How To Solve Issues Related to Log – Index blob is not valid x-content bytes

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Updated: Jan-20

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Troubleshooting background

To troubleshoot Elasticsearch log “Index blob is not valid x-content bytes” it’s important to understand common problems related to Elasticsearch concepts: blobstore, index, repositories, repository-azure. See detailed explanations below complete with common problems, examples and useful tips.

Index in Elasticsearch

What it is

In Elasticsearch, an index (indices in plural) can be thought of as a table inside a database that has 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 below command:

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

Repository in Elasticsearch

What it is

An Elasticsearch snapshot provides a backup mechanism that takes the current state and data in the cluster and saves it to a repository (read the Glossary term Snapshot for more information). The backup process requires a repository to be created first. The repository needs to be registered using the _snapshot endpoint, and multiple repositories per cluster can be created. The following repository types are supported. 

Repository Types:
Repository TypeConfiguration Type
Shared file systemType: “fs”
S3Type : “s3”
HDFSType :“hdfs”
AzureType: “azure”
Google Cloud StorageType : “gcs”
Examples

To register a repository of type fs:

PUT _snapshot/my_repo_01
{
"type": "fs",
"settings": {
"location": "/mnt/my_repo_dir"
  }
}
Notes and common problems
  • S3, HDFS , Azure and Google Cloud requires a relevant plugin to be installed before it can be used for a snapshot.
  • The setting, path.repo: /mnt/my_repo_dir needs to be added to elasticsearch.yml on all the nodes in case you are planning to use repo type of file system otherwise it will fail
  • In case of using remote repositories , the network bandwidth and repository storage throughput should be high enough to complete the snapshot operations normally , otherwise you will end up in partial snapshots.


To help troubleshoot related issues we have gathered selected Q&A from the community and issues from Github , please review the following for further information :

1 AJAX Call with Elasticsearch Search 16.97 K 14

2Github Issue Number 37005  

Index Binary Blob File With Nest/60


Log Context

Log ”[{}] index blob is not valid x-content [{} bytes]” classname is BlobStoreRepository.java
We have extracted the following from Elasticsearch source code to get an in-depth context :

                 // EMPTY is safe here because RepositoryData#fromXContent calls namedObject
                try (XContentParser parser = XContentHelper.createParser(NamedXContentRegistry.EMPTY;
                    LoggingDeprecationHandler.INSTANCE; out.bytes(); XContentType.JSON)) {
                    repositoryData = RepositoryData.snapshotsFromXContent(parser; indexGen);
                } catch (NotXContentException e) {
                    logger.warn("[{}] index blob is not valid x-content [{} bytes]"; snapshotsIndexBlobName; out.bytes().length());
                    throw e;
                }
            }

            // now load the incompatible snapshot ids; if they exist






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