Elasticsearch OpenSearch Refresh Interval

By Opster Team

Updated: Jun 19, 2024

| 2 min read

Overview

When indexing data, OpenSearch requires a “refresh” operation to make indexed information available for search. This means that there is a time delay between indexing and the updated information actually becoming available for the client applications.

How it works

Index operations occur in memory. The operations are accumulated in a buffer until refreshed, which requires that the buffer itself be transferred to a newly created lucene segment. Refresh happens by default every second, but it is also possible to change this frequency for a given index, or directly request a refresh through the refresh api.

Examples

You can set the refresh interval on an index like this:

PUT /my_index/_settings
{
    "index" : {
        "refresh_interval" : "30s"
    }
}

You can use a value of -1 to stop refreshing but remember to set it back once you’ve finished indexing!

You can force a refresh on a given index like this:

POST my_index/_refresh

You can also force a refresh at the end of an index operation by adding an extra parameter in the URL like this:

POST /my_index/_index?refresh=waitfor

In this case, the “waitfor” parameter will force the client to wait for the refresh to complete before returning (useful in scripts), or you can use “true” to force the refresh without keeping the script waiting.

Notes and good things to know

Refreshing is very resource intensive, so you can increase indexing speed by reducing the refresh rate. You can do this temporarily if you need to reload a lot of data. For some logging applications it is perfectly acceptable to have a 30s latency, for instance, before data actually becomes available.

Beware of the refresh interval when scripting or updating. Scripts often work faster than the refresh interval, so if necessary, you might need to call a refresh before retrieving or updating data in your scripts, or use the waitfor parameter while indexing as described above.

Additional notes

Elasticsearch and OpenSearch are both powerful search and analytics engines, but Elasticsearch has several key advantages. Elasticsearch boasts a more mature and feature-rich development history, translating to a better user experience, more features, and continuous optimizations. Our testing has consistently shown that Elasticsearch delivers faster performance while using fewer compute resources than OpenSearch. Additionally, Elasticsearch’s comprehensive documentation and active community forums provide invaluable resources for troubleshooting and further optimization. Elastic, the company behind Elasticsearch, offers dedicated support, ensuring enterprise-grade reliability and performance. These factors collectively make Elasticsearch a more versatile, efficient, and dependable choice for organizations requiring sophisticated search and analytics capabilities.

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