Before you begin reading this guide, we recommend you run Elasticsearch Error Check-Up which analyzes 2 JSON files to detect many errors.
To easily locate the root cause and resolve this issue try AutoOps for Elasticsearch & OpenSearch. It diagnoses problems by analyzing hundreds of metrics collected by a lightweight agent and offers guidance for resolving them. Take a self-guided product tour to see for yourself (no registration required).
This guide will help you check for common problems that cause the log ” Recovery from failed ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: indices and recovery.
Overview
In Elasticsearch, an index (plural: indices) contains a schema and can have one or more shards and replicas. An Elasticsearch index is divided into shards and each shard is an instance of a Lucene index.
Indices are used to store the documents in dedicated data structures corresponding to the data type of fields. For example, text fields are stored inside an inverted index whereas numeric and geo fields are stored inside BKD trees.
Examples
Create index
The following example is based on Elasticsearch version 5.x onwards. An index with two shards, each having one replica will be created with the name test_index1
PUT /test_index1?pretty
{
"settings" : {
"number_of_shards" : 2,
"number_of_replicas" : 1
},
"mappings" : {
"properties" : {
"tags" : { "type" : "keyword" },
"updated_at" : { "type" : "date" }
}
}
}List indices
All the index names and their basic information can be retrieved using the following command:
GET _cat/indices?v
Index a document
Let’s add a document in the index with the command below:
PUT test_index1/_doc/1
{
"tags": [
"opster",
"elasticsearch"
],
"date": "01-01-2020"
}Query an index
GET test_index1/_search
{
"query": {
"match_all": {}
}
}Query multiple indices
It is possible to search multiple indices with a single request. If it is a raw HTTP request, index names should be sent in comma-separated format, as shown in the example below, and in the case of a query via a programming language client such as python or Java, index names are to be sent in a list format.
GET test_index1,test_index2/_search
Delete indices
DELETE test_index1
Common problems
- It is good practice to define the settings and mapping of an Index wherever possible because if this is not done, Elasticsearch tries to automatically guess the data type of fields at the time of indexing. This automatic process may have disadvantages, such as mapping conflicts, duplicate data and incorrect data types being set in the index. If the fields are not known in advance, it’s better to use dynamic index templates.
- Elasticsearch supports wildcard patterns in Index names, which sometimes aids with querying multiple indices, but can also be very destructive too. For example, It is possible to delete all the indices in a single command using the following commands:
DELETE /*
To disable this, you can add the following lines in the elasticsearch.yml:
action.destructive_requires_name: true
Overview
In Elasticsearch, recovery refers to the process of recovering an index or shard when something goes wrong. There are many ways to recover an index or shard, such as by re-indexing the data from a backup / failover cluster to the current one, or by restoring from an Elasticsearch snapshot. Alternatively, Elasticsearch performs recoveries automatically, such as when a node restarts or disconnects and connects again. There is an API to check the updated status of index / shard recoveries.
GET /<index>/_recoveryGET /_recovery
In summary, recovery can happen in the following scenarios:
- Node startup or failure (local store recovery)
- Replication of primary shards to replica shards
- Relocation of a shard to a different node in the same cluster
- Restoring a snapshot
Examples
Getting recovery information about several indices:
GET my_index1 GET my_index2/_recovery
Notes and good things to know
- When a node is disconnected from the cluster, all of its shards go to an unassigned state. After a certain amount of time, the shards will be allocated somewhere else on other nodes. This setting determines the number of concurrent shards per node that will be recovered.
PUT _cluster/settings{"transient":{"cluster.routing.allocation.node_concurrent_recoveries":3}}- You can also control when to start recovery after a node disconnects. This is useful if the node just restarts, for example, because you may not want to initiate any recovery for such transient events.
PUT _all/_settings{"settings":{"index.unassigned.node_left.delayed_timeout":"6m"}}- Elasticsearch limits the speed that is allocated to recovery in order to avoid overloading the cluster. This setting can be updated to make the recovery faster or slower, depending on your requirements.
PUT _cluster/settings{"transient":{"indices.recovery.max_bytes_per_sec":"100mb"}}Log Context
Log “[{}][{}] recovery from [{}] failed” classname is RecoveryTarget.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
if (cause instanceof AlreadyClosedException) {
listener.onIgnoreRecovery(true; "source shard is closed (" + request.sourceNode() + ")");
return;
}
logger.warn("[{}][{}] recovery from [{}] failed"; e; request.shardId().index().name(); request.shardId().id(); request.sourceNode());
listener.onRecoveryFailure(new RecoveryFailedException(request; e); true);
} finally {
shard.store().decRef();
}
} else {
