Does anyone know how to retrieve a cluster that was auto removed from Databricks after not using it for some time? I added a bunch of libraries and global init scripts to it and it automatically got deleted after not using it for a month. I want to see what I did last time to either retrieve it or replicate it.
yes . 30 days after a cluster is terminated, it is permanently deleted. To keep an all-purpose cluster configuration even after a cluster has been terminated for more than 30 days, an administrator can pin the cluster. Up to 70 clusters can be pinned.You can refer : link
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Spot instances brings the posibility to use free resources in the cloud paying a lower price, however if the cloud demand is increased your resources will be dealocated. This is very usefull for non critical workloads whenever you can aford to loose some of the work done. More info 2 3
Databricks has the posibility to run spot instances on AWS but there is no documentation about how to do it on Azure.
Is it possible to run Databricks clusters on Azure Spot instances?
Yes, it is possible but not using Databricks UI. To use Azure spot instances on Databricks you need to use databricks cli.
Note
With the cli tool is it possible to administrate -create, edit, delete- clusters and instances-pools. However, to simplify the process, I'll focus on editing an existing cluster.
You can install databricks cli using pip install databricks-cli and configure your credentials with databricks configure --token. For more information, visit databricks documentation.
Run the command datbricks clusters list to know the ID of the cluster you want to modify:
$ datbricks clusters list
0422-112415-fifes919 Big Spark3 TERMINATED
0612-341234-jails230 Normal Spark3 TERMINATED
0212-623261-mopes727 Small 7.6 TERMINATED
In my case, I have 3 clusters. First column is the cluster ID, second one is the name of the cluster. Last column is the state.
The command databricks cluster get generates the cluster config in json format. Let's generate the json file to modify it:
databricks clusters get --cluster-id 0422-112415-fifes919 > /tmp/my_cluster.json
This file contains all the configuration related to the cluster like name, instance type, owner... In our case we are looking for the azure_attributes section. You will see something similar to:
...
"azure_attributes": {
"first_on_demand": 1,
"availability": "ON_DEMAND_AZURE",
"spot_bid_max_price": -1.0
},
...
We need to change the availability to SPOT_WITH_FALLBACK_AZURE and spot_bid_max_price with our bid price. Edit the file with your favorite tool. The result should be something like:
...
"azure_attributes": {
"first_on_demand": 1,
"availability": "SPOT_WITH_FALLBACK_AZURE",
"spot_bid_max_price": 0.4566
},
...
Once modified, just update the cluster with the new configuration file using databricks clusters edit:
databricks clusters edit --json-file /tmp/my_cluster.json
Now, everytime you start the cluster, the workers will be spot instances.To confirm this, you can go to the configuration tab inside the worker VM that is allocated in the resource group managed by databricks. You will see the Azure spot is active and with the price configured.
Databricks on AWS has more configuration options like SPOT for the availability field. However, until the documentation is released we'll need to wait or configure with try-error approach.
I am new to Apache NIFI tool. I am trying to import data from mongo db and put that data into the HDFS. I have created 2 processors one for MongoDB and second for HDFS and I configured them correctly. The job is running successfully and storing the data into HDFS but the job should terminate automatically on success. But it is not, and creating too many files in HDFS. I want to know how to make On Demand Job in NIFI and how to determine that a job is successfull.
GetMongo will continue to pull data from MongoDB based on the provided properties such as Query, Projection, Limit. It has no way of tracking the execution process, at least for now. What you can do, however, is changing the Run Schedule and/or Scheduling Strategy. You can find them by right clicking on the processor and clicking Configure. By default, Run Schedule will be 0 sec which means running continuously. Changing it to, say, 60 min will make the processor run every one hour. This will still read the same documents from MongoDB again every one hour but since you have mentioned that you just want to run it only once, I'm suggesting this approach.
I have a elasticsearch 5.6.2 cluster with one master and two data nodes and I am using Kibana for visualizing . I want to enable automatic snapshots for the elasticsearch cluster to Amazon-s3 every 30mins. Can I Know How Can I accomplish it ..? There is no proper Documentation . I had also refered curator docs and I have a question, DO I need to configure that curator or on each node ...?
Please help guys
Curator is an external process.
You must put it on one single machine. It can be a node or any other machine.
It will send REST requests to elasticsearch when needed.
Put in your crontab and that is going to be ok.
You can also call the SNAPSHOT endpoint manually from a shell script every 30 minutes and don’t use curator at all.
Elastic cloud does a backup every 30 minutes (in case you don’t want to manage the cluster yourself and have that kind of advanced features like also rolling upgrades, Kibana, security...)
Laconically: Should I start HDFS every that I come back to the cluster after a power-off operation?
I have successfully created a Hadoop cluster (after loosing some battles) and now I want to be very careful on proceeding with this.
Should I execute start-dfs.sh every time I power on the cluster, or it's ready to execute my application's code? Same for start-yarn.sh.
I am afraid that if I run it without everything being fine, it might leave garbage directories after execution.
Just from playing around with the Hortonworks and Cloudera sandboxes, I can say turning them on and off doesn't seem to demonstrate any "side-effects".
However, it is necessary to start the needed services everytime the cluster starts.
As far as power cycling goes in a real cluster, it is recommended to stop the services running on the respective nodes before powering them down (stop-dfs.sh and stop-yarn.sh). That way there are no weird problems and any errors on the way to stopping the services will be properly logged on each node.
I have just spent the best part of 12 hours indexing 70 million documents into Elasticsearch (1.4) on a single node, single server setup on an EC2 Ubuntu 14.04 box. This completed successfully however before taking a snapshot of my server I thought it would be wise to rename the cluster to prevent it accidentally joining production boxes in the future, what a mistake that was! After renaming in the elasticsearch.yml file and restarting the ES service my indexes have disappeared.
I saw the data was still present in the data dir under the old cluster name, i tried stopping ES, moving the data manually in the filesystem and then starting the ES service again but still no luck. I then tried renaming back to the old cluster name, putting everything back in place and still nothing. The data is still there, all 44gb of it but I have no idea how to get this back. I have spent the past 2 hours searching and all i can seem to find is advice on how to restore from a snapshot which I don't have. Any advice would be hugely appreciated - I really hope I haven't lost a day's work. I will never rename a cluster again!
Thanks in advance.
I finally fixed this on my own: Stopped the cluster, deleted the nodes directory that had been created in the new cluster, copied my old nodes directort over being sure to respect the old structure exactly, chowned the folder to elasticsearch just in case, started up the cluster and breathed a huge sigh of relief to see 72 million documents!