The correct answer is: C. Executed
HDFS (Hadoop Distributed File System) is a distributed file system designed to store large amounts of data across commodity servers. It is a key component of the Hadoop ecosystem, which is used for big data processing and analytics.
HDFS files are stored in blocks, which are replicated across multiple nodes in the cluster. This ensures that data is available even if some of the nodes fail.
HDFS files can be read, written, and deleted. However, they cannot be executed. This is because HDFS is a file system, not an execution environment.
If you need to execute a file, you can use a Hadoop application such as MapReduce or Spark. These applications can read data from HDFS and write the results to HDFS. However, they cannot execute files directly.
Here is a brief explanation of each option:
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A. Read
HDFS files can be read by any application that can access the HDFS filesystem. This includes Hadoop applications such as MapReduce and Spark, as well as other applications that can connect to HDFS using the Hadoop Distributed File System API. -
B. Deleted
HDFS files can be deleted by any application that has permission to delete files from the HDFS filesystem. This includes Hadoop applications such as MapReduce and Spark, as well as other applications that can connect to HDFS using the Hadoop Distributed File System API. -
C. Executed
HDFS files cannot be executed. This is because HDFS is a file system, not an execution environment. If you need to execute a file, you can use a Hadoop application such as MapReduce or Spark. These applications can read data from HDFS and write the results to HDFS. However, they cannot execute files directly. -
D. Archived
HDFS files can be archived using the Hadoop Archive (HArchive) tool. HArchive is a tool that can be used to create archives of HDFS files. These archives can then be stored on HDFS or on another file system.