- What metadata is stored on a DataNode when a block is written to it?
- What are some WebHDFS REST API related parameters in HDFS?
- Which NameNode is used when the primary NameNode fails?
- How does Hadoop work when a Datanode fails?
- Which files deal with small file problems?
- When a client contacts the NameNode for accessing a file that NameNode responds with?
- What happens if a Datanode fails during a HDFS write operation?
- What happens when NameNode fails?
- How does Hadoop MapReduce deal with node failures?
- What happens if secondary NameNode fails?
- What is the main problem faced while reading and writing data in parallel from multiple disks?
- Is it possible to provide multiple inputs to Hadoop?
- How does NameNode tackle Datanode failures and what will you do when NameNode is down?
- How do you recover NameNode if it is down?
- What happens when a MapReduce job is submitted?
- When a NameNode fails what action should be taken?
- What if master node fails in Hadoop?
- What happens when a user submits a Hadoop job when the NameNode is down?
- Does Hdfs allow a client to read a file that is already opened for writing?
What metadata is stored on a DataNode when a block is written to it?
It stores a file with the checksum of the blocks that it stored.
meta file in datanode will contain the checksum information for taht block which would be cross-checked when a client reads that block from datanode, if the checksum is not matched it throws an error..
What are some WebHDFS REST API related parameters in HDFS?
WebHDFS REST APIGet Content Summary of a Directory.Get File Checksum.Get Home Directory.Set Permission.Set Owner.Set Replication Factor.Set Access or Modification Time.
Which NameNode is used when the primary NameNode fails?
4. ________ NameNode is used when the Primary NameNode goes down. Explanation: Secondary namenode is used for all time availability and reliability.
How does Hadoop work when a Datanode fails?
What happens if one of the Datanodes gets failed in HDFS? Namenode periodically receives a heartbeat and a Block report from each Datanode in the cluster. Every Datanode sends heartbeat message after every 3 seconds to Namenode.
Which files deal with small file problems?
A HAR file is created using the hadoop archive command, which runs a MapReduce job to pack the files being archived into a small number of HDFS files. To a client using the HAR filesystem nothing has changed: all of the original files are visible and accessible (albeit using a har:// URL).
When a client contacts the NameNode for accessing a file that NameNode responds with?
When the local file accumulates data worth over one HDFS block size, the client contacts the NameNode. The NameNode inserts the file name into the file system hierarchy and allocates a data block for it. The NameNode responds to the client request with the identity of the DataNode and the destination data block.
What happens if a Datanode fails during a HDFS write operation?
The failed DataNode gets removed from the pipeline, and a new pipeline gets constructed from the two alive DataNodes. The remaining of the block’s data is then written to the alive DataNodes, added in the pipeline.
What happens when NameNode fails?
The single point of failure in Hadoop v1 is NameNode. If NameNode gets fail the whole Hadoop cluster will not work. Actually, there will not any data loss only the cluster work will be shut down, because NameNode is only the point of contact to all DataNodes and if the NameNode fails all communication will stop.
How does Hadoop MapReduce deal with node failures?
The Master must also inform each Reduce task that the location of its input from that Map task has changed. Dealing with a failure at the node of a Reduce worker is simpler. The Master simply sets the status of its currently executing Reduce tasks to idle. These will be rescheduled on another reduce worker later.
What happens if secondary NameNode fails?
If NameNode is failed, File System metadata can be recovered from the last saved FsImage on the Secondary NameNode but Secondary NameNode can’t take the primary NameNode’s functionality.
What is the main problem faced while reading and writing data in parallel from multiple disks?
Q 4 – What is the main problem faced while reading and writing data in parallel from multiple disks? A – Processing high volume of data faster.
Is it possible to provide multiple inputs to Hadoop?
Here Hadoop development experts will make you understand the concept of multiple input files required in Hadoop MapReduce. As a mapper extracts its input from the input file, if there are multiple input files, developers will require the same amount of mapper to read records from input files.
How does NameNode tackle Datanode failures and what will you do when NameNode is down?
This is how Namenode handles datanode failures. HDFS works in Master/Slave mode where NameNode act as a Master and DataNodes act as a Slave. NameNode periodically receives a Heartbeat and a Data Blocks report from each of the DataNodes in the cluster in an interval of specified time.
How do you recover NameNode if it is down?
Recover Hadoop NameNode FailureStart the namenode in a different host with a empty dfs. name. dir.Point the dfs. name. … Use –importCheckpoint option while starting namenode after pointing fs. checkpoint. … Change the fs.default.name to the backup host name URI and restart the cluster with all the slave IP’s in slaves file.
What happens when a MapReduce job is submitted?
A MapReduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner. The framework sorts the outputs of the maps, which are then input to the reduce tasks. Typically both the input and the output of the job are stored in a file-system.
When a NameNode fails what action should be taken?
Whenever the active NameNode fails, the passive NameNode or the standby NameNode replaces the active NameNode, to ensure that the Hadoop cluster is never without a NameNode. The passive NameNode takes over the responsibility of the failed NameNode and keep the HDFS up and running.
What if master node fails in Hadoop?
1. Namenode also known as Master node is the linchpin of Hadoop. If namenode fails, your cluster is officially lost. To avoid this scenario, you must configure standby namenode.
What happens when a user submits a Hadoop job when the NameNode is down?
By Hadoop job, you probably mean MapReduce job. If your NN is down, and you don’t have spare one (in HA setup) your HDFS will not be working and every component dependent on this HDFS namespace will be either stuck or crashed.
Does Hdfs allow a client to read a file that is already opened for writing?
Yes, the client can read the file which is already opened for writing.