{"id":5727,"date":"2018-01-16T14:13:59","date_gmt":"2018-01-16T14:13:59","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=5727"},"modified":"2018-09-18T10:39:58","modified_gmt":"2018-09-18T05:09:58","slug":"structured-streaming-in-sparkr","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/structured-streaming-in-sparkr\/","title":{"rendered":"Structured Streaming in SparkR &#8211; Example &amp; Programming Model"},"content":{"rendered":"<h2>1. Objective &#8211; SparkR Structured Streaming<\/h2>\n<p><span class=\"adverb\">Basically<\/span>, <a href=\"https:\/\/data-flair.training\/blogs\/category\/spark\/\"><strong>SparkR<\/strong><\/a> supports Structured Streaming API.\u00a0In this article, we will learn the whole concept of Structured Streaming in spark\u00a0<a href=\"https:\/\/data-flair.training\/blogs\/r-programming-tutorial\/\"><strong>R<\/strong>.<\/a> Moreover, we will\u00a0also learn the programming model for Structured Streaming, to understand it better. Also, we will see an example of Structured Streaming in SparkR.<\/p>\n<p>So, let&#8217;s start the Structured Streaming tutorial.<\/p>\n<div id=\"attachment_6334\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Structured-Streaming-in-R-01-2.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-6334\" class=\"wp-image-6334 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Structured-Streaming-in-R-01-2.jpg\" alt=\"Structured Streaming in SparkR\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Structured-Streaming-in-R-01-2.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Structured-Streaming-in-R-01-2-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Structured-Streaming-in-R-01-2-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Structured-Streaming-in-R-01-2-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Structured-Streaming-in-R-01-2-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-6334\" class=\"wp-caption-text\">Structured Streaming in SparkR &#8211; Example &amp; Programming Model<\/p><\/div>\n<h2>2. What is Structured Streaming in SparkR?<\/h2>\n<p><span style=\"font-weight: 400\"><span class=\"adverb\">Basically<\/span>, <em>SparkR supports Structured Streaming API<\/em>. <\/span><\/p>\n<ul>\n<li><span style=\"font-weight: 400\">It is built on the <a href=\"https:\/\/data-flair.training\/blogs\/spark-sql-tutorial\/\"><strong>Spark SQL<\/strong><\/a> engine, which is scalable and fault-tolerant in nature.\u00a0<\/span><\/li>\n<li><span style=\"font-weight: 400\">It helps to express streaming aggregations, event-time windows, stream-to-batch joins and many more. <\/span><\/li>\n<li><span style=\"font-weight: 400\">Here it executes computation on the same optimized Spark SQL engine.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Although, as same as we express a batch computation on static data. In the same way, we can express our streaming computation. We can use the <strong><a href=\"https:\/\/data-flair.training\/blogs\/apache-spark-dataset-tutorial\/\">Dataset<\/a>\/<a href=\"https:\/\/data-flair.training\/blogs\/apache-spark-sql-dataframe-tutorial\/\">DataFrame<\/a><\/strong> API in <a href=\"https:\/\/data-flair.training\/blogs\/why-you-should-learn-scala-introductory-tutorial\/\"><strong>Scala<\/strong><\/a>, Java, <a href=\"https:\/\/data-flair.training\/blogs\/python-tutorial-for-beginners\/\"><strong>Python<\/strong><\/a> or R as well.<\/span><\/p>\n<p><span style=\"font-weight: 400\">In addition, the system ensures end-to-end exactly-once. Also guarantees <a href=\"https:\/\/data-flair.training\/blogs\/fault-tolerance-in-apache-spark\/\"><strong>fault-tolerance<\/strong><\/a> through <a href=\"https:\/\/data-flair.training\/blogs\/apache-spark-streaming-checkpoint\/\"><strong>checkpointing<\/strong><\/a> and Write-Ahead Logs. Also, provides fast, scalable, fault-tolerant, end-to-end exactly-once stream processing without the user having to reason about <a href=\"https:\/\/data-flair.training\/blogs\/apache-spark-streaming-tutorial\/\"><strong>streaming<\/strong><\/a>.<\/span><\/p>\n<h2>a. Example of Spark Structured Streaming in R<\/h2>\n<p><span style=\"font-weight: 400\">Structured Streaming in SparkR example. If we want to maintain a running word count of text data received from a data server listening on a TCP socket. We can express this using Structured Streaming and create a local SparkSession, the starting point of all functionalities related to Spark.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">sparkR.session(appName = \"StructuredNetworkWordCount\")\r\n# Split the lines into words\r\nwords &lt;- selectExpr(lines, \"explode(split(value, ' ')) as word\")\r\n# Generate running word count\r\nwordCounts &lt;- count(group_by(words, \"word\"))<\/pre>\n<h2>3. Structure Streaming Programming Model In SparkR<\/h2>\n<p><span style=\"font-weight: 400\">In Structured Streaming, the key idea is to treat a live data stream as a table, that\u00a0appends continuously. Basically, it leads to a new stream processing model. However, it is very similar to a batch processing model. Also, can express our streaming computation as a standard batch-like query as on a static table. Moreover, Spark runs it as an incremental query on the unbounded input table. Furthermore, let\u2019s understand the detailed description of this model.<\/span><\/p>\n<div id=\"attachment_5740\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Programming-model-of-Structured-Streaming-1.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-5740\" class=\"wp-image-5740 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Programming-model-of-Structured-Streaming-1.jpg\" alt=\"Structured Streaming in SparkR\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Programming-model-of-Structured-Streaming-1.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Programming-model-of-Structured-Streaming-1-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Programming-model-of-Structured-Streaming-1-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Programming-model-of-Structured-Streaming-1-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Programming-model-of-Structured-Streaming-1-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-5740\" class=\"wp-caption-text\">Programming Model Of Structure Streaming in SparkR<\/p><\/div>\n<h3>a. Basic Concepts Spark\u00a0Structured Streaming<\/h3>\n<p><span style=\"font-weight: 400\">Let\u2019s consider the input data stream as the \u201cInput Table\u201d. Although, every data item that is arriving on the stream is like a new row being appended to the input table.<\/span><\/p>\n<h3>b. Stream as a Table<span style=\"font-weight: 400\"><br \/>\n<\/span><\/h3>\n<p><span style=\"font-weight: 400\">Basically, a query on the input will generate the \u201cResult Table\u201d. Moreover, every trigger interval (say, every 1 second), new rows get appended to the input table. Hence, it eventually updates the result table. Although,\u00a0the time when we update the result table,\u00a0it leads us to write the changed result rows to an external sink.<\/span><\/p>\n<h3>c. Model of\u00a0Structured Streaming<span style=\"font-weight: 400\"><br \/>\n<\/span><\/h3>\n<p><span style=\"font-weight: 400\">Basically, we can call an\u201cOutput\u201d is what we get written out to the external storage.<\/span>\u00a0Although, we can define the output in different modes, for example,\u00a0<span style=\"font-weight: 400\">Complete Mode, Append Mode, Update Mode. Let&#8217;s discuss all in detail.<\/span><\/p>\n<h4><span style=\"font-weight: 400\">i. Complete Mode\u00a0<\/span><\/h4>\n<p><span style=\"font-weight: 400\">When\u00a0updated result table will be written to the external storage, t<\/span>hat mode is Complete Mode. Although, it\u00a0depends on the storage connector only. That decides how to handle the writing of the entire table.<\/p>\n<h4><span style=\"font-weight: 400\">ii. Append Mode\u00a0<\/span><\/h4>\n<p><span style=\"font-weight: 400\">This is the mode where only the new rows appended to the result table since the last trigger. We will write those rows to the external storage.<\/span>\u00a0Basically, it is only applicable to the queries where existing rows in the result table are not expected to change.<span style=\"font-weight: 400\"><br \/>\n<\/span><\/p>\n<h4><span style=\"font-weight: 400\">iii. Update Mode\u00a0<\/span><\/h4>\n<p><span style=\"font-weight: 400\">In this mode, only the rows that were updated in the result table since the last trigger will be written to the external storage. It is available since Spark 2.1.1.<\/span>\u00a0It is very important to note that this is different from the complete mode. This mode only outputs the rows that have changed since the last trigger. Moreover, we can say if the query doesn\u2019t contain aggregations, it will be\u00a0as same as Append mode.<span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><span style=\"font-weight: 400\">In addition, it is significantly different from many other stream processing engines. Basically, the spark is responsible for updating the result table in this model.<\/span><\/p>\n<p>So, this was all in SparkR Structure Streaming. Hope you like our explanation.<\/p>\n<h2>4. Conclusion &#8211; Structured Streaming<\/h2>\n<p>Hence, in this article, we have learned the whole concept of Structured Streaming in SparkR. Also, we have discussed the whole programming model of Structured Streaming in R. Although if any query occurs, feel free to ask in the comment section.<\/p>\n<p><a href=\"https:\/\/spark.apache.org\/\">For reference<\/a>.<span hidden class=\"__iawmlf-post-loop-links\" data-iawmlf-links=\"[{&quot;id&quot;:2052,&quot;href&quot;:&quot;https:\\\/\\\/spark.apache.org&quot;,&quot;archived_href&quot;:&quot;http:\\\/\\\/web-wp.archive.org\\\/web\\\/20251009215151\\\/https:\\\/\\\/spark.apache.org\\\/&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[{&quot;date&quot;:&quot;2025-12-11 00:11:34&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2025-12-14 03:24:05&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2025-12-17 05:06:29&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2025-12-20 07:19:55&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2025-12-23 14:10:46&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2025-12-26 19:03:14&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2025-12-30 13:05:23&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-02 13:25:12&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-05 14:08:05&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-09 10:16:58&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-12 11:04:53&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-15 17:09:49&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-18 18:39:09&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-21 19:15:09&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-26 04:14:49&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-29 05:32:17&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-01 07:55:30&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-04 10:44:57&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-07 12:28:46&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-11 00:52:17&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-14 12:51:24&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-17 14:17:39&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-20 17:49:34&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-02-24 04:42:19&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-27 06:25:21&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-02 08:44:49&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-05 10:27:17&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-08 11:13:11&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-11 12:04:06&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-14 12:32:46&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-18 01:16:16&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-21 21:29:48&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-25 06:37:35&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-28 07:59:07&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-31 10:36:07&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-04 11:16:36&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-07 18:11:02&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-11 05:09:37&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-14 06:26:10&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-18 15:58:17&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-22 11:10:25&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-27 06:59:55&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-30 12:38:54&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-03 15:24:36&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-06 17:05:30&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-10 12:07:21&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-14 23:33:58&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-19 11:27:54&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-23 02:59:38&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-29 05:05:46&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-01 06:55:32&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-04 20:59:59&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-08 05:37:55&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-11 15:39:15&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-14 16:52:39&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-18 01:16:02&quot;,&quot;http_code&quot;:206}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-06-18 01:16:02&quot;,&quot;http_code&quot;:206},&quot;process&quot;:&quot;done&quot;}]\"><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>1. Objective &#8211; SparkR Structured Streaming Basically, SparkR supports Structured Streaming API.\u00a0In this article, we will learn the whole concept of Structured Streaming in spark\u00a0R. Moreover, we will\u00a0also learn the programming model for Structured&#46;&#46;&#46;<\/p>\n","protected":false},"author":6,"featured_media":6334,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[16601,13103,13136,13137,13947,16598,16599,16600],"class_list":["post-5727","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-spark","tag-example-of-spark-structured-streaming","tag-spark-r","tag-spark-structure-streaming","tag-spark-structured-streaming-in-r","tag-structure-streaming-in-sparkr","tag-structured-streaming","tag-structured-streaming-api","tag-structured-streaming-in-spark"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Structured Streaming in SparkR - Example &amp; Programming Model - DataFlair<\/title>\n<meta name=\"description\" content=\"Structured Streaming in SparkR- Example of Spark Structure streaming, Structure Streaming Programming Model In SparkR:Complete Mode,Append Mode, Update Mode\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/structured-streaming-in-sparkr\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Structured Streaming in SparkR - Example &amp; 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