Deleting Index – How to solve related issues

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Deleting Index – How to solve related issues

Opster Team

Feb-22, Version: 1.7-8.0

Before you begin reading this guide, we recommend you run Elasticsearch Error Check-Up that will review your configuration and resolve issues that cause many errors.

This guide will explain what causes the log “deleting index” to appear and how to resolve this.

Background

To learn about indices in Elasticsearch, read this guide: Elasticsearch Index.

What does this message mean?

When you use the DELETE API, you’ll see the following logs:

[2022-02-12T13:15:46,541][INFO ][o.e.c.m.MetadataDeleteIndexService] [opster] [my_index/gnQA70A1TVWFns7Yp2728Q] deleting index

This is an INFO message informing you that the index `my_index` is being removed from the node.

It’s very important to know that If you don’t have a snapshot or backup set up, you won’t be able to recover the index once it’s been removed.

How to reproduce this log

Make sure your Elasticsearch instance is running before proceeding with the following steps.

Create index:

Using the PUT API, create an index (let’s call it `my_index`):

PUT /my_index

Delete index:

The next step is to use the DELETE API to delete the index:

DELETE /my_index

Log Context

Log “{} Deleting Index” classname is MetaDataDeleteIndexService.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :

 
        final IndexGraveyard.Builder graveyardBuilder = IndexGraveyard.builder(metaDataBuilder.indexGraveyard());
        final int previousGraveyardSize = graveyardBuilder.tombstones().size();
        for (final Index index : indices) {
            String indexName = index.getName();
            logger.info("{} deleting index"; index);
            routingTableBuilder.remove(indexName);
            clusterBlocksBuilder.removeIndexBlocks(indexName);
            metaDataBuilder.remove(indexName);
        }
        // add tombstones to the cluster state for each deleted index




 

Run the Check-Up to get customized insights on your system:

Overview

In Elasticsearch, an index (plural: indices) 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

Log Context

Log “{} Deleting Index” classname is MetaDataDeleteIndexService.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :

 
        final IndexGraveyard.Builder graveyardBuilder = IndexGraveyard.builder(metaDataBuilder.indexGraveyard());
        final int previousGraveyardSize = graveyardBuilder.tombstones().size();
        for (final Index index : indices) {
            String indexName = index.getName();
            logger.info("{} deleting index"; index);
            routingTableBuilder.remove(indexName);
            clusterBlocksBuilder.removeIndexBlocks(indexName);
            metaDataBuilder.remove(indexName);
        }
        // add tombstones to the cluster state for each deleted index




 

Run the Check-Up to get customized insights on your system:

Analyze your cluster

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