What is the number of remote clusters can handle by Elasticsearch CMS smoothly? The number of Seeds can be joined at a time to run a CMS cluster.
I am currently joined 3 remote cluster in a CMS. But if the remote number increased what is the maximum number of Remote Cluster can join for CMS
Related
If I need a 3-node cluster do I need to have 3 instances? Or are they created in same instance?
https://i.stack.imgur.com/4oRAI.png
If you need a 3-node cluster then you must have 3 instances. Node means a separate instance and 3 machine ElasticSearch cluster will have different jobs assigned to each node.
What is an Elasticsearch cluster?
As the name implies, an Elasticsearch cluster is a group of one or more Elasticsearch nodes instances that are connected together. The power of an Elasticsearch cluster lies in the distribution of tasks, searching and indexing, across all the nodes in the cluster.
The nodes in the Elasticsearch cluster can be assigned different jobs or responsibilities:
Data Nodes - stores data and executes data-related operations such as search and aggregation
Master Nodes - in charge of cluster-wide management and configuration actions such as adding and removing nodes
Client Nodes - forwards cluster requests to the master node and data-related requests to data nodes
Ingest Nodes - for pre-processing documents before indexing
By default, each node is automatically assigned a unique identifier, or name, that is used for management purposes and becomes even more important in a multi-node, or clustered, environment.
When installed, a single Elasticsearch node will form a new single-node cluster entitled elasticsearch but it can also be configured to join an existing cluster using the cluster name.
I have 10 amazon ec2 node cluster used for every day data processing and i want to use all the 10 nodes for each day batch process (2 hours process only) and once the reporting data points got generated then i want to shutdown 5 nodes and make only 5 nodes active rest of the day for cost optimization.
I have a replication factor of 3.
In some scenarios all the 3 data blocks(actual & replication blocks) got stored in those 5 nodes which i am shutting down. Because of which i am not able to read the data properly.
Can i make some settings in cloudera manager to persist specific Database or Specific tables into given nodes, so that i will not have any issue in reading the data with only 5 nodes active.
Or any other suggestions will be appreciated.
You can use rack awareness (virtually) to separate your cluster into 2 "racks", and place your 5 nodes that you shut down regularly on a separate "rack". Replication policy will require that the NN place the replicas on separate racks, if configured. Again, I'm referring to racks in the virtual sense here. That should get you what you want.
I need to provide many elasticSearch instances for different clients but hosted in my infrastructre.
For the moment it is only some small instances.
I am wondering if it is not better to build a big ElastSearch Cluster with 3-5 servers to handle all instances and then each client gets a different index in this cluster and each instance is distributed over servers.
Or maybe another idea?
And another question is about quorum, what is the quorum for ES please?
thanks,
You don’t have to assign each client to different index, Elasticsearch cluster will automatically share loading among all nodes which share shards.
If you are not sure how many nodes are needed, start from a small cluster then keep monitoring the health status of cluster. Add more nodes to the cluster if server loading is high; remove nodes if server loading is low.
When the cluster continuously grow, you may need to assign a dedicated role to each node. In this way, you will have more control over the cluster, easier to diagnose the problem and plan resources. For example, adding more master nodes to stabilize the cluster, adding more data nodes to increase searching and indexing performance, adding more coordinate nodes to handle client requests.
A quorum is defined as majority of eligible master nodes in cluster as follows:
(master_eligible_nodes / 2) + 1
I want to use sharding in arangoDB.I have made coordinators, DBServers as mentioned in documentation 2.8.5. But still can someone still explain it in details and also how can I able to check the performance of my query after and before sharding.
Testing your application can be done with a local cluster, were all instances run on one machine - which is what you already did, if I get that correctly?
An ArangoDB cluster consists of coordinator and dbserver nodes. Coordinators don't have own user specific local collections on disk. Their role is to handle the I/O with the clients, parse, optimize and distribute the queries and the user data to the dbserver nodes. Foxx services will also be run on the coordinators. DBServers are the storage nodes in this setup, they keep the user data.
To compare the performance between clustered and non clustered mode you import a dataset on a clustered instance and a non clustered one and compare the query result times. Since the cluster setup can have more network communication (i.e. if you do a join) than the single server case, the performance can be different. On a
physically distributed cluster you may achieve higher throughput, since in the end the cluster nodes are own machines and have their own IO paths that end on separate physical harddisks.
In the cluster case you create collections specifying the number of shards using the numberOfShards parameter; the shardKeys parameter can control the distribution of your documents across the shards. You should choose that key so documents distribute well across the shards (i.e. are not inbalanced to just one shard). The numberOfShards can be an arbitrary value and doesn't have to corrospond to the number of dbserver nodes - it could even be bigger so you can more easily move a shard from one dbserver to a new dbserver when scaling up your cluster to more nodes in the future to adapt to higher loads.
When you're developping AQL queries with cluster use in mind, its essential to use the explain command to inspect how the query is distributed across the clusters, and where filters can be deployed:
db._create("sharded", {numberOfShards: 2})
db._explain("FOR x IN sharded RETURN x")
Query string:
FOR x IN sharded RETURN x
Execution plan:
Id NodeType Est. Comment
1 SingletonNode 1 * ROOT
2 EnumerateCollectionNode 1 - FOR x IN sharded /* full collection scan */
6 RemoteNode 1 - REMOTE
7 GatherNode 1 - GATHER
3 ReturnNode 1 - RETURN x
Indexes used:
none
Optimization rules applied:
Id RuleName
1 scatter-in-cluster
2 remove-unnecessary-remote-scatter
In this simple query the RETURN & GATHER -nodes are on the coordinator; the nodes upwards including the REMOTE-node are deployed to the DB-server.
In general less REMOTE / SCATTER -> GATHER pairs means less cluster communication. The closer FILTER nodes can be deployed to *CollectionNodes to reduce the amount of the documents to be sent via the REMOTE-nodes the better the performance.
I'm newbie to search and elasticsearch. I have gone some online docs and developed some app using elasticsearch setup in our test environment. So far, its smooth in developing and testing, Now do create in production and setup the cluster, i need some expert advise on,
Number of shards
Number of replicas
Should i need to separate out master and data nodes
can all the nodes be data node
i dont have any advanced search use case, but atleast need plural match (phone) should match all docs with phones and vice versa, any special stemming need in this case ?
My usecase and traffic patterns are,
Upto 100M read per day
Upto 1M write/update per day
Initial data size 10GB, grow rate 1 GB every 6 months
Cluster info
1. Initial cluster size 14 machines, 28 GB RAM / 120 GB spin hard disk / 12 cores
2. load balancer with dns, would distribute the traffic to any 14 machines.
I have used unicast and i have bootstrap.mlockall: true and index.routing.allocation.disable_allocation: false
Please advise.
Thanks
1. Number of shards
The number of shards in Elasticsearch is a one-time setting, once your shard size is set you cannot change it. So you need to plan how many shards are required for your cluster taking into consideration your current dataset size plus any index growth. To do this set up one Elasticsearch node with one shard and zero replicas on a box that has the same specifications as your production boxes.
The capacity of a single shard will depend on a number of factors:
The size of your documents
The size of your fields
The amount a RAM you assign the JVM that runs Elasticsearch. If you have lots of aggregations,
sorting and parent/child documents, you will need to make sure that you have assigned enough RAM
to Elasticsearch so it can cache the results.
Your number of queries per second requirement.
The maximum search request response time allowed.
Index documents into your single shard node at iterations of x million (or less), at each iteration perform benchmarks by executing x queries per second using a testing tool like JMeter. When the queries in your tests are returning response times that are reaching your maximum search request time you have the amount of documents a single shard can index. Once you have this value you can calculate the number of shards that is required for your full dataset and calculate how many shards you will need for index growth.
2. Number of replicas
Start with 1 replica, a replica shard will be placed on a different node from its primary shard so if one node goes down you still have the full dataset available. One replica is usually sufficient, if you find you need more you can always add them in later on.
3.Should i need to separate out master and data nodes
It depends on the size of your cluster, if you have more than 5 nodes in your cluster it is advisable to have master only nodes to maintain cluster state only.
4. can all the nodes be data node
There must always be at least one master node in your cluster, the master node maintains the cluster state. If you have a small cluster (< 5 nodes), you can make every node in your cluster both a data node and a master node. One of of the nodes will be elected as the master, if the master node goes down another node in the cluster will be elected as the master. If you have master only nodes as described in point 3, the rest of the of the nodes in the cluster can be data only nodes.
5. i dont have any advanced search use case, but atleast need plural match (phone) should match all docs with phones and vice versa, any special stemming need in this case ?
Yes, stemming will handle your use case.
Also, Elasticsearch comes with very good configurations OOTB, you should start out by only changing the configurations listed in the link below.
http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/_important_configuration_changes.html