REST API updates indexes, analyzer

Author: HeidiSteen

articles/search/index-add-custom-analyzers.md

@@ -132,7 +132,7 @@ The analyzer definition is a part of the larger index. Definitions for char filt
 
 ## Test custom analyzers
 
-You can use the [Test Analyzer (REST)](/rest/api/searchservice/test-analyzer) to see how an analyzer breaks given text into tokens.
+You can use the [Test Analyzer (REST)](/rest/api/searchservice/indexes/analyze) to see how an analyzer breaks given text into tokens.
 
 **Request**
 

articles/search/index-add-language-analyzers.md

@@ -37,7 +37,7 @@ A better experience is to search for individual words: 明るい (Bright), 私
 
 Azure AI Search supports 35 language analyzers backed by Lucene, and 50 language analyzers backed by proprietary Microsoft natural language processing technology used in Office and Bing.
 
-Some developers might prefer the more familiar, simple, open-source solution of Lucene. Lucene language analyzers are faster, but the Microsoft analyzers have advanced capabilities, such as lemmatization, word decompounding (in languages like German, Danish, Dutch, Swedish, Norwegian, Estonian, Finnish, Hungarian, Slovak) and entity recognition (URLs, emails, dates, numbers). If possible, you should run comparisons of both the Microsoft and Lucene analyzers to decide which one is a better fit. You can use [Analyze API](/rest/api/searchservice/test-analyzer) to see the tokens generated from a given text using a specific analyzer.
+Some developers might prefer the more familiar, simple, open-source solution of Lucene. Lucene language analyzers are faster, but the Microsoft analyzers have advanced capabilities, such as lemmatization, word decompounding (in languages like German, Danish, Dutch, Swedish, Norwegian, Estonian, Finnish, Hungarian, Slovak) and entity recognition (URLs, emails, dates, numbers). If possible, you should run comparisons of both the Microsoft and Lucene analyzers to decide which one is a better fit. You can use [Analyze API](/rest/api/searchservice/indexes/analyze) to see the tokens generated from a given text using a specific analyzer.
 
 Indexing with Microsoft analyzers is on average two to three times slower than their Lucene equivalents, depending on the language. Search performance shouldn't be significantly affected for average size queries. 
 

articles/search/index-add-suggesters.md

@@ -63,7 +63,7 @@ To satisfy both search-as-you-type experiences, add all of the fields that you n
 
 Your choice of an analyzer determines how fields are tokenized and prefixed. For example, for a hyphenated string like "context-sensitive", using a language analyzer results in these token combinations: "context", "sensitive", "context-sensitive". Had you used the standard Lucene analyzer, the hyphenated string wouldn't exist. 
 
-When evaluating analyzers, consider using the [Analyze Text API](/rest/api/searchservice/test-analyzer) for insight into how terms are processed. Once you build an index, you can try various analyzers on a string to view token output.
+When evaluating analyzers, consider using the [Analyze Text API](/rest/api/searchservice/indexes/analyze) for insight into how terms are processed. Once you build an index, you can try various analyzers on a string to view token output.
 
 Fields that use [custom analyzers](index-add-custom-analyzers.md) or [built-in analyzers](index-add-custom-analyzers.md#built-in-analyzers) (except for standard Lucene) are explicitly disallowed to prevent poor outcomes.
 

articles/search/query-lucene-syntax.md

@@ -184,7 +184,7 @@ Azure AI Search uses frequency-based scoring ([BM25](https://en.wikipedia.org/wi
 
 In some circumstances, you may want to search for a special character, like an '❤' emoji or the '€' sign. In such cases, make sure that the analyzer you use doesn't filter those characters out. The standard analyzer bypasses many special characters, excluding them from your index.
 
-Analyzers that tokenize special characters include the whitespace analyzer, which takes into consideration any character sequences separated by whitespaces as tokens (so the `❤` string would be considered a token). Also, a language analyzer like the Microsoft English analyzer ("en.microsoft"), would take the "€" string as a token. You can [test an analyzer](/rest/api/searchservice/test-analyzer) to see what tokens it generates for a given query.
+Analyzers that tokenize special characters include the whitespace analyzer, which takes into consideration any character sequences separated by whitespaces as tokens (so the `❤` string would be considered a token). Also, a language analyzer like the Microsoft English analyzer ("en.microsoft"), would take the "€" string as a token. You can [test an analyzer](/rest/api/searchservice/indexes/analyze) to see what tokens it generates for a given query.
 
 When using Unicode characters, make sure symbols are properly escaped in the query url (for instance for `❤` would use the escape sequence `%E2%9D%A4+`). Some REST clients do this translation automatically.  
 

articles/search/query-simple-syntax.md

@@ -50,7 +50,7 @@ Strings passed to the `search` parameter can include terms or phrases in any sup
 
 Depending on your search client, you might need to escape the quotation marks in a phrase search. For example, in a POST request, a phrase search on `"Roach Motel"` in the request body might be specified as `"\"Roach Motel\""`. If you're using the Azure SDKs, the search client escapes the quotation marks when it serializes the search text. Your search phrase can be sent be as "Roach Motel".
 
-By default, all strings passed in the `search` parameter undergo lexical analysis. Make sure you understand the tokenization behavior of the analyzer you're using. Often, when query results are unexpected, the reason can be traced to how terms are tokenized at query time. You can [test tokenization on specific strings](/rest/api/searchservice/test-analyzer) to confirm the output.
+By default, all strings passed in the `search` parameter undergo lexical analysis. Make sure you understand the tokenization behavior of the analyzer you're using. Often, when query results are unexpected, the reason can be traced to how terms are tokenized at query time. You can [test tokenization on specific strings](/rest/api/searchservice/indexes/analyze) to confirm the output.
 
 Any text input with one or more terms is considered a valid starting point for query execution. Azure AI Search will match documents containing any or all of the terms, including any variations found during analysis of the text.
 
@@ -111,7 +111,7 @@ If you need special character representation, you can assign an analyzer that pr
 
 + A [language analyzer](search-language-support.md), such as the Microsoft English analyzer (`en.microsoft`), would take the '$' or '€' string as a token. 
 
-For confirmation, you can [test an analyzer](/rest/api/searchservice/test-analyzer) to see what tokens are generated for a given string. As you might expect, you might not get full tokenization from a single analyzer. A workaround is to create multiple fields that contain the same content, but with different analyzer assignments (for example, `description_en`, `description_fr`, and so forth for language analyzers).
+For confirmation, you can [test an analyzer](/rest/api/searchservice/indexes/analyze) to see what tokens are generated for a given string. As you might expect, you might not get full tokenization from a single analyzer. A workaround is to create multiple fields that contain the same content, but with different analyzer assignments (for example, `description_en`, `description_fr`, and so forth for language analyzers).
 
 When using Unicode characters, make sure symbols are properly escaped in the query url (for instance for '❤' would use the escape sequence `%E2%9D%A4+`). Some web clients do this translation automatically.  
 

articles/search/reference-stopwords.md

@@ -25,7 +25,7 @@ This article lists the stopwords used by the Microsoft analyzer for each languag
 For the stopword list for Lucene analyzers, see the [Apache Lucene source code on GitHub](https://github.com/apache/lucene/tree/main/lucene/analysis/common/src/resources/org/apache/lucene/analysis).
 
 > [!TIP]
-> To view the output of any given analyzer, call the [Analyze Text REST API](/rest/api/searchservice/test-analyzer). This API is often helpful for debugging unexpected search results.
+> To view the output of any given analyzer, call the [Analyze Text REST API](/rest/api/searchservice/indexes/analyze). This API is often helpful for debugging unexpected search results.
 
 ## Arabic (ar.microsoft)
 

articles/search/search-analyzers.md

@@ -124,7 +124,7 @@ Overriding the standard analyzer requires an index rebuild. If possible, decide
 
 ### Inspect tokenized terms
 
-If a search fails to return expected results, the most likely scenario is token discrepancies between term inputs on the query, and tokenized terms in the index. If the tokens aren't the same, matches fail to materialize. To inspect tokenizer output, we recommend using the [Analyze API](/rest/api/searchservice/test-analyzer) as an investigation tool. The response consists of tokens, as generated by a specific analyzer.
+If a search fails to return expected results, the most likely scenario is token discrepancies between term inputs on the query, and tokenized terms in the index. If the tokens aren't the same, matches fail to materialize. To inspect tokenizer output, we recommend using the [Analyze API](/rest/api/searchservice/indexes/analyze) as an investigation tool. The response consists of tokens, as generated by a specific analyzer.
 
 <a name="examples"></a>
 

articles/search/search-howto-create-indexers.md

@@ -147,7 +147,7 @@ Indexers also require a search index. Recall that indexers pass data off to the
 
    Indexers can automatically map source fields to target index fields when the names and types are equivalent. If a field can't be implicitly mapped, remember that you can [define an explicit field mapping](search-indexer-field-mappings.md) that tells the indexer how to route the content.
 
-1. Review the analyzer assignments on each field. Analyzers can transform strings. As such, indexed strings might be different from what you passed in. You can evaluate the effects of analyzers using [Analyze Text (REST)](/rest/api/searchservice/test-analyzer). For more information about analyzers, see [Analyzers for text processing](search-analyzers.md).
+1. Review the analyzer assignments on each field. Analyzers can transform strings. As such, indexed strings might be different from what you passed in. You can evaluate the effects of analyzers using [Analyze Text (REST)](/rest/api/searchservice/indexes/analyze). For more information about analyzers, see [Analyzers for text processing](search-analyzers.md).
 
 During indexing, an indexer only checks field names and types. There's no validation step that ensures incoming content is correct for the corresponding search field in the index.
 

articles/search/search-lucene-query-architecture.md

@@ -159,7 +159,7 @@ When the default analyzer processes the term, it will lowercase "ocean view" and
 
 ### Testing analyzer behaviors 
 
-The behavior of an analyzer can be tested using the [Analyze API](/rest/api/searchservice/test-analyzer). Provide the text you want to analyze to see what terms given analyzer generates. For example, to see how the standard analyzer would process the text "air-condition", you can issue the following request:
+The behavior of an analyzer can be tested using the [Analyze API](/rest/api/searchservice/indexes/analyze). Provide the text you want to analyze to see what terms given analyzer generates. For example, to see how the standard analyzer would process the text "air-condition", you can issue the following request:
 
 ```json
 {

articles/search/search-query-create.md

@@ -165,7 +165,7 @@ For field attribute definitions, see [Create Index (REST API)](/rest/api/searchs
 
 During indexing, the search engine uses a text analyzer on strings to maximize the potential for finding a match at query time. At a minimum, strings are lower-cased, but depending on the analyzer, might also undergo lemmatization and stop word removal. Larger strings or compound words are typically broken up by whitespace, hyphens, or dashes, and indexed as separate tokens. 
 
-The point to take away here's that what you think your index contains, and what's actually in it, can be different. If queries don't return expected results, you can inspect the tokens created by the analyzer through the [Analyze Text (REST API)](/rest/api/searchservice/test-analyzer). For more information about tokenization and the impact on queries, see [Partial term search and patterns with special characters](search-query-partial-matching.md).
+The point to take away here's that what you think your index contains, and what's actually in it, can be different. If queries don't return expected results, you can inspect the tokens created by the analyzer through the [Analyze Text (REST API)](/rest/api/searchservice/indexes/analyze). For more information about tokenization and the impact on queries, see [Partial term search and patterns with special characters](search-query-partial-matching.md).
 
 ## Next steps