Hadoop Datanode, namenode, secondary-namenode, job-tracker and task-tracker

Question

I am new in hadoop so I have some doubts. If the master-node fails what happened the hadoop cluster? Can we recover that node without any loss? Is it possible to keep a secondary master-node to switch automatically to the master when the current one fails?

We have the backup of the namenode (Secondary namenode), so we can restore the namenode from Secondary namenode when it fails. Like this, How can we restore the data's in datanode when the datanode fails? The secondary namenode is the backup of namenode only not to datenode, right? If a node is failed before completion of a job, so there is job pending in job tracker, is that job continue or restart from the first in the free node?

How can we restore the entire cluster data if anything happens?

And my final question, can we use C program in Mapreduce (For example, Bubble sort in mapreduce)?

Thanks in advance

Answer 1

Although, It is too late to answer your question but just It may help others..

First of all let me Introduce you with Secondary Name Node:

It Contains the name space image, edit log files' back up for past one hour (configurable). And its work is to merge latest Name Node NameSpaceImage and edit logs files to upload back to Name Node as replacement of the old one. To have a Secondary NN in a cluster is not mandatory.

Now coming to your concerns..

• If the master-node fails what happened the hadoop cluster?

Supporting Frail's answer, Yes hadoop has single point of failure so whole of your currently running task like Map-Reduce or any other that is using the failed master node will stop. The whole cluster including client will stop working.

• Can we recover that node without any loss?

That is hypothetical, Without loss it is least possible, as all the data (block reports) will lost which has sent by Data nodes to Name node after last back up taken by secondary name node. Why I mentioned least, because If name node fails just after a successful back up run by secondary name node then it is in safe state.

• Is it possible to keep a secondary master-node to switch automatically to the master when the current one fails?

It is staright possible by an Administrator (User). And to switch it automatically you have to write a native code out of the cluster, Code to moniter the cluster that will cofigure the secondary name node smartly and restart the cluster with new name node address.

• We have the backup of the namenode (Secondary namenode), so we can restore the namenode from Secondary namenode when it fails. Like this, How can we restore the data's in datanode when the datanode fails?

It is about replication factor, We have 3 (default as best practice, configurable) replicas of each file block all in different data nodes. So in case of failure for time being we have 2 back up data nodes. Later Name node will create one more replica of the data that failed data node contained.

• The secondary namenode is the backup of namenode only not to datenode, right?

Right. It just contains all the metadata of data nodes like data node address,properties including block report of each data node.

• If a node is failed before completion of a job, so there is job pending in job tracker, is that job continue or restart from the first in the free node?

HDFS will forcely try to continue the job. But again it depends on replication factor, rack awareness and other configuration made by admin. But if following Hadoop's best practices about HDFS then it will not get failed. JobTracker will get replicated node address to continnue.

• How can we restore the entire cluster data if anything happens?

By Restarting it.

• And my final question, can we use C program in Mapreduce (For example, Bubble sort in mapreduce)?

yes, you can use any programming language which support Standard file read write operations.

I Just gave a try. Hope it will help you as well as others.

*Suggestions/Improvements are welcome.*

Answer 2

Currently hadoop cluster has a single point of failure which is namenode.

And about the secondary node isssue (from apache wiki) :

The term "secondary name-node" is somewhat misleading. It is not a name-node in the sense that data-nodes cannot connect to the secondary name-node, and in no event it can replace the primary name-node in case of its failure.

The only purpose of the secondary name-node is to perform periodic checkpoints. The secondary name-node periodically downloads current name-node image and edits log files, joins them into new image and uploads the new image back to the (primary and the only) name-node. See User Guide.

So if the name-node fails and you can restart it on the same physical node then there is no need to shutdown data-nodes, just the name-node need to be restarted. If you cannot use the old node anymore you will need to copy the latest image somewhere else. The latest image can be found either on the node that used to be the primary before failure if available; or on the secondary name-node. The latter will be the latest checkpoint without subsequent edits logs, that is the most recent name space modifications may be missing there. You will also need to restart the whole cluster in this case.

There are tricky ways to overcome this single point of failure. If you are using cloudera distribution, one of the ways explained here. Mapr distribution has a different way to handle to this spof.

Finally, you can use every single programing language to write map reduce over hadoop streaming.

Answer 3

Although, It is too late to answer your question but just It may help others..firstly we will discuss role of Hadoop 1.X daemons and then your issues..

1. What is role of secondary name Node it is not exactly a backup node. it reads a edit logs and create updated fsimage file for name node periodically. it get metadata from name node periodically and keep it and uses when name node fails. 2. what is role of name node it is manager of all daemons. its master jvm proceess which run at master node. it interact with data nodes.

3. what is role of job tracker it accepts job and distributes to task trackers for processing at data nodes. its called as map process

4. what is role of task trackers it will execute program provided for processing on existing data at data node. that process is called as map.

limitations of hadoop 1.X

1. single point of failure which is name node so we can maintain high quality hardware for the name node. if name node fails everything will be inaccessible

Solutions solution to single point of failure is hadoop 2.X which provides high availability.

high availability with hadoop 2.X

now your topics ....

How can we restore the entire cluster data if anything happens? if cluster fails we can restart it..

If a node is failed before completion of a job, so there is job pending in job tracker, is that job continue or restart from the first in the free node? we have default 3 replicas of data(i mean blocks) to get high availability it depends upon admin that how much replicas he has set...so job trackers will continue with other copy of data on other data node

can we use C program in Mapreduce (For example, Bubble sort in mapreduce)? basically mapreduce is execution engine which will solve or process big data problem in(storage plus processing) distributed manners. we are doing file handling and all other basic operations using mapreduce programming so we can use any language of where we can handle files as per the requirements.

hadoop 1.X architecture hadoop 1.x has 4 basic daemons

I Just gave a try. Hope it will help you as well as others.

Suggestions/Improvements are welcome.