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Hadoop Basic Interview Questions and Answers Part-5

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hadoop41. Do we need to give a password, even if the key is added in SSH?

Yes, password is still required even if the key is added in SSH.

42. What if a Namenode has no data?

If a Namenode has no data it is not a Namenode. Practically, Namenode will have some data.

43. What happens to job tracker when Namenode is down?

When Namenode is down, your cluster is OFF, this is because Namenode is the single point of failure in HDFS.

44. What happens to a Namenode, when job tracker is down?

When a job tracker is down, it will not be functional but Namenode will be present. So, cluster is accessible if Namenode is working, even if the job tracker is not working.

45. Can you give us some more details about SSH communication between Masters and the Slaves?

SSH is a password-less secure communication where data packets are sent across the slave. It has some format into which data is sent across. SSH is not only between masters and slaves but also between two hosts.

46. What is formatting of the DFS?

Just like we do for Windows, DFS is formatted for proper structuring. It is not usually done as it formats the Namenode too.

47. Does the HDFS client decide the input split or Namenode?

No, the Client does not decide. It is already specified in one of the configurations through which input split is already configured.

48. In Cloudera there is already a cluster, but if I want to form a cluster on Ubuntu can we do it?

Yes, you can go ahead with this! There are installation steps for creating a new cluster. You can uninstall your present cluster and install the new cluster.

49. Can we create a Hadoop cluster from scratch?

Yes we can do that also once we are familiar with the Hadoop environment.

50. Can we use Windows for Hadoop?

Actually, Red Hat Linux or Ubuntu are the best Operating Systems for Hadoop. Windows is not used frequently for installing Hadoop as there are many support problems attached with Windows. Thus, Windows is not a preferred environment for Hadoop.

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