Before you begin reading this guide, we recommend you try running the Elasticsearch Error Check-Up which analyzes 2 JSON files to detect many configuration 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.
This guide will help you check for common problems that cause the log ” unexpected token while parsing source settings ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: source and settings.
Overview
When a document is sent for indexing, Elasticsearch indexes all the fields in the format of an 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.
Settings in Elasticsearch
In Elasticsearch, you can configure cluster-level settings, node-level settings and index level settings. Here is a quick rundown of each level.
A. Cluster settings
These settings can either be:
- Persistent, meaning they apply across restarts, or
- Transient, meaning they won’t survive a full cluster restart.
If a transient setting is reset, the first one of these values that is defined is applied:
- The persistent setting
- The setting in the configuration file
- The default value
The order of precedence for cluster settings is:
- Transient cluster settings
- Persistent cluster settings
- Settings in the elasticsearch.yml configuration file
Examples
An example of persistent cluster settings update:
PUT /_cluster/settings
{
"persistent" : {
"indices.recovery.max_bytes_per_sec" : "500mb"
}
}An example of a transient update:
PUT /_cluster/settings
{
"transient" : {
"indices.recovery.max_bytes_per_sec" : "40mb"
}
}B. Index settings
These are the settings that are applied to individual indices. There is an API to update index level settings.
Examples
The following API call will set the number of replica shards to 5 for my_index index.
PUT /my_index/_settings
{
"index" : {
"number_of_replicas" : 5
}
}To revert a setting to the default value, use null.
PUT /my_index/_settings
{
"index" : {
"refresh_interval" : null
}
}C. Node settings
These settings apply to nodes. Nodes can fulfill different roles. These include the master, data, and coordination roles. Node settings are set through the elasticsearch.yml file for each node.
Examples
Setting a node to be a data node (in the elasticsearch.yml file):
node.data: true
Disabling the ingest role for the node (which is enabled by default):
node.ingest: false
For production clusters, you will need to run each type of node on a dedicated machine with two or more instances of each, for HA (minimum three for master nodes).
Notes and good things to know
- Learning more about the cluster settings and index settings is important – it can spare you a lot of trouble. For example, if you are going to ingest huge amounts of data into an index and the number of replica shards is set to say, 5, the indexing process will be super slow because the data will be replicated at the same time it is indexed. What you can do to speed up indexing is to set the replica shards to 0 by updating the settings, and set it back to the original number when indexing is done, using the settings API.
- Another useful example of using cluster-level settings is when a node has just joined the cluster and the cluster is not assigning any shards to the node. Although shard allocation is enabled by default on all nodes, someone may have disabled shard allocation at some point (for example, in order to perform a rolling restart), and forgot to re-enable it later. To enable shard allocation, you can update the Cluster Settings API:
PUT /_cluster/settings{"transient":{"cluster.routing.allocation.enable":"all"}}- It’s better to set cluster-wide settings with Settings API instead of with the elasticsearch.yml file and to use the file only for local changes. This will keep the same setting on all nodes. However, if you define different settings on different nodes by accident using the elasticsearch.yml configuration file, it is hard to notice these discrepancies.
- See also: Recovery
Log Context
Log “unexpected token while parsing source settings”classname is MultiGetRequest.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :
currentList.add(parser.text());
}
} else if (token.isValue()) {
currentList.add(parser.text());
} else {
throw new ElasticsearchParseException("unexpected token while parsing source settings");
}
}
fetchSourceContext = new FetchSourceContext(fetchSourceContext.fetchSource();
includes == null ? Strings.EMPTY_ARRAY : includes.toArray(new String[includes.size()]);
