{"id":2172,"date":"2017-04-21T12:16:01","date_gmt":"2017-04-21T12:16:01","guid":{"rendered":"http:\/\/data-flair.training\/blogs\/?p=2172"},"modified":"2018-11-20T15:04:14","modified_gmt":"2018-11-20T09:34:14","slug":"hadoop-inputformat","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/hadoop-inputformat\/","title":{"rendered":"Hadoop InputFormat, Types of InputFormat in MapReduce"},"content":{"rendered":"<h2>1. Objective<\/h2>\n<p><a href=\"http:\/\/data-flair.training\/blogs\/hadoop-tutorial-for-beginners\/\"><strong>Hadoop<\/strong><\/a> InputFormat checks the Input-Specification of the job. InputFormat split the Input file into InputSplit and assign to individual Mapper.\u00a0In this Hadoop InputFormat Tutorial, we will learn what is InputFormat in Hadoop <a href=\"http:\/\/data-flair.training\/blogs\/hadoop-mapreduce-tutorial\/\"><strong>MapReduce<\/strong><\/a>, different methods to get the data to the mapper and different types of InputFormat in Hadoop like FileInputFormat in Hadoop, TextInputFormat, KeyValueTextInputFormat, etc. We will also see what is the default InputFormat in Hadoop?<\/p>\n<div id=\"attachment_42945\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-42945\" class=\"size-full wp-image-42945\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1.jpg\" alt=\"Hadoop InputFormat, Types of InputFormat in MapReduce\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1-1024x536.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/04\/hadoop-inputformat-introduction-1-520x272.jpg 520w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-42945\" class=\"wp-caption-text\">Hadoop InputFormat, Types of InputFormat in MapReduce<\/p><\/div>\n<h2>2. What is Hadoop InputFormat?<\/h2>\n<p>How the input files are split up and read in Hadoop is defined by the InputFormat. An Hadoop InputFormat is the first component in Map-Reduce, it is responsible for creating the input splits and dividing them into records. If you are not familiar with MapReduce Job Flow, so follow our <a href=\"http:\/\/data-flair.training\/blogs\/how-hadoop-mapreduce-works\/\"><strong>Hadoop MapReduce Data flow tutorial<\/strong><\/a> for more understanding.<\/p>\n<p>Initially, the data for a MapReduce task is stored in input files, and input files typically reside in <a href=\"http:\/\/data-flair.training\/blogs\/comprehensive-hdfs-guide-introduction-architecture-data-read-write-tutorial\/\"><strong>HDFS<\/strong><\/a>. Although these files format is arbitrary, line-based log files and binary format can be used. Using InputFormat we define how these input files are split and read. The InputFormat class is one of the fundamental classes in the Hadoop MapReduce framework which provides the following functionality:<\/p>\n<ul>\n<li>The files or other objects that should be used for input is selected by the InputFormat.<\/li>\n<li>InputFormat defines the Data splits, which defines both the size of individual<strong> <a href=\"http:\/\/data-flair.training\/blogs\/mapper-in-hadoop-mapreduce\/\">Map tasks <\/a><\/strong>and its potential execution server.<\/li>\n<li>InputFormat defines the <a href=\"http:\/\/data-flair.training\/blogs\/recordreader-in-hadoop-mapreduce\/\"><strong>RecordReader<\/strong><\/a>, which is responsible for reading actual records from the input files.<\/li>\n<\/ul>\n<h2>3. How we get the data to mapper?<\/h2>\n<p>We have 2 methods to get the data to<a href=\"http:\/\/data-flair.training\/blogs\/mapper-in-hadoop-mapreduce\/\"><strong> mapper<\/strong><\/a> in MapReduce: getsplits() and createRecordReader() as shown below:<\/p>\n<p>[php]public abstract class InputFormat&lt;K, V&gt;<br \/>\n{<br \/>\npublic abstract List&lt;InputSplit&gt; getSplits(JobContext context)<br \/>\nthrows IOException, InterruptedException;<br \/>\npublic abstract RecordReader&lt;K, V&gt;<br \/>\ncreateRecordReader(InputSplit split,<br \/>\nTaskAttemptContext context) throws IOException,<br \/>\nInterruptedException;<br \/>\n}[\/php]<\/p>\n<h2>4. Types of InputFormat in MapReduce<\/h2>\n<div id=\"attachment_4150\" style=\"width: 3352px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/types-of-inputformat-in-mapreduce.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-4150\" class=\"wp-image-4150 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/types-of-inputformat-in-mapreduce.jpg\" alt=\"Different Types of InputFormats in Hadoop MapReduce\" width=\"3342\" height=\"1750\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/types-of-inputformat-in-mapreduce.jpg 3342w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/types-of-inputformat-in-mapreduce-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/types-of-inputformat-in-mapreduce-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/types-of-inputformat-in-mapreduce-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/types-of-inputformat-in-mapreduce-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 3342px) 100vw, 3342px\" \/><\/a><p id=\"caption-attachment-4150\" class=\"wp-caption-text\">Types of InputFormat<\/p><\/div>\n<p>Let us now see what are the types of InputFormat in Hadoop?<\/p>\n<h3>4.1. FileInputFormat in Hadoop<\/h3>\n<p>It is the base class for all file-based InputFormats. Hadoop FileInputFormat specifies input directory where data files are located. When we start a Hadoop job, FileInputFormat is provided with a path containing files to read. FileInputFormat will read all files and divides these files into one or more InputSplits.<\/p>\n<h3>4.2. TextInputFormat<\/h3>\n<p>It is the default InputFormat of MapReduce. TextInputFormat treats each line of each input file as a separate record and performs no parsing. This is useful for unformatted data or line-based records like log files.<\/p>\n<ul>\n<li><strong>Key &#8211;\u00a0<\/strong>It is the byte offset of the beginning of the line within the file (not whole file just one split), so it will be unique if combined with the file name.<\/li>\n<li><strong>Value &#8211;\u00a0<\/strong>It is the contents of the line, excluding line terminators.<\/li>\n<\/ul>\n<h3>4.3. KeyValueTextInputFormat<\/h3>\n<p>It is similar to TextInputFormat as it also treats each line of input as a separate record. While TextInputFormat treats entire line as the value, but the KeyValueTextInputFormat breaks the line itself into key and value by a tab character (\u2018\/t\u2019). Here Key is everything up to the tab character while the value is the remaining part of the line after tab character.<\/p>\n<h3>4.4. SequenceFileInputFormat<\/h3>\n<p>Hadoop <strong>SequenceFileInputForma<\/strong>t is an InputFormat which reads sequence files. Sequence files are binary files that stores sequences of binary<a href=\"http:\/\/data-flair.training\/blogs\/key-value-pairs-hadoop-mapreduce\/\"><strong> key-value pairs<\/strong><\/a>. Sequence files block-compress and provide direct serialization and deserialization of several arbitrary data types (not just text). Here Key &amp; Value both are user-defined.<\/p>\n<h3>4.5. SequenceFileAsTextInputFormat<\/h3>\n<p>Hadoop <strong>SequenceFileAsTextInputFormat<\/strong> is another form of SequenceFileInputFormat which converts the sequence file key values to Text objects. By calling <strong>\u2018tostring()\u2019<\/strong> conversion is performed on the keys and values. This InputFormat makes sequence files suitable input for streaming.<\/p>\n<h3>4.6. SequenceFileAsBinaryInputFormat<\/h3>\n<p>Hadoop <strong>SequenceFileAsBinaryInputFormat<\/strong>\u00a0is a SequenceFileInputFormat using which we can extract the sequence file\u2019s keys and values as an opaque binary object.<\/p>\n<h3>4.7. NLineInputFormat<\/h3>\n<p>Hadoop <strong>NLineInputFormat<\/strong> is another form of TextInputFormat where the keys are byte offset of the line and values are contents of the line. Each mapper receives a variable number of lines of input with TextInputFormat and KeyValueTextInputFormat and the number depends on the size of the split and the length of the lines. And if we want our mapper to receive a fixed number of lines of input, then we use NLineInputFormat.<br \/>\nN is the number of lines of input that each mapper receives. By default (N=1), each mapper receives exactly one line of input. If N=2, then each split contains two lines. One mapper will receive the first two Key-Value pairs and another mapper will receive the second two key-value pairs.<\/p>\n<h3>4.8. DBInputFormat<\/h3>\n<p>Hadoop <strong>DBInputFormat<\/strong> is an InputFormat that reads data from a relational database, using JDBC. As it doesn\u2019t have portioning capabilities, so we need to careful not to swamp the database from which we are reading too many mappers. So it is best for loading relatively small datasets, perhaps for joining with large datasets from HDFS using MultipleInputs. Here Key is LongWritables while Value is DBWritables.<\/p>\n<h2>5. Conclusion<\/h2>\n<p>In conclusion, we can say that InputFormat defines how to split and read input files. InputFormat defines RecordReader. One can also use different types of InputFormats for the different purpose. In our next blog, we will discuss<a href=\"http:\/\/data-flair.training\/blogs\/outputformat-recordwriter-hadoop-mapreduce\/\"> OutputFormat in Hadoop mapReduce<\/a> in detail. Hope this blog helped you to understand the MapReduce concepts.<br \/>\nIf you have any doubts in Hadoop InputFormat, so feel free to share with us. We will be glad to solve your queries.<br \/>\n<strong>See Also-<\/strong><\/p>\n<ul>\n<li><a href=\"http:\/\/data-flair.training\/blogs\/counters-hadoop-mapreduce\/\">Counter in Hadoop Mapreduce<\/a><\/li>\n<li><a href=\"http:\/\/data-flair.training\/blogs\/shuffling-sorting-hadoop-mapreduce\/\">Shuffling and Sorting in MapReduce<\/a><\/li>\n<\/ul>\n<p><a href=\"https:\/\/hadoop.apache.org\/docs\/r2.7.2\/api\/org\/apache\/hadoop\/mapred\/InputFormat.html\">Reference<\/a><span hidden class=\"__iawmlf-post-loop-links\" 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04:39:04&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-12 14:12:27&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-19 06:04:47&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-22 06:52:10&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-25 14:48:23&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-01-28 15:43:49&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-04 22:20:20&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-11 08:16:26&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-14 11:13:20&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-17 23:50:24&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-22 17:26:31&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-02-26 06:27:41&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-01 14:56:18&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-05 09:42:26&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-08 16:22:19&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-12 09:01:47&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-16 07:32:21&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-19 14:21:31&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-23 02:40:14&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-03-26 13:35:24&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-01 18:17:44&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-05 13:43:27&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-08 17:51:49&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-14 21:19:23&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-19 07:38:00&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-24 14:17:31&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-04-29 16:32:43&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-03 10:34:22&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-09 12:41:16&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-13 09:08:54&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-18 01:58:19&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-21 23:05:01&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-28 07:10:22&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-05-31 07:50:30&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-05 11:51:08&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-08 12:50:55&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-15 03:00:58&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-24 11:33:57&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-06-29 05:54:47&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2026-07-03 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Objective Hadoop InputFormat checks the Input-Specification of the job. InputFormat split the Input file into InputSplit and assign to individual Mapper.\u00a0In this Hadoop InputFormat Tutorial, we will learn what is InputFormat in Hadoop&#46;&#46;&#46;<\/p>\n","protected":false},"author":6,"featured_media":42945,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[37],"tags":[4688,5265,6732,6733,6734,8545],"class_list":["post-2172","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-mapreduce","tag-fileinputformat","tag-hadoop-inputformats","tag-inputformat-in-hadoop","tag-inputformats-in-hadoop","tag-inputformats-in-mapreduce","tag-mapreduce-inputformats"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Hadoop InputFormat, Types of InputFormat in MapReduce - DataFlair<\/title>\n<meta name=\"description\" content=\"Hadoop InputFormat tutorial cover what is Inputformat in mapReduce,types of InputFormat in MapReduce,FileInputFormat,TextInputFormat,KeyValueTextInputFormat\" \/>\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\/hadoop-inputformat\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hadoop InputFormat, Types of InputFormat in MapReduce - 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