Before you begin reading this guide, we recommend you run Elasticsearch Error Check-Up which can resolve issues that cause many errors.
This guide will help you check for common problems that cause the log ” Failed to send error back to recovery source ” to appear. It’s important to understand the issues related to the log, so to get started, read the general overview on common issues and tips related to the Elasticsearch concepts: indices, recovery and source.
Advanced users might want to skip right to the common problems section in each concept or try running the Check-Up which analyses ES to pinpoint the cause of many errors and provides suitable actionable recommendations how to resolve them (free tool that requires no installation).
Overview
In Elasticsearch, an index (plural: indices) can be thought of as a table inside a database. An index 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"}}
Overview
When a document is sent to for indexing, Elasticsearch indexes all the fields in the format of inverted index but it also keeps the original json document in a special field called _source.
Examples
Disabling source field in the index
PUT /api-logs?pretty { "mappings": { "_source": { "enabled": false } } }
Store only selected fields as a part of _source field
PUT api-logs { "mappings": { "_source": { "includes": [ "*.count", "error_info.*" ], "excludes": [ "error_info.traceback_message" ] } } }
Including only selected fields using source filtering
GET api-logs/_search { "query": { "match_all": {} }, "_source": { "includes": ["api_name","status_code", "*id"] } }
Notes
The source field brings an overhead of extra storage space but serves special purposes such as:
- Return as a part of the response when a search query is executed.
- Used for reindexing purpose, update and update_by_query operations.
- Used for highlighting, if the field is not stored, it means the field is not set as “store to true” inside the mapping.
- Allows selection of fields to be returned.
The only concern with source field is the extra storage usage on disk. But this storage space used by source field can be optimized by changing compression level to best_compression. This setting is done using index.codec parameter.
Log Context
Log “failed to send error back to recovery source” classname is RecoveryTarget.java
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
protected void onFailure(Exception e) { try { channel.sendResponse(e); } catch (IOException e1) { logger.warn("failed to send error back to recovery source"; e1); } } Override public void onClusterServiceClose() {
Run the Check-Up to get customized recommendations like this:

Heavy merges detected in specific nodes

Description
A large number of small shards can slow down searches and cause cluster instability. Some indices have shards that are too small…

Recommendations Based on your specific ES deployment you should…
Based on your specific ES deployment you should…
X-PUT curl -H [a customized code snippet to resolve the issue]