# `AshScylla.Search.Analyzer`
[🔗](https://github.com/ohhi-vn/ash_scylla/blob/main/lib/ash_scylla/search/analyzer.ex#L1)

Text analysis pipeline coordinator.

Orchestrates the full text analysis pipeline:

    Document text
      → Tokenizer (split into words)
      → Normalizer (lowercase, strip punctuation, NFC normalize)
      → Stop Words filter (remove common words)
      → Stemmer (reduce to root form)
      → Unique terms with counts

## Usage

    iex> Analyzer.analyze("Learning Elixir Phoenix Framework")
    [{"phoenix", 1}, {"framework", 1}, {"learn", 1}, {"elixir", 1}]

The result is a keyword list of `{term, frequency}` pairs ready for
indexing or query processing.

# `analyze`

```elixir
@spec analyze(
  String.t(),
  keyword()
) :: [{String.t(), pos_integer()}]
```

Analyzes text and returns a list of `{term, term_frequency}` tuples.

The terms are:
  1. Tokenized from the input text
  2. Normalized (lowercase, punctuation removal, NFC)
  3. Filtered to remove stop words
  4. Stemmed to their root form
  5. Deduplicated with frequency counts

## Options
  * `:stem` — whether to apply stemming (default: `true`)
  * `:remove_stop_words` — whether to remove stop words (default: `true`)
  * `:min_length` — minimum token length (default: `1`)

## Examples

    iex> Analyzer.analyze("The Phoenix Framework is running fast")
    [{"phoenix", 1}, {"framework", 1}, {"run", 1}, {"fast", 1}]

# `analyze_fields`

```elixir
@spec analyze_fields(
  %{optional(atom()) => String.t()},
  keyword()
) :: [{String.t(), pos_integer()}]
```

Analyzes a map of field names to text values.

Returns a single merged term-frequency list across all fields.
Each field is analyzed independently and results are merged.

## Examples

    iex> Analyzer.analyze_fields(%{
    ...>   title: "Learning Elixir",
    ...>   body: "Elixir is great"
    ...> })
    [{"elixir", 2}, {"learn", 1}, {"great", 1}]

# `analyze_query`

```elixir
@spec analyze_query(
  String.t(),
  keyword()
) :: [String.t()]
```

Analyzes a query string for search.

Unlike document analysis, query analysis preserves the term order
for phrase search support. Returns a flat list of normalized terms.

## Examples

    iex> Analyzer.analyze_query("learning phoenix framework")
    ["learn", "phoenix", "framework"]

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*Consult [api-reference.md](api-reference.md) for complete listing*