How can we write or store data/file in Hadoop HDFS?
its same as how we keep/save data on Linux file system.
However HDFS is distributed file system. Data will be shared across cluster .
Copying data from Your Local System :-
HDFS follow Write once Read many models. So we cannot edit files already stored in HDFS, but we can append data by reopening the file. In Read-Write operation client first, interact with the NameNode. NameNode provides privileges so, the client can easily read and write data blocks into/from the respective datanodes.
To write a file in HDFS, a client needs to interact with master i.e. namenode (master). Namenode provides the address of the datanodes (slaves) on which client will start writing the data. Client can directly write data on the datanodes, now datanode will create data write pipeline.
The first datanode will copy the block to another datanode, which intern copy it to the third datanode. Once it creates the replicas of blocks, it sends back the acknowledgment.
HDFS Data Write Pipeline Workflow
a. The HDFS client sends a create request on DistributedFileSystem APIs.
b. DistributedFileSystem makes an RPC call to the namenode to create a new file in the file system’s namespace. The namenode performs various checks to make sure that the file doesn’t already exist and that the client has the permissions to create the file. When these checks pass, then only the namenode makes a record of the new file; otherwise, file creation fails and the client is thrown an IOException.
c. The DistributedFileSystem returns a FSDataOutputStream for the client to start writing data to. As the client writes data, DFSOutputStream splits it into packets, which it writes to an internal queue, called the data queue. The data queue is consumed by the DataStreamer, which is responsible for asking the namenode to allocate new blocks by picking a list of suitable datanodes to store the replicas.
d. The list of datanodes forms a pipeline, and based on replication factor (usually 3), there are three nodes in the pipeline. The DataStreamer streams the packets to the first datanode in the pipeline, which stores the packet and forwards it to the second datanode in the pipeline. Similarly, the second datanode stores the packet and forwards it to the third (and last) datanode in the pipeline.
e. DFSOutputStream also maintains an internal queue of packets that are waiting to be acknowledged by datanodes, called the ack queue. A packet is removed from the ack queue only when it has been acknowledged by the datanodes in the pipeline. Datanode sends the acknowledgment once required replicas are created (3 by default). Similarly, all the blocks are stored and replicated on the different datanodes, the data blocks are copied in parallel.
f. When the client has finished writing data, it calls close() on the stream.
g. This action flushes all the remaining packets to the datanode pipeline and waits for acknowledgments before contacting the namenode to signal that the file is complete. The namenode already knows which blocks the file is made up of, so it only has to wait for blocks to be minimally replicated before returning successfully.
Read here more on Data read-write operation