Unassigned primary shards - elasticsearch

Using ES 1.5.2
When a primary shard is unassigned. Does it mean the data is lost?
I had some unassigned primaries tried to re-allocate them with the allocate command, but the index didn't go back to it's original size.

There shouldn't be any data loss, one of the the master node's roles is specifically to retrieve all the data in the soon-to-be unassigned shard and dispatch it across all the other available shards.

Related

Allocate Shards and replica to specific node

I am beginner to Elastic search ,
I have an elastic search cluster with 3 nodes in ec2 AWS, from these nodes 2 are spot instances, and one is on-demand instances. Since shards and replicas are distributed among all nodes. I need to set that on-demand instance as a primary node means there should be allocated a replica of every index in the 3 nodes into the primary node(on-demand instance). So if even the spot instances get terminated I will not lose the data. Is there an way to configure it. Thanks in advance.
If I understand correctly, you want to allocate primary shard to the on-demand instance?
Primary/replica shard level filtering is not possible currently. However, if your concern is regarding data loss, you don't have to worry so much because if the primary shards goes down one of the replica shard gets promoted to primary shard.

Do all shards (within index) have the same content?

Do all shards (within index) have the same content?
If yes, more shards = longer propagation (save) time?
If no, when one of shards failed = data is incomplete when merging?
First, you need to understand what is sharding and why it's important in distributed systems like elasticsearch. You can read some good resources on shards here here and here.
Now Coming to your question,
Do all shards (within index) have the same content.
The answer, is no (assuming you are referring to primary shards here, of course, replica shard is just a copy of primary shard), let's take an example.
Your Index contains around 100 million docs and you have a 10 data nodes cluster, then you want to horizontally scale your index, so you started with the setting of 10 primary shards and 1 replica shards. In this case, elasticsearch will physically divide your data into 10 primary shards and each primary shard will be on a different node of a cluster as there are 10 data nodes and similarly every primary shards copy which is called replica of a shard which is on a different node of its primary shard.
Now coming to your follow-up question.
If yes, more shards = longer propagation (save) time? If no, when one
of shards failed = data is incomplete when merging?
As elasticsearch doesn't store the same data in all the primary shards, so more shards mean longer propagation or save time is invalid and also when one of the shards is failed then elasticsearch recover its data from its replica shard as it's present physically on a different data node server.
Bonus tip:- Shards are used to split your data and to make your application horizontal scalable, while the replica is to make your application is highly available as it contains the duplicated data, so the application can recover easily from the scenario you just asked in your follow-up question.
Let me know if you need any clarification or more details.
short answer:
Q-1: no
if-no: if index has not a replica, it affects the whole index but not other shards of the index .
please read this document:
https://www.elastic.co/guide/en/elasticsearch/reference/6.2/_basic_concepts.html

Does Elasticsearch stop indexing data when some nodes go down?

I have read that when a new indexing request is sent to ES cluster. ES will specify which shard should that document be stored in depending on routing. Then that node which hosts that primary shard (aka coordinating node) will broadcast the indexing request to each node containing a replica for that shard and it will respond to the client that the document has been indexed successfully if the primary shard and it's replicas stored/indexed that document.
Does that mean that ES supports high availability(node tolerant) for reading requests and not for writing request or it's the default behavior and can be changed?
The main purpose of replicas is for failover, if the node holding a primary shard dies, a replica is promoted to the role of primary. Also, replica shards can serve read requests thus improving search performance.
For write requests though, indexing will be affected if one of your nodes (which has the primary shard for a live index) in the cluster suddenly runs out of disk space because if a node disk usage hits configured watermark levels then ES throws a cluster block exception preventing any writes to the node. If ALL nodes are down/ unreachable indexing will stop however if only one or some nodes go down, indexing shouldn't completely stop as replica shards on other nodes are promoted to primary if the node holding the original primary is offline. Ideally, it goes without saying that some analysis and effort should go to right size an ES cluster and have monitoring in place to prevent any issues.

If a shard goes down, then, after re-allocating that shard, will data residing in that shard be retrievable

I have manually allocated 3 primary shards to a particular node in ElasticSearch. The replicas of these shards reside in different nodes. Now, let's say, primary shard number 2 goes down (for example, due to overflow of data) without the node on which it is residing going down. Then is it possible to retrieve the data residing on that particular shard, after I manually re-allocate it to a different node? If yes, how?
Yes.
Once the node with primary shard number 2 goes down then the replica shard on the other node will be upgraded to a primary shard - allowing you to retrieve the data. See here:
Coping with failure (ES Definitive Guide)

elasticsearch undefined index and how to get rid of it

I am seeing the following index Unassigned which is very annoying. How do I get rid of it
Those unassigned shards are actually unassigned replicas of your actual shards from the master node.
The main purpose of replicas is for failover: if the node holding a primary shard dies, then a replica is promoted to the role of primary.
At index time, a replica shard does the same amount of work as the primary shard. New documents are first indexed on the primary and then on any replicas. Increasing the number of replicas does not change the capacity of the index.
However, replica shards can serve read requests. If, as is often the case, your index is search-heavy, you can increase search performance by increasing the number of replicas, but only if you also add extra hardware.
In order to assign these shards, you need to run a new instance of elasticsearch to create a secondary node to carry the data replicas. (The node can be master eligible or just a workhorse. Of course, you can set those configurations in the elasticsearch config files)
For more details about it you can refer to the official documentation and the Elasticsearch Definitive Guide (the work on it is still in progress but you will find what you are looking for here)

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