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The data in Hadoop is chunked into blocks of the size 128 MB, but is it the same for all kinds of data? What happens when we are running files of a smaller size?

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Technical Lead & Archiect - Azure & Databricks, Spark,Kafka,Snowflake,Scala,Pyspark,AWS Cloud,NoSQL

we can run small size of the data like 10KB also but recommended in Hadoop . 128MB is block size where data can be either lesser or max size also . Total Block = sizeofData/blocksize . This is the thumb rules. This is configurable size during hadoop cluster setup which can be 64MB,128MB or 256MB also...
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I prefer to think of the block size as a block limit, i.e., the biggest chunk of storage you want reserved for for your file. Note that this property can be set per file if you want — the type of data doesn’t matter. It’s a frequent misconception that a block in HDFS represents a fixed amount of storage...
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I prefer to think of the block size as a block limit, i.e., the biggest chunk of storage you want reserved for for your file. Note that this property can be set per file if you want — the type of data doesn’t matter. It’s a frequent misconception that a block in HDFS represents a fixed amount of storage space (it doesn’t). It merely sets the amount of storage that requires one unit of metadata to track it. An 8 KB file with a block size of 128 MB is not particularly different, from an HDFS standpoint, from a 126 MB file. They would be tracked at the same metadata cost by the NameNode. There aren’t many compelling reasons to keep small files around, however. Hadoop understands files largely as containers of data. So long as you have a kajillion files holding data with the same record structure — be it small graphics files, log entries or even structured records — you often have more reasons to merge them into a large file than keep them separate. read less
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