NodeManager | rapid development of battery-powered sensors
kandi X-RAY | NodeManager Summary
kandi X-RAY | NodeManager Summary
NodeManager is intended to take care on your behalf of all those common tasks that a MySensors node has to accomplish, speeding up the development cycle of your projects. Consider it as a sort of frontend for your MySensors projects. When you need to add a sensor (which requires just uncommeting a single line), NodeManager will take care of importing the required library, presenting the sensor to the gateway/controller, executing periodically the main function of the sensor (e.g. measure a temperature, detect a motion, etc.), allowing you to interact with the sensor and even configuring it remotely.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of NodeManager
NodeManager Key Features
NodeManager Examples and Code Snippets
Community Discussions
Trending Discussions on NodeManager
QUESTION
I'm creating a Dataproc cluster, and it is timing out when i'm adding the connectors.sh in the initialization actions.
here is the command & error
...ANSWER
Answered 2022-Feb-01 at 20:01It seems you are using an old version of the init action script. Based on the documentation from the Dataproc GitHub repo, you can set the version of the Hadoop GCS connector without the script in the following manner:
QUESTION
I am trying to set up distributed HBase on 3 nodes. I have already set up hadoop, YARN ZooKeeper and now HBase but when I launch hbase shell and run the simplest command for example status or list I get the exception:
ANSWER
Answered 2021-Dec-30 at 11:11UPDATE:
I have solved the issue by adding the following property to the hbase-site.xml:
QUESTION
I'm currently working on a C# project where I want to develop my own OPC server application that I can configure with XML. I already compiled a custom XML object with the UA-ModelCompiler repo.
I used the Boiler example from the UA-.NETStandard-Samples repo. I added some custom objects for an agv and I want to integrate it with my own NodeManager. I copied the BoilerNodeManager and modified it for an agv. The following method always has an error.
...ANSWER
Answered 2021-Dec-10 at 12:56I forgot to add the EmbeddedResouce path within Opc.Ua.Sample.csproj.
QUESTION
All,
We have a Apache Spark v3.12 + Yarn on AKS (SQLServer 2019 BDC). We ran a refactored python code to Pyspark which resulted in the error below:
Application application_1635264473597_0181 failed 1 times (global limit =2; local limit is =1) due to AM Container for appattempt_1635264473597_0181_000001 exited with exitCode: -104
Failing this attempt.Diagnostics: [2021-11-12 15:00:16.915]Container [pid=12990,containerID=container_1635264473597_0181_01_000001] is running 7282688B beyond the 'PHYSICAL' memory limit. Current usage: 2.0 GB of 2 GB physical memory used; 4.9 GB of 4.2 GB virtual memory used. Killing container.
Dump of the process-tree for container_1635264473597_0181_01_000001 :
|- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE
|- 13073 12999 12990 12990 (python3) 7333 112 1516236800 235753 /opt/bin/python3 /var/opt/hadoop/temp/nm-local-dir/usercache/grajee/appcache/application_1635264473597_0181/container_1635264473597_0181_01_000001/tmp/3677222184783620782
|- 12999 12990 12990 12990 (java) 6266 586 3728748544 289538 /opt/mssql/lib/zulu-jre-8/bin/java -server -XX:ActiveProcessorCount=1 -Xmx1664m -Djava.io.tmpdir=/var/opt/hadoop/temp/nm-local-dir/usercache/grajee/appcache/application_1635264473597_0181/container_1635264473597_0181_01_000001/tmp -Dspark.yarn.app.container.log.dir=/var/log/yarnuser/userlogs/application_1635264473597_0181/container_1635264473597_0181_01_000001 org.apache.spark.deploy.yarn.ApplicationMaster --class org.apache.livy.rsc.driver.RSCDriverBootstrapper --properties-file /var/opt/hadoop/temp/nm-local-dir/usercache/grajee/appcache/application_1635264473597_0181/container_1635264473597_0181_01_000001/spark_conf/spark_conf.properties --dist-cache-conf /var/opt/hadoop/temp/nm-local-dir/usercache/grajee/appcache/application_1635264473597_0181/container_1635264473597_0181_01_000001/spark_conf/spark_dist_cache.properties
|- 12990 12987 12990 12990 (bash) 0 0 4304896 775 /bin/bash -c /opt/mssql/lib/zulu-jre-8/bin/java -server -XX:ActiveProcessorCount=1 -Xmx1664m -Djava.io.tmpdir=/var/opt/hadoop/temp/nm-local-dir/usercache/grajee/appcache/application_1635264473597_0181/container_1635264473597_0181_01_000001/tmp -Dspark.yarn.app.container.log.dir=/var/log/yarnuser/userlogs/application_1635264473597_0181/container_1635264473597_0181_01_000001 org.apache.spark.deploy.yarn.ApplicationMaster --class 'org.apache.livy.rsc.driver.RSCDriverBootstrapper' --properties-file /var/opt/hadoop/temp/nm-local-dir/usercache/grajee/appcache/application_1635264473597_0181/container_1635264473597_0181_01_000001/spark_conf/spark_conf.properties --dist-cache-conf /var/opt/hadoop/temp/nm-local-dir/usercache/grajee/appcache/application_1635264473597_0181/container_1635264473597_0181_01_000001/spark_conf/spark_dist_cache.properties 1> /var/log/yarnuser/userlogs/application_1635264473597_0181/container_1635264473597_0181_01_000001/stdout 2> /var/log/yarnuser/userlogs/application_1635264473597_0181/container_1635264473597_0181_01_000001/stderr
[2021-11-12 15:00:16.921]Container killed on request. Exit code is 143
[2021-11-12 15:00:16.940]Container exited with a non-zero exit code 143.
For more detailed output, check the application tracking page: https://sparkhead-0.mssql-cluster.everestre.net:8090/cluster/app/application_1635264473597_0181 Then click on links to logs of each attempt.
. Failing the application.
The default setting is as below and there are no runtime settings:
"settings": {
"spark-defaults-conf.spark.driver.cores": "1",
"spark-defaults-conf.spark.driver.memory": "1664m",
"spark-defaults-conf.spark.driver.memoryOverhead": "384",
"spark-defaults-conf.spark.executor.instances": "1",
"spark-defaults-conf.spark.executor.cores": "2",
"spark-defaults-conf.spark.executor.memory": "3712m",
"spark-defaults-conf.spark.executor.memoryOverhead": "384",
"yarn-site.yarn.nodemanager.resource.memory-mb": "12288",
"yarn-site.yarn.nodemanager.resource.cpu-vcores": "6",
"yarn-site.yarn.scheduler.maximum-allocation-mb": "12288",
"yarn-site.yarn.scheduler.maximum-allocation-vcores": "6",
"yarn-site.yarn.scheduler.capacity.maximum-am-resource-percent": "0.34".
}
Is the AM Container mentioned the Application Master Container or Application Manager (of YARN). If this is the case, then in a Cluster Mode setting, the Driver and the Application Master run in the same Container?
What runtime parameter do I change to make the Pyspark code successfully.
Thanks,
grajee
ANSWER
Answered 2021-Nov-19 at 13:36Likely you don't change any settings 143 could mean a lot of things, including you ran out of memory. To test if you ran out of memory. I'd reduce the amount of data you are using and see if you code starts to work. If it does it's likely you ran out of memory and should consider refactoring your code. In general I suggest trying code changes first before making spark config changes.
For an understanding of how spark driver works on yarn, here's a reasonable explanation: https://sujithjay.com/spark/with-yarn
QUESTION
I am getting the following error while run the obiee12c configuration assistant.
weblogic.nodemanager.common.ConfigException: Identity key store file not found DemoIdentity.jks
The following is the error log:
.../security/DemoIdentity.jks on server AdminServer> /security/DemoIdentity.jks on server AdminServer> /security/DemoIdentity.jks on server AdminServer.> /security/DemoIdentity.jks on server AdminServer>
ANSWER
Answered 2021-Sep-14 at 08:26The following is the workaround to resolve the issue.
Step 1: Browse to the location '\security'
Step 2: Copy the file "DemoIdentity.jks" from '\security' location and paste to '\security' location
Step 3: Re-run the obiee12c configuration assistant.
QUESTION
I saw a bunch of question with a similar topic but I couldn't find a solution to my problem. Hopefully someone can help.
I have a Ruby on Rails app. In this app, I have some base64 data that I want to decode and write in a file. When I have a small script that I call through ruby myFile.rb, the program behaves as expeted. However when I run the same code with rails c. I have the following error:
...ANSWER
Answered 2021-Jul-15 at 13:00A simple solution was to give the File.write function the 'wb' rights
QUESTION
I am following this example:
I find the namenode as follows:
ANSWER
Answered 2021-Jul-15 at 11:38Remove the $ at the beginning. That's what $: command not found means. Easy to miss when copy pasting code
QUESTION
I ran several streaming spark jobs and batch spark jobs in the same EMR cluster. Recently, one batch spark job is programmed wrong, which consumed a lot of memory. It causes the master node not response and all other spark jobs stuck, which means the whole EMR cluster is basically down.
Are there some way that we can restrict the maximum memory that a spark job can consume? If the spark job consumes too much memory, it can be failed. However, we do not hope the whole EMR cluster is down.
The spark jobs are running in the client mode with spark submit cmd as below.
...ANSWER
Answered 2021-Jul-13 at 11:58You can utilize yarn.nodemanager.resource.memory-mb
The total amount of memory that YARN can use on a given node.
Example : If your machine is having 16 GB Ram,
and you set this property to 12GB , maximum 6 executors or drivers will launched (since you are using 2gb per executor/driver) and 4 GB will be free and can be used for background processes.
QUESTION
I'm trying to make a Node Based editor with C# and Dataflow. I created the following class for the nodes:
...ANSWER
Answered 2021-Jul-13 at 00:31The particular overload of LinkTo you are looking for is implemented as an Extension Method. You can find this detail from the documentation for IPropagatorBlock.
Unfortunately, the dynamic keyword and Extension method syntax don't work as you would like. IPropagatorBlock does define a LinkTo method with two parameters, but the one you were trying to use that only has one parameter could not be found. Another answer in the link above explains even more about why dynamic and Extension Methods don't play nice.
As the linked answer says, you can still use Extension methods with dynamic, but you have to call it as a static method and pass in both arguments. In your case, the line with the Exception becomes:
QUESTION
What does mean Mem Avail in yarn UI?
I set yarn.scheduler.minimum-allocation-mb to 1024 and yarn.scheduler.maximum-allocation-mb to 4096. yarn.nodemanager.resource.memory-mb is also set to -1 as default. I can see the memory is free in every nodes and UI show that Phys Mem Used is just 14%. However, the Mem Avail is 0 B and I don't know what is it and how to increase it.
ANSWER
Answered 2021-Jun-29 at 13:42I found the answer!
It's equal to yarn.nodemanager.resource.memory-mb which is The total amount of memory that YARN can use on a given node. You might need to set it higher inside yarn-site.xml depending on the amount of data you plan on processing.
The default value of this config is 8GB, although with getconf command you will see -1 which doesn't mean total memory of the system.
Before:
$ hdfs getconf -confKey yarn.nodemanager.resource.memory-mb
-1
After set it in yarn-site.xml:
$ hdfs getconf -confKey yarn.nodemanager.resource.memory-mb
40960
The result:
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Install NodeManager
Install NodeManager as an Arduino library (https://www.arduino.cc/en/Guide/Libraries)
Please be aware when upgrading to v1.8 from an older version this procedure is not supported and the code should be migrated manually.
Make a backup copy of the library, remove it, download the latest version of NodeManager and install the new library
Review the release notes in case there is any manual change required to the main sketch
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