Before you dig into reading this guide, have you tried asking OpsGPT what this log means? You’ll receive a customized analysis of your log.
Try OpsGPT now for step-by-step guidance and tailored insights into your OpenSearch operation.
Briefly, this error occurs when OpenSearch is unable to locate a segment file that corresponds to a specific metadata file in a remote location. This could be due to file corruption, deletion, or a network issue. To resolve this, you can try to restore the missing segment file from a backup, ensure the file path in the metadata is correct, or check the network connection to the remote location. If the file is corrupted, you may need to rebuild the index.
For a complete solution to your to your search operation, try for free AutoOps for Elasticsearch & OpenSearch . With AutoOps and Opster’s proactive support, you don’t have to worry about your search operation – we take charge of it. Get improved performance & stability with less hardware.
This guide will help you check for common problems that cause the log ” Segment file {} corresponding to metadata file {} does not exist in remote ” to appear. To understand the issues related to this log, read the explanation below about the following OpenSearch concepts: index, metadata.
Quick links
Overview
In OpenSearch, an index (plural: indices) contains a schema and can have one or more shards and replicas. An OpenSearch 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 OpenSearch 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",
"OpenSearch"
],
"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, OpenSearch 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.
- OpenSearch 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 OpenSearch.yml:
action.destructive_requires_name: true
Overview
Metadata in OpenSearch refers to additional information stored for each document. This is achieved using the specific metadata fields available in OpenSearch. The default behavior of some of these metadata fields can be customized during mapping creation.
Examples
Using _meta meta-field for storing application-specific information with the mapping:
PUT /my_index?pretty
{
"mappings": {
"_meta": {
"domain": "security",
"release_information": {
"date": "18-01-2020",
"version": "7.5"
}
}
}
}Notes
- Meta fields available include: _index, _type, _id, _source, _size, and _field_name.
Log Context
Log “Segment file {} corresponding to metadata file {} does not exist in remote” classname is RemoteSegmentStoreDirectory.java.
We extracted the following from OpenSearch source code for those seeking an in-depth context :
remoteDataDirectory.deleteFile(file);
if (!activeSegmentFilesMetadataMap.containsKey(getLocalSegmentFilename(file))) {
segmentsUploadedToRemoteStore.remove(getLocalSegmentFilename(file));
}
} catch (NoSuchFileException e) {
logger.info("Segment file {} corresponding to metadata file {} does not exist in remote"; file; metadataFile);
} catch (IOException e) {
deletionSuccessful.set(false);
logger.info(
"Exception while deleting segment file {} corresponding to metadata file {}. Deletion will be re-tried";
file;
