Index in Elasticsearch

What it is:

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 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:

DELETE /*

action.destructive_requires_name: true

Recovery in Elasticsearch

What it is:

In Elasticsearch, recovery refers to the process of recovering an index or shard when something goes wrong. There are many ways to recover an index or shard, such as by re-indexing the data from a backup / failover cluster to the current one, or by restoring from an Elasticsearch snapshot. Alternatively, Elasticsearch performs recoveries automatically, such as when a node restarts or disconnects and connects again. There is an API to check the updated status of index/shard recoveries.

GET /<index>/_recoveryGET /_recovery

In summary, recovery can happen in the following scenarios:

• Node startup or failure ( local store recovery )
• Replication of primary shards to replica shards
• Relocation of a shard to a different node in the same cluster
• Restoring a Snapshot

Examples:

Getting recovery information about several indices:

GET my_index1,my_index2/_recovery

Common problems related to recovery settings:

• When a node is disconnected from the cluster, all of its shards go to an unassigned state. After a certain amount of time, the shards will be allocated somewhere else on other nodes. This setting determines the number of concurrent shards per node that will be recovered.

PUT _cluster/settings{"transient":{"cluster.routing.allocation.node_concurrent_recoveries":3}}

• You can also control when to start recovery after a node disconnects. This is useful if the node just restarts, for example, because you may not want to initiate any recovery for such transient events.

PUT _all/_settings{"settings":{"index.unassigned.node_left.delayed_timeout":"6m"}}

• Elasticsearch limits the speed that is allocated to recovery in order to avoid overloading the cluster. This setting can be updated to make the recovery faster or slower, depending on your requirements.

PUT _cluster/settings{"transient":{"indices.recovery.max_bytes_per_sec":"100mb"}}

Source in Elasticsearch

What it is:

When a document is sent to for indexing, Elasticsearch indexes all the fields in the format of 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.