I am new to mesos.
After starting mesos-master, I tried to connect mesos-slave with the following command
/usr/sbin/mesos-slave --ip=192.192.7.180 --master=192.192.7.19:5050 --work_dir=/tmp/mesos/work/int --no-systemd_enable_support
It is not connecting to master. It is throwing the following error
No credentials provided. Attempting to register without authentication
Thank you in advance.
No credentials provided meaning you are trying to load a slave which is on a different network which is not configured in mesos config files.
once you register it then you can add it.
for the example sake try
for master
./bin/mesos-master.sh –ip=127.0.0.1 –work_dir=/var/lib/mesos
for slave
./bin/mesos-slave.sh –master=127.0.0.1:5050 –work_dir=/tmp/mesos –no-systemd_enable_support
open browser
localhost:5050
if all the steps are followed properly you should find a Mesos dashboard more details
Related
I am trying to connect to Cassandra cluster through Kerberos ticket cache with following set of configs -
java -Dcassaandra.ip.address=<IPaddress> \
-Djava.security.auth.login.config=kerb-client.conf \
-Dsun.security.krb5.debug=true \
-Djavax.security.auth.useSubjectCredsOnly=false \
-Djava.security.krb5.conf=krb5.conf -jar test-kerberos.jar
kerb-client.conf:
CassandraJavaClient {
com.sun.security.auth.module.Krb5LoginModule required useTicketCache=true ticketCache=cacheFile principal="abc#abc.net";
};
I am getting following error -
Unexpected error during transport initialization (java.lang.SecurityException: java.io.IOException: Configuration Error:
Line 3: expected [option value])
at com.datastax.driver.core.Connection$2.apply(Connection.java:205)
at com.datastax.driver.core.Connection$2.apply(Connection.java:191)
It seems like that there is some config missing but i am unable to identify the root cause.
Please advise on the corrective steps.
The Java driver needs to have a custom authenticator configured in order to authenticate using Kerberos.
Instaclustr has an open-source Kerberos authenticator for Cassandra that works with the Java driver. Details and code are available here:
Cassandra Kerberos authenticator
Java driver Kerberos plugin
Cheers!
Thanks for your reply. I am already using com.datastax.cassandra:cassandra-driver-core:3.5.1. Below is my sample code snippet.
Cluster cluster = Cluster.builder()
.addContactPoints(ipAddress)
.withAuthProvider(KerberosAuthProvider.builder().withSaslProperties(saslProperties).build())
.withSSL()
.build();
cluster.connect();
The issue got fixed after changing the ticketCache file name. It seems like that i was referring to incorrect cache file.Now, i seem to be getting something else - No valid credentials exception provided.
But i have moved ahead from basic configuration error.
I can confirm the 3-replica cluster of h2o inside K3s is correctly deployed, as executing in the Python3 interpreter h2o.init(ip="x.x.x.x") works as expected. I followed the instructions noted here: https://www.h2o.ai/blog/running-h2o-cluster-on-a-kubernetes-cluster/
Nevertheless, I had to modify the service.yaml and comment out the line which says clusterIP: None, as K3s was complaining about something related to its inability to set the clusterIP to None. But even though, I can certify it is working correctly, and I am able to use an external IP to connect to the cluster.
If I try to load the dataset using the h2o cluster inside the K3s cluster using the exact same steps as described here http://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html, this is the output that I get:
>>> train = h2o.import_file("https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv")
...
h2o.exceptions.H2OResponseError: Server error java.lang.IllegalArgumentException:
Error: Key not loaded: Key<Frame> https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv
Request: POST /3/ParseSetup
data: {'check_header': '0', 'source_frames': '["https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv"]'}
The same error occurs if I use the h2o.upoad_file("x.csv") method.
There is a clue about what may be happening here: Key not loaded: Key<Frame> while POSTing source frame through ParseSetup in H2O API call but I am not using curl, and I can not find any parameter that could help me overcome this issue: http://docs.h2o.ai/h2o/latest-stable/h2o-py/docs/h2o.html?highlight=import_file#h2o.import_file
I need to use the Python client inside the same K3s cluster due to different technical reasons, so I am not able to kick off nor Flow nor Firebug to know what may be happening.
I can confirm it is working correctly when I simply issue a h2o.init(), using the local Java instance.
UPDATE 1:
I have tried in different K3s clusters without success. I changed the service.yaml to a NodePort, and now this is the error traceback:
>>> train = h2o.import_file("https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv")
...
h2o.exceptions.H2OResponseError: Server error java.lang.IllegalArgumentException:
Error: Job is missing
Request: GET /3/Jobs/$03010a2a016132d4ffffffff$_a2366be93ec99a78d7bc161de8c54d67
UPDATE 2:
I have tried using different services (NodePort, LoadBalancer, ClusterIP) and none of them work. I also have tried using Minikube with the official image, and with a custom image made by me, without success. I suspect this is something related to either h2o itself, or the clustering between pods. I will keep digging and let's think there will be some gold in it.
UPDATE 3:
I also found out that the post about running H2O in Docker is really outdated https://www.h2o.ai/blog/h2o-docker/ nor is working the Dockerfile present at GitHub (I changed it to uncomment the ENTRYPOINT section without success): https://github.com/h2oai/h2o-3/blob/master/Dockerfile
Even though, I tried with the custom image I built for h2o-k8s and it is working seamlessly in pure Docker. I am wondering why it is still not working in K8s...
UPDATE 4:
I have tried modifying the environment variable called H2O_KUBERNETES_SERVICE_DNS without success.
In the meantime, the cluster started to be unavailable, that is, the readinessProbe's would not successfully complete. No matter what I change now, it does not work.
I spinned up a K3d cluster in local to see what happened, and surprisingly, the readinessProbe's were not failing, using v3.30.0.6. But now I started testing it with R instead of Python. I am glad I tried, because I may have pinpointed what was wrong. There is a version mismatch between the client and the server. So I updated accordingly the image to v3.30.0.1.
But now again, the readinessProbe is not working in my k3d cluster, so I am unable to test it.
It seems it is working now. R client version 3.30.0.1 with server version 3.30.0.1. Also tried with Python version 3.30.0.7 and server version 3.30.0.7 and it started working. Marvelous. The problem was caused by a version mismatch between the client and the server, as the python client was updated to 3.30.0.7 while the latest server for docker was 3.30.0.6.
While starting kudu-master, I am getting the below error and unable to start kudu cluster.
F0706 10:21:33.464331 27576 master_main.cc:71] Check failed: _s.ok() Bad status: Invalid argument: Unable to initialize catalog manager: Failed to initialize sys tables async: on-disk master list (hadoop-master:7051, slave2:7051, slave3:7051) and provided master list (:0) differ. Their symmetric difference is: :0, hadoop-master:7051, slave2:7051, slave3:7051
It is a cluster of 8 nodes and i have provided 3 masters as given below in master.gflagfile on master nodes.
--master_addresses=hadoop-master,slave2,slave3
TL;DR
If this is a new installation, working under the assumption that master ip addresses are correct, I believe the easiest solution is to
Stop kudu masters
Nuke the <kudu-data-dir>/master directory
Start kudu masters
Explanation
I believe the most common (if not only) cause of this error (Failed to initialize sys tables async: on-disk master list (hadoop-master:7051, slave2:7051, slave3:7051) and provided master list (:0) differ.) is when a kudu master node gets added incorrectly. The error suggests that kudu-master thinks it's running on a single node rather than 3-node cluster.
Maybe you did not intend to "add a node", but that's most likely what happened. I'm saying this because I had the same problem; after some googling and debugging, I discovered that during the installation, I started kudu-master before putting the correct IP address in master.gflagfile, so that kudu-master was spun up thinking it was running on a single node, not 3 node. Using steps above to clean install kudu-master again, my problem was solved.
I'm using EC2 Amazon Web Service to launch my server using NodeJS, MongoDB.
I completed to save and load the data using my android application through NodeJS server and MongoDB but when I tried to check the data using RoboMongo (Robo 3T), the error occurred.
Resource temporarily unavailable. Authentication by key (path of the .pem key) failed (Error -18). (Error #35)
Robomongo 1
Robomongo 2
Error dialog
This is what I did in Robomongo.
These are the result of searching the google... I think I did right...
What is wrong?
I Solved the problem myself.
When you have this problem,
1. Check out /etc/mongod.conf
In network interfaces.
bindIP must be 0.0.0.0
not 127.0.0.1
2. Check the SSH User Name.
For an Amazon Linux AMI, the user name is ec2-user.
For the others, Check out the link ! https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html
3. If it didn't help,
try to download what developer uploaded (1.2 - Beta)
https://github.com/Studio3T/robomongo/issues/1189#issuecomment-353279070
Hi I have configured prestodb with one coordinator and one worker.
when I run the worker I do get the message like
Discovery server connect succeeded for refresh (presto/general)
Discovery server connect succeeded for refresh (collector/general)
io.airlift.discovery.client.Announcer Discovery server connect succeeded for announce
however when I run a query it says worker not available.
also when I try to see if the below urls works
http://<master>/v1/service/presto/general - works ( i can see both nodes)
However when i use
http://<master>//v1/service/collector/general - doesn't work below is the result
{"environment":"dev","services":[]}
Server config.properties
coordinator=true
node-scheduler.include-coordinator=false
http-server.http.port=8000
query.max-memory=50GB
query.max-memory-per-node=3GB
discovery-server.enabled=true
discovery.uri=http://gdcrtdev01.[domain]:8000
Worker config.properties
coordinator=false
http-server.http.port=8000
query.max-memory=50GB
query.max-memory-per-node=1GB
discovery.uri=http://gdcrtdev01.[domain]:8000