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Adjusting named anchor. #2702

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Apr 2, 2024
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Adjusting named anchor. #2702

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2 changes: 1 addition & 1 deletion _posts/2024-04-02-2.13-is-ready-for-download.md
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Expand Up @@ -27,7 +27,7 @@ The [OpenSearch Assistant Toolkit](https://opensearch.org/docs/latest/ml-commons
OpenSearch provides the ability to integrate with LLMs to power generative AI use cases. LLMs can potentially generate harmful content, so for this release, the OpenSearch [agent framework](https://opensearch.org/docs/latest/ml-commons-plugin/agents-tools/index/) adds support for [user-defined regex rules](https://opensearch.org/docs/latest/ml-commons-plugin/remote-models/guardrails/) or word lists to filter inappropriate text generation that could be produced by integrated LLMs.

### Apply aggregations to hybrid search results
[Hybrid search](https://opensearch.org/docs/latest/search-plugins/hybrid-search/) combines results from lexical and neural search, providing more relevant results than either one separately. OpenSearch now offers the ability to [post-filter](https://opensearch.org/docs/latest/search-plugins/hybrid-search/#combining-hybrid-search-and-aggregations/) the combined results and to apply aggregations to them to support use cases such as faceting.
[Hybrid search](https://opensearch.org/docs/latest/search-plugins/hybrid-search/) combines results from lexical and neural search, providing more relevant results than either one separately. OpenSearch now offers the ability to [post-filter](https://opensearch.org/docs/latest/search-plugins/hybrid-search/#combining-hybrid-search-and-aggregations) the combined results and to apply aggregations to them to support use cases such as faceting.

### Query and manage external data sources more efficiently
OpenSearch community members looking to optimize costs can find themselves storing infrequently queried data outside of OpenSearch in object stores. In the 2.9 release, we introduced data sources, which allow you to create a new Apache Spark data source type to directly query object stores. For those who wanted to [increase query performance](https://opensearch.org/docs/latest/dashboards/management/accelerate-external-data/), we released skipping indexes (in the 2.9 release) to speed up direct queries as well as materialized views and covering indexes (both in the 2.11 release) to ingest data directly into OpenSearch indexes. In the 2.13 release, we’ve added a new skipping index type, [Bloom filter](https://opensearch.org/docs/latest/install-and-configure/configuring-opensearch/index-settings/), which is more efficient for data types like IP addresses and hostnames that have many different values that can be stored. In addition, we’ve made improvements to the [data sources experience](https://opensearch.org/docs/latest/dashboards/management/multi-data-sources/), where community members can now manage tables and accelerations visually instead of using SQL statements in [Query Workbench](https://opensearch.org/docs/latest/dashboards/query-workbench/). In upcoming releases, we will improve the querying experience as we merge observability logs functionality into [Discover](https://opensearch.org/docs/latest/dashboards/discover/index-discover/).
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