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This guide will help you check for common problems that cause the log ” timed out waiting for mapping updates ” + “(timeout ” + timeout + “) ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: recovery, indices, mapping.
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
Mapping is similar to database schemas that define the properties of each field in the index. These properties may contain the data type of each field and how fields are going to be tokenized and indexed. In addition, the mapping may also contain various advanced level properties for each field to define the options exposed by Lucene and Elasticsearch. You can create a mapping of an index using the _mappings REST endpoint. The very first time Elasticsearch finds a new field whose mapping is not pre-defined inside the index, it automatically tries to guess the data type and analyzer of that field and set its default value. For example, if you index an integer field without pre-defining the mapping, Elasticsearch sets the mapping of that field as long.
Examples
Create an index with predefined mapping:
PUT /my_index?pretty
{
"settings": {
"number_of_shards": 1
},
"mappings": {
"properties": {
"name": {
"type": "text"
},
"age": {
"type": "integer"
}
}
}
}Create mapping in an existing index:
PUT /my_index/_mapping?pretty
{
"properties": {
"email": {
"type": "keyword"
}
}
}View the mapping of an existing index:
GET my_index/_mapping?pretty
View the mapping of an existing field:
GET /my_index/_mapping/field/name?pretty
Notes
- It is not possible to update the mapping of an existing field. If the mapping is set to the wrong type, re-creating the index with updated mapping and re-indexing is the only option available.
- In version 7.0, Elasticsearch has deprecated the document type and the default document type is set to _doc. In future versions of Elasticsearch, the document type will be removed completely.
Common problems
- The most common problem in Elasticsearch is incorrectly defined mapping which limits the functionality of the field. For example, if the data type of a string field is set as text, you cannot use that field for aggregations, sorting or exact match filters. Similarly, if a string field is dynamically indexed without predefined mapping, Elasticsearch automatically creates two fields internally. One as a text type for full-text search and another as keyword type, which in most cases is a waste of space.
- Elasticsearch automatically creates an _all field inside the mapping and copies values of each field of a document inside the _all field. This field is used to search text without specifying a field name. Make sure to disable the _all field in production environments to avoid wasting space. Please note that support for the _all field has been removed in version 7.0.
- In versions lower than 5.0, it was possible to create multiple document types inside an index, similar to creating multiple tables inside a database. In those versions, there were higher chances of getting data types conflicts across different document types if they contained the same field name with different data types.
- The mapping of each index is part of the cluster state and is managed by master nodes. If the mapping is too big, meaning there are thousands of fields in the index, the cluster state grows too large to be handled and creates the issue of mapping explosion, resulting in the slowness of the cluster.
Log Context
Log “timed out waiting for mapping updates ” + “(timeout [” + timeout + “])”classname is PeerRecoveryTargetService.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :
@Override
public void onTimeout(TimeValue timeout) {
// note that we do not use a timeout (see comment above)
listener.onFailure(
new ElasticsearchTimeoutException("timed out waiting for mapping updates " + "(timeout [" + timeout + "])")
);
}
});
};
final IndexMetadata indexMetadata = clusterService.state().metadata().index(request.shardId().getIndex());
Find & fix Elasticsearch problems
