Before you begin reading this guide, we recommend you try running the Elasticsearch Error Check-Up which can resolve issues that cause many errors.
This guide will help you check for common problems that cause the log ” Updating index.codec from to ” to appear. It’s important to understand the issues related to the log, so to get started, read the general overview on common issues and tips related to the Elasticsearch concepts: index.
Advanced users might want to skip right to the common problems section in each concept or try running the Check-Up which analyses ES to pinpoint the cause of many errors and provides suitable actionable recommendations how to resolve them (free tool that requires no installation).
Overview
In Elasticsearch, an index (plural: indices) can be thought of as a table inside a database. An index 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 “updating index.codec from [{}] to [{}]” classname is InternalEngine.java
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
InternalEngine.this.indexConcurrency = indexConcurrency;
// we have to flush in this case; since it only applies on a new index writer
requiresFlushing = true;
}
if (!codecName.equals(InternalEngine.this.codecName)) {
logger.info("updating index.codec from [{}] to [{}]"; InternalEngine.this.codecName; codecName);
InternalEngine.this.codecName = codecName;
// we want to flush in this case; so the new codec will be reflected right away...
requiresFlushing = true;
}
if (failOnMergeFailure != InternalEngine.this.failOnMergeFailure) {
