{"id":93711,"date":"2025-03-19T14:54:27","date_gmt":"2025-03-19T09:24:27","guid":{"rendered":"https:\/\/cloudfoundation.com\/blog\/?p=93711"},"modified":"2026-02-04T15:06:29","modified_gmt":"2026-02-04T09:36:29","slug":"spark-sql-tutorial","status":"publish","type":"post","link":"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/","title":{"rendered":"Spark SQL Tutorial"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.9.7&#8243;][et_pb_row _builder_version=&#8221;4.9.7&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_post_title meta=&#8221;off&#8221; featured_image=&#8221;off&#8221; _builder_version=&#8221;4.9.7&#8243; title_font=&#8221;Times New Roman||||||||&#8221; title_text_align=&#8221;left&#8221; title_text_color=&#8221;#000000&#8243; title_font_size=&#8221;47&#8243; background_color=&#8221;RGBA(0,0,0,0)&#8221; background_enable_image=&#8221;off&#8221; custom_margin=&#8221;|||10%&#8221; title_font_size_tablet=&#8221;40&#8243; title_font_size_phone=&#8221;35&#8243; title_font_size_last_edited=&#8221;on|desktop&#8221;][\/et_pb_post_title][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.9.7&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.9.7&#8243; text_font=&#8221;Georgia||||||||&#8221; text_text_color=&#8221;#000000&#8243; text_font_size=&#8221;22px&#8221; text_line_height=&#8221;1.9em&#8221; max_width=&#8221;800px&#8221; max_width_last_edited=&#8221;off|phone&#8221; custom_margin=&#8221;|||10%&#8221; custom_margin_last_edited=&#8221;off|desktop&#8221; text_font_size_tablet=&#8221;&#8221; text_font_size_phone=&#8221;&#8221; text_font_size_last_edited=&#8221;on|phone&#8221; text_line_height_last_edited=&#8221;off|phone&#8221;]<\/p><div id=\"ez-toc-container\" class=\"ez-toc-v2_0_80 ez-toc-wrap-center counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<span class=\"ez-toc-title-toggle\"><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Introduction_to_Spark_Framework\" >Introduction to Spark Framework<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Spark_API_Algorithms_and_Components\" >Spark API Algorithms and Components<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Spark_API\" >Spark API<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Spark_SQL\" >Spark SQL<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Spark_SQL_architecture\" >Spark SQL architecture<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Challenges_and_Benefits_of_Spark_SQL\" >Challenges and Benefits of Spark SQL<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Data_Organization\" >Data Organization<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Spark_can_create_an_EMP_data_frame\" >Spark can create an EMP data frame<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Apache_Hive\" >Apache Hive<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Hive_Meta_Store_for_Spark_SQL\" >Hive Meta Store for Spark SQL<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#The_performance_of_Spark_SQL_compared_to_Hado\" >The performance of Spark SQL compared to Hado<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/#Data_Frames\" >Data Frames<\/a><\/li><\/ul><\/nav><\/div>\n\n<h2><span class=\"ez-toc-section\" id=\"Introduction_to_Spark_Framework\"><\/span><strong>Introduction to Spark Framework<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark Framework is an open-source cluster computing and fast processing engine which has become essential to industry for big data processing and analysis. Built around speed, ease-of-use and analytics features, Spark is ideal for large scale dataset projects as it ensures efficient management and data efficiency.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Spark_API_Algorithms_and_Components\"><\/span><strong>Spark API Algorithms and Components<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark API offers an assortment of machine-learning algorithms, such as classification, regression, clustering and collaborative filtering, which are intended for implementation using code written from scratch. Furthermore, there&#8217;s also an ML library designed specifically for machine learning tasks.<\/p>\n<p>Spark Step, responsible for manipulating graphX files, is another component of Spark API that serves an integral function in its overall implementation. This component allows users to manipulate graphX directly.<\/p>\n<p><img decoding=\"async\" class=\"size-medium aligncenter\" src=\"https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2025\/03\/Spark-SQL-Overview.png\" alt=\"\" width=\"800\" height=\"2890\" \/><\/p>\n<p>Implementation of machine learning algorithms into IoT scenarios such as big data analytics and ML Lib scenarios has the ability to process zero-structured sources, like Hive, while simultaneously processing live streaming data via Park Streaming.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Spark_API\"><\/span><strong>Spark API<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark is a relational data processing API designed for efficient processing of various structured and non-structured sources, including CSV files, JSON files and K files. Designed to work across resources including Cascading Node databases such as Cassandra and Couchbase that provide schemaRDDs which provide additional RDD storage space efficiently across machines for more effective data analysis. The Spark object may even be processed across machines for rapid data collection.<\/p>\n<p>Spark API&#8217;s execution flow revolves around carrying out various tasks, from processing large files and complex data sets, to meeting performance goals with higher performance goals. Spark API offers a high-level abstraction layer which facilitates improved integration between tasks and data types.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Spark_SQL\"><\/span><strong>Spark SQL <\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark SQL is an exceptional data processing tool designed to enable users to process structured information from various sources with defined schema. Each Rho object represents one record; Park SQL allows users to query this data using this mechanism.<\/p>\n<p>External tools, including JDBC and ODBC database connectors, may be utilized to connect Spark SQL. Furthermore, these external tools may also help integrate it with business intelligence (BI) tools like Tableau.<\/p>\n<p>Spark SQL&#8217;s foundational abstraction, the DataFrame, allows users to organize data in multiple columns for access and manipulation in different ways.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Spark_SQL_architecture\"><\/span><strong>Spark SQL architecture<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark SQL is an open-source database management system which stores and retrieves information from multiple sources &#8211; CSV files, JSON strings, or JDBC formats are supported &#8211; quickly and effortlessly.<\/p>\n<p>Designed to be easy for its users and administrators alike to maintain, with features like user-defined data registration (UDF) registration as well as creating data frames using different APIs available within it.<\/p>\n<p><img decoding=\"async\" class=\"size-medium aligncenter\" src=\"https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2025\/03\/Spark-SQL-Architecture.png\" alt=\"\" width=\"800\" height=\"2304\" \/><\/p>\n<p>Created using various formats including CSV, JSON and JDBC data sources API&#8217;s, creating a data frame involves gathering its components together before being transformed using data source API into its final form.<\/p>\n<p>When developing such structures it&#8217;s imperative that creators consider both their database&#8217;s specific requirements as well as those being addressed when building out data frames.<\/p>\n<p>Spark SQL architecture also offers various methods for accessing and manipulating data, including show API to retrieve output and source API to retrieve source. As such, Spark SQL architecture serves as an all-inclusive solution for securely and efficiently storing information.[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_3,1_3,1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#064399&#8243; use_background_color_gradient=&#8221;on&#8221; background_color_gradient_start=&#8221;#0095f2&#8243; background_color_gradient_end=&#8221;#7dbed8&#8243; background_color_gradient_direction=&#8221;92deg&#8221; background_color_gradient_start_position=&#8221;35%&#8221; background_color_gradient_end_position=&#8221;80%&#8221; transform_scale=&#8221;73%|62%&#8221; transform_scale_linked=&#8221;off&#8221; transform_translate=&#8221;-53px|-50px&#8221; transform_translate_linked=&#8221;off&#8221; link_option_url=&#8221;https:\/\/cloudfoundation.com\/blog\/&#8221; link_option_url_new_window=&#8221;on&#8221;][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2023\/06\/SS_436-_Converted_-1.png&#8221; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; transform_scale=&#8221;114%|112%&#8221; transform_scale_linked=&#8221;off&#8221; transform_translate=&#8221;25px|-4px&#8221; transform_translate_linked=&#8221;off&#8221; width=&#8221;98.1%&#8221; custom_margin=&#8221;|7px|||false|false&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; text_font=&#8221;Georgia|700|||||||&#8221; text_font_size=&#8221;23px&#8221; text_line_height=&#8221;1.3em&#8221; header_font=&#8221;Georgia|700|||||||&#8221; header_font_size=&#8221;21px&#8221; header_letter_spacing=&#8221;-1px&#8221; header_line_height=&#8221;2em&#8221; transform_scale=&#8221;171%|159%&#8221; transform_scale_linked=&#8221;off&#8221; transform_translate=&#8221;40px|44px&#8221; transform_translate_linked=&#8221;off&#8221; transform_origin=&#8221;70%|50%&#8221; z_index=&#8221;-161&#8243; width=&#8221;100%&#8221; custom_margin=&#8221;|-215px||||&#8221; custom_padding=&#8221;|0px||||&#8221; link_option_url=&#8221;https:\/\/cloudfoundation.com\/blog\/&#8221; link_option_url_new_window=&#8221;on&#8221;]<\/p>\n<h1 style=\"text-align: center;\"><span style=\"color: #ffffff;\"><strong>Spark SQL <\/strong> Training<\/span><\/h1>\n<p>[\/et_pb_text][et_pb_button button_url=&#8221;https:\/\/cloudfoundation.com\/blog\/&#8221; url_new_window=&#8221;on&#8221; button_text=&#8221;Explore Course Content&#8221; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; custom_button=&#8221;on&#8221; button_text_color=&#8221;#0C71C3&#8243; button_bg_color=&#8221;#FFFFFF&#8221; button_font=&#8221;|700|||||||&#8221; transform_translate=&#8221;64px|65px&#8221; transform_translate_linked=&#8221;off&#8221;][\/et_pb_button][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2019\/06\/logo_resize_color.png&#8221; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; transform_translate=&#8221;-36px|0px&#8221; transform_translate_linked=&#8221;off&#8221; custom_margin=&#8221;|||178px||&#8221;][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.9.7&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.9.7&#8243; text_font=&#8221;Georgia||||||||&#8221; text_text_color=&#8221;#000000&#8243; text_font_size=&#8221;22px&#8221; text_line_height=&#8221;1.9em&#8221; max_width=&#8221;800px&#8221; max_width_last_edited=&#8221;off|phone&#8221; custom_margin=&#8221;|||10%&#8221; custom_margin_last_edited=&#8221;off|desktop&#8221; hover_enabled=&#8221;0&#8243; text_font_size_tablet=&#8221;&#8221; text_font_size_phone=&#8221;&#8221; text_font_size_last_edited=&#8221;on|phone&#8221; text_line_height_last_edited=&#8221;off|phone&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Challenges_and_Benefits_of_Spark_SQL\"><\/span><strong>Challenges and Benefits of Spark SQL<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark SQL can bring several challenges and benefits when used for data analysis, from converting an input data frame into 2DFS format and creating temporary views or tables, through to passing up our SQL statements with SparkSQL for evaluation of performance of temporary views created within 2DFS files.<\/p>\n<p><img decoding=\"async\" class=\"size-medium aligncenter\" src=\"https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2025\/03\/Spark-SQL-Challenges.png\" alt=\"\" width=\"800\" height=\"2876\" \/><\/p>\n<p>Spark SQL presents us with the challenge of performing any SQL query without directly accessing its original data frame, instead we must create temporary tables or views identical to its original one and write or replace statements to execute all <a href=\"https:\/\/spark.apache.org\/docs\/latest\/sql-ref-syntax-ddl-create-view.html\" rel=\"nofollow\">Temporary view<\/a> or table queries.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Data_Organization\"><\/span><strong>Data Organization<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Data is organized into named columns to create an illusion of order. This data comes from relational databases.<\/p>\n<p>Data processing occurs using SparkSQL before being imported to an SQL-based database like Cassandra. To open the Spark shell and load competitive X Spark CSV packages into it. &#8220;Open spark&#8221; opens it first then loads them using &#8220;load package&#8221;.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Spark_can_create_an_EMP_data_frame\"><\/span><strong>Spark can create an EMP data frame<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Process involves loading an EMP dot file and creating a data frame using Spark library, before displaying in its schema format which Spark automatically understands.<\/p>\n<p>Schemas provide options such as ID integer, Name string and Fields which make up several options in schema representation of data frames.<\/p>\n<p>Users are then presented with an entire dataset in data frame format for exploration and operations such as filtering dot filters or selecting specific departments.<\/p>\n<p>Spark makes creating data frames both complex and time consuming; however, its advantages include improved performance and flexibility when handling large datasets.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Apache_Hive\"><\/span><strong>Apache Hive <\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Apache Hive is an innovative database management system, offering developers access to writing SQL queries that will then be translated into MapReduce jobs resulting in slower performance than its competitor systems such as MySQL or MSSQL.<\/p>\n<p><img decoding=\"async\" class=\"size-medium aligncenter\" src=\"https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2025\/03\/Spark-SQL-Advantages.png\" alt=\"\" width=\"800\" height=\"1940\" \/><\/p>\n<p>Apache Hive can present several challenges when handling smaller datasets &#8211; particularly those less than 200GB in size &#8211; leading to performance issues such as no resume capability and stuck systems; difficulties starting or restarting Hive; as well as not allowing dropping encrypted databases which presents additional security concerns.<\/p>\n<p>Spark SQL has successfully overcome many of its issues and can run faster with MapReduce.<\/p>\n<p>Spark SQL excels over Hive due to its in-memory computation abilities, enabling it to process data directly in memory and complete queries in under one minute compared to Hive&#8217;s 10-minute query performance.<\/p>\n<p>Spark SQL offers several distinct advantages over Hive, including faster performance, enhanced data management and greater data storage capacities.[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_3,1_3,1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#064399&#8243; use_background_color_gradient=&#8221;on&#8221; 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link_option_url_new_window=&#8221;on&#8221;]<\/p>\n<h1 style=\"text-align: center;\"><span style=\"color: #000000;\"><strong>Spark SQL <\/strong> Online Training<\/span><\/h1>\n<p>[\/et_pb_text][et_pb_button button_url=&#8221;https:\/\/cloudfoundation.com\/blog\/&#8221; url_new_window=&#8221;on&#8221; button_text=&#8221;Up Coming Batches&#8221; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; custom_button=&#8221;on&#8221; button_text_color=&#8221;#E09900&#8243; button_bg_color=&#8221;#FFFFFF&#8221; button_font=&#8221;|700|||||||&#8221; transform_translate=&#8221;64px|65px&#8221; transform_translate_linked=&#8221;off&#8221; background_layout=&#8221;dark&#8221;][\/et_pb_button][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2019\/06\/logo_resize_color.png&#8221; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; 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text_line_height_last_edited=&#8221;off|phone&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Hive_Meta_Store_for_Spark_SQL\"><\/span><strong>Hive Meta Store for Spark SQL <\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark SQL takes full advantage of Hive&#8217;s metastore services to query data stored and managed by Hive, making query creation and management efficient and timely.<\/p>\n<p>All Spark SQL-generated tables or queries can also be stored directly within Hive&#8217;s megastore allowing faster execution time while improving efficiency.<\/p>\n<p>Spark SQL relies heavily on computation for faster results, with computation taking place entirely within memory reducing storage requirements and speed.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_performance_of_Spark_SQL_compared_to_Hado\"><\/span><strong>The performance of Spark SQL compared to Hado<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Spark SQL&#8217;s performance compares favorably with Hado. One feature unique to Spark SQL is its ability to establish connections using simple, JDBC or <a href=\"https:\/\/learn.microsoft.com\/en-us\/sql\/connect\/odbc\/download-odbc-driver-for-sql-server?view=sql-server-ver17\" rel=\"nofollow\">ODBC Drivers<\/a> allowing users to connect to Spark SQL using all three drivers simultaneously.<\/p>\n<p><img decoding=\"async\" class=\"size-medium aligncenter\" src=\"https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2025\/03\/SparkSQL-Performance.png\" alt=\"\" width=\"800\" height=\"1719\" \/><\/p>\n<p>Users may create user-defined functions (UDF) if no function exists to fill their need, while UDF (Understanding Data Functions) allow for execution of unavailable functions.<\/p>\n<p>Spark SQL offers additional features, including user-defined functions that allow for greater customization when standard functions become unavailable, helping users create customized functions more quickly while improving calculations more efficiently.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Data_Frames\"><\/span><strong>Data Frames <\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Data Frames are structured databases designed to store and process structured and unstructured data using SQL queries, to convert raw information into formats which can then be processed using various APIs such as Data Frame DSL or Spark SQL.<\/p>\n<p>Data frames store columns from all data nodes, including worker notes, column details and row details. They&#8217;re then converted into data frames using APIs such as DataFrameDSL or Spark SQL for easy storage and processing.<\/p>\n<p>The Data Source API reads and stores structured and unstructured data into SQL databases while Data Frame API reads and stores it directly into an SQL table.<\/p>\n<p>Data frames are essential in managing and processing structured and unstructured data in SQL databases efficiently and provide a centralised platform for accessing and processing it. Understanding various types of data frames as well as their applications for effective data management and analysis.[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_3,1_3,1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#064399&#8243; use_background_color_gradient=&#8221;on&#8221; background_color_gradient_start=&#8221;#494fff&#8221; background_color_gradient_end=&#8221;#9ea6ff&#8221; background_color_gradient_type=&#8221;radial&#8221; background_color_gradient_direction_radial=&#8221;top left&#8221; background_color_gradient_start_position=&#8221;35%&#8221; background_color_gradient_end_position=&#8221;80%&#8221; transform_scale=&#8221;74%|71%&#8221; transform_scale_linked=&#8221;off&#8221; transform_translate=&#8221;-53px|-50px&#8221; transform_translate_linked=&#8221;off&#8221; link_option_url=&#8221;https:\/\/cloudfoundation.com\/blog\/&#8221; link_option_url_new_window=&#8221;on&#8221;][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2023\/06\/Untitled-11.png&#8221; title_text=&#8221;Untitled-11&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; transform_scale=&#8221;103%|103%&#8221; transform_scale_linked=&#8221;off&#8221; transform_translate=&#8221;11px|0px&#8221; transform_translate_linked=&#8221;off&#8221; custom_padding=&#8221;|88px||||&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; text_font=&#8221;Georgia|700|||||||&#8221; text_text_color=&#8221;#FFFFFF&#8221; text_font_size=&#8221;23px&#8221; text_line_height=&#8221;1.3em&#8221; header_font=&#8221;Georgia|700|||||||&#8221; header_font_size=&#8221;19px&#8221; header_letter_spacing=&#8221;-1px&#8221; header_line_height=&#8221;1.2em&#8221; transform_scale=&#8221;171%|159%&#8221; transform_scale_linked=&#8221;off&#8221; transform_translate=&#8221;40px|44px&#8221; transform_translate_linked=&#8221;off&#8221; transform_origin=&#8221;70%|50%&#8221; z_index=&#8221;-161&#8243; width=&#8221;100%&#8221; custom_margin=&#8221;|-215px||||&#8221; custom_padding=&#8221;|0px||||&#8221; link_option_url=&#8221;https:\/\/cloudfoundation.com\/blog\/&#8221; link_option_url_new_window=&#8221;on&#8221;]<\/p>\n<h1 style=\"text-align: center;\"><span style=\"color: #ffffff;\"><strong>Spark SQL Course Price<\/strong><\/span><\/h1>\n<p>[\/et_pb_text][et_pb_button button_url=&#8221;https:\/\/cloudfoundation.com\/&#8221; url_new_window=&#8221;on&#8221; button_text=&#8221;Offer Price&#8221; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; custom_button=&#8221;on&#8221; button_text_color=&#8221;#0C71C3&#8243; button_bg_color=&#8221;#FFFFFF&#8221; button_font=&#8221;|700|||||||&#8221; transform_translate=&#8221;64px|65px&#8221; transform_translate_linked=&#8221;off&#8221;][\/et_pb_button][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2019\/06\/logo_resize_color.png&#8221; title_text=&#8221;logo_resize_color&#8221; _builder_version=&#8221;4.9.7&#8243; _module_preset=&#8221;default&#8221; transform_translate=&#8221;-36px|0px&#8221; transform_translate_linked=&#8221;off&#8221; custom_margin=&#8221;|||178px||&#8221;][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.9.7&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_team_member name=&#8221;Sai Susmitha&#8221; position=&#8221;Author&#8221; image_url=&#8221;https:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2025\/03\/Sai-Susmitha.png&#8221; _builder_version=&#8221;4.9.7&#8243; header_level=&#8221;h5&#8243; header_font=&#8221;Titillium Web|700|||||||&#8221; body_font=&#8221;Titillium Web||||||||&#8221; body_font_size=&#8221;16&#8243;]<\/p>\n<p>The Journey of Personal Development is a Continuous path of learning and growth.<\/p>\n<p>[\/et_pb_team_member][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.9.7&#8243;][et_pb_row _builder_version=&#8221;4.9.7&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_post_title meta=&#8221;off&#8221; featured_image=&#8221;off&#8221; _builder_version=&#8221;4.9.7&#8243; title_font=&#8221;Times New Roman||||||||&#8221; title_text_align=&#8221;left&#8221; title_text_color=&#8221;#000000&#8243; title_font_size=&#8221;47&#8243; background_color=&#8221;RGBA(0,0,0,0)&#8221; background_enable_image=&#8221;off&#8221; custom_margin=&#8221;|||10%&#8221; title_font_size_tablet=&#8221;40&#8243; title_font_size_phone=&#8221;35&#8243; title_font_size_last_edited=&#8221;on|desktop&#8221;][\/et_pb_post_title][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.9.7&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.9.7&#8243; text_font=&#8221;Georgia||||||||&#8221; text_text_color=&#8221;#000000&#8243; text_font_size=&#8221;22px&#8221; text_line_height=&#8221;1.9em&#8221; max_width=&#8221;800px&#8221; max_width_last_edited=&#8221;off|phone&#8221; custom_margin=&#8221;|||10%&#8221; custom_margin_last_edited=&#8221;off|desktop&#8221; text_font_size_tablet=&#8221;&#8221; text_font_size_phone=&#8221;&#8221; text_font_size_last_edited=&#8221;on|phone&#8221; text_line_height_last_edited=&#8221;off|phone&#8221;] Introduction to Spark Framework Spark Framework is an [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":93763,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"2880","footnotes":""},"categories":[1],"tags":[],"class_list":{"0":"post-93711","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-uncategorized"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Spark SQL Tutorial<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Spark SQL Tutorial\" 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Framework is an [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/\" \/>\n<meta property=\"og:site_name\" content=\"CloudFoundation | Blog\" \/>\n<meta property=\"article:published_time\" content=\"2025-03-19T09:24:27+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-02-04T09:36:29+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/cloudfoundation.com\/blog\/wp-content\/uploads\/2025\/03\/SparkSQL-FI.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"500\" \/>\n\t<meta property=\"og:image:height\" content=\"283\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"NAGENDRAG\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"NAGENDRAG\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Spark SQL Tutorial","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/cloudfoundation.com\/blog\/spark-sql-tutorial\/","og_locale":"en_US","og_type":"article","og_title":"Spark SQL Tutorial","og_description":"[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.9.7&#8243;][et_pb_row _builder_version=&#8221;4.9.7&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_post_title meta=&#8221;off&#8221; featured_image=&#8221;off&#8221; _builder_version=&#8221;4.9.7&#8243; title_font=&#8221;Times New 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