Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Indexing data in Amazon OpenSearch Service

Because Amazon OpenSearch Service uses a REST API, numerous methods exist for indexing documents. You can use standard clients like curl or any programming language that can send HTTP requests. To further simplify the process of interacting with it, OpenSearch Service has clients for many programming languages. Advanced users can skip directly to Loading streaming data into Amazon OpenSearch Service.

We strongly recommend that you use Amazon OpenSearch Ingestion to ingest data, which is a fully managed data collector built within OpenSearch Service. For more information, see Amazon OpenSearch Ingestion.

For an introduction to indexing, see the OpenSearch documentation.

Naming restrictions for indexes

OpenSearch Service indexes have the following naming restrictions:

Don't include sensitive information in index, type, or document ID names. OpenSearch Service uses these names in its Uniform Resource Identifiers (URIs). Servers and applications often log HTTP requests, which can lead to unnecessary data exposure if URIs contain sensitive information:

2018-10-03T23:39:43 198.51.100.14 200 "GET https://opensearch-domain/dr-jane-doe/flu-patients-2018/202-555-0100/ HTTP/1.1"

Even if you don't have permissions to view the associated JSON document, you could infer from this fake log line that one of Dr. Doe's patients with a phone number of 202-555-0100 had the flu in 2018.

If OpenSearch Service detects a real or percieved IP address in an index name (for example, my-index-12.34.56.78.91), it masks the IP address. A call to _cat/indices yields the following response:

green open my-index-x.x.x.x.91    soY19tBERoKo71WcEScidw 5 1 0 0   2kb  1kb

To prevent unnecessary confusion, avoid including IP addresses in index names.

Reducing response size

Responses from the _index and _bulk APIs contain quite a bit of information. This information can be useful for troubleshooting requests or for implementing retry logic, but can use considerable bandwidth. In this example, indexing a 32 byte document results in a 339 byte response (including headers):

PUT opensearch-domain/more-movies/_doc/1
{"title": "Back to the Future"}

Response

{
  "_index": "more-movies",
  "_type": "_doc",
  "_id": "1",
  "_version": 4,
  "result": "updated",
  "_shards": {
    "total": 2,
    "successful": 2,
    "failed": 0
  },
  "_seq_no": 3,
  "_primary_term": 1
}

This response size might seem minimal, but if you index 1,000,000 documents per day—approximately 11.5 documents per second—339 bytes per response works out to 10.17 GB of download traffic per month.

If data transfer costs are a concern, use the filter_path parameter to reduce the size of the OpenSearch Service response, but be careful not to filter out fields that you need in order to identify or retry failed requests. These fields vary by client. The filter_path parameter works for all OpenSearch Service REST APIs, but is especially useful with APIs that you call frequently, such as the _index and _bulk APIs:

PUT opensearch-domain/more-movies/_doc/1?filter_path=result,_shards.total
{"title": "Back to the Future"}

Response

{
  "result": "updated",
  "_shards": {
    "total": 2
  }
}

Instead of including fields, you can exclude fields with a - prefix. filter_path also supports wildcards:

POST opensearch-domain/_bulk?filter_path=-took,-items.index._*
{ "index": { "_index": "more-movies", "_id": "1" } }
{"title": "Back to the Future"}
{ "index": { "_index": "more-movies", "_id": "2" } }
{"title": "Spirited Away"}

Response

{
  "errors": false,
  "items": [
    {
      "index": {
        "result": "updated",
        "status": 200
      }
    },
    {
      "index": {
        "result": "updated",
        "status": 200
      }
    }
  ]
}

Index codecs

Index codecs determine how the stored fields on an index are compressed and stored on disk. The index codec is controlled by the static index.codec setting, which specifies the compression algorithm. This setting impacts the index shard size and operation performance.

For a list of supported codecs and their performance characteristics, see Supported codecs in the OpenSearch documentation.

When you choose an index codec, consider the following: