I have an EAR and I am deploying it in a WAS cluster. WAS version is 7. I want this to be an Active/Passive cluster.
I am wondering how can I make sure that only one node is started at a time? And how to instuct WAS to start up the second node in case the first one crashes?
I don't know of a way to control the entire "node" as described, but you can insure that only one "Server" (aka JVM) is running for the cluster.
Expand Server > expand Clusters > click, Dynamic clusters > click on [your cluster]
A few sections down on this config page you'll see the section, Maximum number of cluster instances
A. Select, "Limit the number of instances that can start" and fill in "1".
Also make sure that your cluster membership policy includes multiple nodes (you can verify this by clicking "preview membership".)
There is no such topology in WAS.
There is way to create backup Cell.
If main cell is crushed, backup cell will be active.
Related
I have a cluster with 3 nodes - say cluster1 on AWS EC2 instances. The cluster is up and running, took snapshot of the keyspace's volume.
Now I want to restore few tables/keyspaces from the snapshot volumes, so I created another cluster say cluster2 and attached the snapshot volumes on to the new cluster's ec2 nodes (same number of nodes). Cluster2 is not starting bcz the system keyspace in the snapshot taken was having cluster name as cluster1 and the cluster on which it is being restored is cluster2. How do I do a restore in this case? I do not want to do any modifications to the existing cluster.
Also when I do restore do I need to think about the token ranges of the old and new cluster's mapping?
Before starting the cluster2, it's important to ensure that none of the IP addresses of the cluster1 are included in the seed list of the cluster2 to ensure that they are kept unaware between them. Also, to remove from the path data_file_directories (as defined in the cassandra.yaml), the following directories:
system
system_auth
system_distributed
system_traces
system_schema should not be touched, as it contains the schema definition of the keyspaces and tables.
Start the cluster, one node at a time; the first node should include its own IP address at the beginning of the seed list; This will be a one time change, and the change should be removed once that the cluster is up and running.
At this moment you should have a separate cluster, with the information and structure of the original cluster at the time that the snapshot was taken. To test this, execute nodetool gossipinfo and only the nodes of the cluster2 should be listed, login into cqlsh describe keyspaces should list all your keyspaces, and executing queries of your application should retrieve your data. You will note that Cassandra already generated the system* keyspaces, as well as dealt with the token distribution.
The next step is to update the name of the restored cluster, in each one of the nodes:
Log into cqlsh
Execute UPDATE system.local SET cluster_name = 'cluster2' where key='local';
exit cqlsh
run nodetool flush
run nodetool drain
edit the cassandra.yaml file, update cluster_name with the name 'cluster2'
restart the cassandra service
wait until the node is reported as NORMAL with nodetool status or nodetool netstats
repeat with a different node
At this point you will have 2 independent clusters, with different name.
I have a clustered nifi setup and we are running GetMongo processor with the Primary mode on, so that duplicate data is not fetched. This seems to be working fine. However once I have this data I want the following processes in the chain to run on a cluster, as in parallel processing to be done on this data which has been fetched. Somehow this is not happening. So my question is below assuming GetMongo has fetched 30000 records and they are in the queue:
1) How do I check whether a processor is running its process on a single node or on all nodes. The config has been set to all nodes, but when the processor is running I see it displays 1 in the top right corner.
2) If one processor has been set to run only on primary node, do all other processors in the flow also run on Primary mode?
Example:
In the screenshot above, my getmongo is running in primary node, how do I make sure that the execute script processor runs in parallel on all 3 nifi nodes. As of now if I check the view status history in the executescript process I see data flowing only through the primary node.
Yes, that's correct. When you mark the source processor to run only the Primary Node, all the subsequent steps will only happen on that node alone since the data is residing only that node (primary node), even when you have the NiFi in a clustered mode. To make it work the way you want, you can follow either of the following two approaches:
Approach #1 : Comibination of RPG and Site-To-Site
Here your flow will look like this:
Create an Input Port on the Root Group (the very top level of the NiFi canvas)
Make GetMongo run only on Primary Node.
Connect the success relationship of the processor to a Remote Processor Group (RPG). This RPG can be configured with the cluster details itself and configure it to connect to the port you added in step #1.
From the input port, connect it to your processing logic.
Useful Links:
https://pierrevillard.com/2017/02/23/listfetch-pattern-and-remote-process-group-in-apache-nifi/
This is cumbersome and would make your flow very complex but this how it has to be done, till NiFi 1.8. With NiFi 1.8, you can use the following approach.
Approach #2 : Load-Balanced Connections (Apache NiFi 1.8+)
Apache NiFi had a new release - 1.8, a week ago. With this release, there is a new feature (a long time coming and very much desired one) was introduced. It is called Load-Balanced Connections.
In this approach, you can simply ignore the RPG/Site-To-Site combination and rather do the following:
Connect the output of your source processor, in this case GetMongo with the subsequent processors.
Right click the success relationship of the source processor.
Click configure
Go to Settings tab
Set the Load Balance Strategy to the desired one, preferably Roudd robin in your case.
Useful Links:
https://blogs.apache.org/nifi/entry/load-balancing-across-the-cluster
https://pierrevillard.com/2018/10/29/nifi-1-8-revolutionizing-the-list-fetch-pattern-and-more/
I have a 3 node nifi cluster, using embedded Zookeeper. Now I need to add a new node to the cluster. What is the procedure for the same?
Will I have to bring down all the nodes, since I need to add an entry to the /nifi/conf/zookeeper.conf(server=) and also to the list of zookeeper servers in /nifi/conf/nifi.properties(nifi.zookeeper.connect.string). As far as I understand, these both will have to be edited on the existing 3 as well as the new box. But dont think this is the right way, since each time the cluster will have to be brought down. Can someone please help out?
Usually you would have three or five ZooKeeper nodes, so if you already have three then you don't really need to add a fourth. You could add another NiFi node that uses the existing embedded ZooKeepers on the other nodes.
Is it possible to specify on which nodes to run specific mapper jobs?
Have distributed data on nodes and want to run jobs on the nodes containing that data
I'm not sure there's a reliable way to make sure a map task runs on a specific node. You can create a custom InputFormat and override InputFormat.getLocations() to return only the host name of the node you want that split to run on. However, these locations are merely suggestions to the MR framework and it can choose to ignore them.
Apache Hadoop out of the box doesn't support it. But, this feature is supported in MapR distribution (1).
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
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.*
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.
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
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.