What is HDFS?
HDFS, or Hadoop Distributed File System, is a distributed file system that runs on commodity hardware. HDFS, or Hadoop Distributed File System, is a distributed file system that runs on commodity hardware. It has a lot in common with other distributed file systems. However, there are considerable distinctions between it and other distributed file systems. HDFS is meant to run on low-cost hardware and is highly fault-tolerant. HDFS is a file system that allows high-throughput access to application data and is well-suited to applications with huge data collections.
What is the difference between Federation and High Availability in HDFS?
MapReduce may launch numerous HDFS namespaces in the cluster using HDFS federation, keep track of their health, and fail over in the event of a daemon or host failure. Running on different hosts, namespaces are independent and do not need to coordinate with one another.
With the help of the HDFS NameNode High Availability feature, you can operate backup NameNodes in the same cluster in an Active/Passive configuration with a hot standby. As a result, the NameNode is no longer a single point of failure (SPOF) within the HDFS cluster.
HDFS Federation offers fault tolerance, so if one NameNode goes down, the data of the other NameNode won’t be impacted.
It takes two different machines (for Primary NN and Standby NN) to use HDFS High Availability. The primary NameNode will be configured first, followed by the standby NameNode on the other system.
What is a Data node?
HDFS is a distributed file system, and each machine is referred to as a Data-Node. Serving read and write requests from the file system’s customers is the responsibility of the DataNodes. Upon receiving a command from the NameNode, the DataNodes also carry out block creation, deletion, and replication. The NameNode and DataNode are software applications made to run on common computers.
What is a Namenode?
The master node in the Apache Hadoop HDFS Architecture, or NameNode, is responsible for managing and maintaining the blocks on the DataNodes (slave nodes). The File System Namespace is managed by NameNode, a very highly available server, which also maintains client access to files.
What does Namenode actually do?
The Name node’s job is to keep track of the metadata and monitor all of the Data nodes in the cluster.
What are the benefits of a secondary node?
The secondary name node isn’t a typical backup option. However, it aids in the backup of Name node metadata, which might be useful in the event of Name node failure or rebuild.
What is the Standalone mode?
This is the default mode. The Hadoop services are implemented using a single Java process and the local FileSystem. This means that HDFS is not really used and Standalone mode is primarily used for debugging. In standalone mode, you can use both input and output as a local file system.
What is the Pseudo-distributed mode?
All Hadoop services are implemented here using a single-node Hadoop configuration. The pseudo-distribute mode, which places the NameNode and DataNode on the same system, is sometimes known as a single-node cluster.
All of the Hadoop daemons will be active on a single node in pseudo-distributed mode. When testing and not having to worry about the resources or other people using them, this configuration is typically utilized.
What is the Fully-distributed mode?
Hadoop will be operating in this production mode with several nodes. Data will be split among numerous nodes in this case, with processing taking place on each node individually. In fully distributed Hadoop Mode, Master and Slave services will be executing on distinct nodes.
is HDFS fault-tolerant?
Yes. HDFS replicates data across many DataNodes, making it fault-tolerant. A block of data is duplicated by default on three DataNodes. Different DataNodes house the data chunks. The information can still be obtained from other DataNodes even if one node crashes.
Big Data and SQL 