are a special type of data table in Apache Spark that offer advantages like ACID transactions, data versioning, and efficient data integration.

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Non-Delta Tables

Tables in an external source that are not Delta Lake tables. They could be from various formats.

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Identifying non-Delta tables (Listing)

Method for finding tables in a database that are not formatted as Delta Lake tables, by filtering table names to exclude '.delta'.

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Identifying non-Delta tables (Checking format)

Method for finding tables that are not Delta lake table by checking the format of each table.

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Identifying non-Delta tables (Using metadata)

Method for finding tables that are not Delta Lake tables by inspecting catalog metadata.

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Spark View

A named, logical representation of data in Spark. It's a saved query that encapsulates and reuses complex queries.

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Temporary View

A view in Spark that exists only during the current Spark session and is not stored permanently.

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CTE (Common Table Expression)

A temporary, named result set defined within a query. Useful for breaking down complicated queries.

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Non-Delta Table

A table in an external source that is not a Delta Lake table.

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Identifying Non-Delta Tables (Listing)

Finding tables in a database that are not Delta Lake tables by filtering out table names containing ".delta".

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Identifying Non-Delta Tables (Format Check)

Determining if a table is not a Delta Lake table by examining its format using Spark's metadata.

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Identifying Non-Delta Tables (Metadata)

Locating tables that are not Delta Lake tables via Spark's catalog metadata.

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Spark Read Single File

Reads data from a single file using Spark's spark.read method with the file format and path.

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Spark Read Directory

Reads data from a directory of files in Spark, Spark automatically reads all files in the folder.

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Data Source Prefix (FROM)

In Spark SQL, the prefix following FROM indicates the data source (e.g., csv, parquet, json).

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Spark SQL CSV

Specifies that the data is coming from a Comma Separated Value (CSV) file in Spark SQL.

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Spark SQL Parquet

Indicates the data is in Parquet format, used for efficient data storage in Spark SQL.

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Spark SQL JSON

Specifies JSON file format for Spark SQL data access.

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Spark SQL Hive Table

Reads data from a Hive table in Spark SQL.

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Spark SQL JDBC

Specifies external data source (e.g., a database) using JDBC, requiring a connection URL/credentials in Spark SQL.

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Spark View

A named, logical, schema view of data.

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Spark Temporary View

A view that exists only during the current Spark session.

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Spark CTE

A temporary, named result set within a Spark SQL query.

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Study Notes

Extracting Data from Files in Apache Spark

  • Single file extraction: Use spark.read.csv() (or other formats like JSON, Parquet) to read data from a specified file path.
  • Directory extraction: Use spark.read.csv() (or other formats) to read all files within a given directory. Spark automatically handles multiple files.
  • Code example (single file):
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("example").getOrCreate()
df = spark.read.csv("path/to/your/file.csv")
df.show()
  • Code example (directory):
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("example").getOrCreate()
df = spark.read.csv("path/to/your/directory")
df.show()

Data Source Prefixes in Spark SQL

  • Data Source Identification: The prefix after FROM in Spark SQL queries (e.g., csv, parquet, json, hive, jdbc) indicates how Spark should interpret and access the data.
  • Examples:
    • `SELECT * FROM csv./path/to/csv/files: Reads from CSV files.
    • `SELECT * FROM hive.database_name.table_name: Reads from Hive tables.
    • `SELECT * FROM jdbc.jdbc:postgresql://host:port/database_name?user=user&password=password: Reads from JDBC-connected tables.

Creating Views, Temporary Views, and CTEs

  • Views: Named logical schemas for reusable complex queries.
  • Creating a view:
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("ELT Example").getOrCreate()
df = spark.read.csv("path/to/your/file.csv", header=True, inferSchema=True)
df.createOrReplaceTempView("my_view")
spark.sql("SELECT * FROM my_view").show()
  • Temporary Views: Accessible only during the current Spark session, not stored persistently.
  • Creating a temporary view:
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("ELT Example").getOrCreate()
df = spark.read.csv("path/to/your/file.csv", header=True, inferSchema=True)
df.createOrReplaceTempView("my_temp_view")
spark.sql("SELECT * FROM my_temp_view").show()
  • Common Table Expressions (CTEs): Temporary result sets used within queries.
  • Creating a CTE:
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("ELT Example").getOrCreate()
df = spark.read.csv("path/to/your/file.csv", header=True, inferSchema=True)
df.createOrReplaceTempView("my_temp_view")
ct_query = """
WITH my_cte AS (
    SELECT * FROM my_temp_view
)
SELECT * FROM my_cte
"""
spark.sql(ct_query).show()

Identifying Non-Delta Lake Tables

  • External source tables are not Delta Lake tables by default. Use methods to distinguish them.

  • Methods for identifying non-Delta tables:

    • Listing tables: List all tables and filter by exclusion pattern (e.g., LIKE '%.delta%').
    • Checking table format: Query table details to find the table format and filter accordingly.
    • Using metadata: Query metadata stored in the catalog to find non-Delta Lake table types.

  • Example (listing tables):

from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("ELT Example").getOrCreate()
tables = spark.sql("SHOW TABLES IN database_name")
non_delta_tables = tables.filter("NOT tableName LIKE '%.delta%'")
non_delta_tables.show()

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