Elasticsearch & Full Text Search Systems · Урок

Поиск фраз и близости

Узнайте, как искать точные фразы и слова на заданном расстоянии друг от друга с помощью параметров `match_phrase` и `slop`.

«Поиск фраз и близости» — бесплатный урок Elasticsearch & Full Text Search Systems на CoddyKit. Это урок 1 из 4. Ты можешь прочитать весь урок бесплатно ниже — а потом практиковать его прямо в браузере с встроенным редактором кода и ИИ-репетитором 24/7. Это часть пути обучения Elasticsearch & Full Text Search Systems, и твой прогресс синхронизируется между веб-версией и приложением CoddyKit. Курс Elasticsearch & Full Text Search Systems содержит 4 уроков всего.

Части этого урока еще не переведены и отображаются на английском.

Beyond Single Words

Welcome! So far, you've learned to search for individual words. But what if you need to find exact phrases like "quick brown fox" or words that appear close together?

This lesson introduces phrase and proximity searches, powerful techniques to make your searches more precise and relevant.

Finding Exact Phrases

Sometimes, the order of words matters. For example, "New York" is different from "York New". To find an exact sequence of words, we use a phrase query.

In Elasticsearch, the match_phrase query is perfect for this. It looks for all terms in your query string, in the exact order, and next to each other.

match_phrase Example

Let's see match_phrase in action. We'll simulate indexing a few documents and then search for the exact phrase "quick brown fox".

public class Main {
  public static void main(String[] args) {
    System.out.println("Simulating search for exact phrase 'quick brown fox'");
    System.out.println("on documents:");
    System.out.println("- 'The quick brown fox jumps.'");
    System.out.println("- 'A fox brown quick jumps.'");
    System.out.println("- 'Quick brown fox is fast.'");

    System.out.println("
--- Elasticsearch Query (simulated) ---");
    System.out.println("{");
    System.out.println("  \"query\": {");
    System.out.println("    \"match_phrase\": {");
    System.out.println("      \"text_field\": \"quick brown fox\"");
    System.out.println("    }");
    System.out.println("  }");
    System.out.println("}");

    System.out.println("
--- Search Results (simulated) ---");
    System.out.println("Document: 'The quick brown fox jumps.' (MATCH!)");
    System.out.println("Document: 'Quick brown fox is fast.' (MATCH!)");
    System.out.println("No match for 'A fox brown quick jumps.'");
  }
}

Phrase Matching Logic

The match_phrase query requires two conditions:

All terms present: Every word in your phrase ("quick", "brown", "fox") must exist in the document.
Exact order: The words must appear in the same sequence.
Contiguous: By default, the words must be right next to each other.

If any of these conditions aren't met, the document won't be considered a match.

Proximity Search with slop

What if you want to find words that are *close* to each other, but not necessarily an exact, contiguous phrase? This is where proximity search comes in.

Elasticsearch introduces the slop parameter for match_phrase queries. It allows for a certain number of "slops" or "gaps" between the words in your phrase.

Understanding slop

The slop parameter defines the maximum number of positions tokens can be "moved" to match the phrase.

slop: 0 (default) means words must be contiguous.
slop: 1 allows one word to be skipped or reordered slightly.
Higher slop values allow more flexibility in word order and distance.

Think of it as how many "moves" it takes to transform the document's words into your target phrase.

slop=1 Demonstration

Let's modify our previous search. We'll look for "quick fox" but allow for one word in between using "slop": 1.

public class Main {
  public static void main(String[] args) {
    System.out.println("Simulating search for 'quick fox' with slop: 1");
    System.out.println("on documents:");
    System.out.println("- 'The quick brown fox jumps.'");
    System.out.println("- 'A quick sly fox is here.'");
    System.out.println("- 'The quick fox is fast.'");

    System.out.println("
--- Elasticsearch Query (simulated) ---");
    System.out.println("{");
    System.out.println("  \"query\": {");
    System.out.println("    \"match_phrase\": {");
    System.out.println("      \"text_field\": {");
    System.out.println("        \"query\": \"quick fox\",");
    System.out.println("        \"slop\": 1");
    System.out.println("      }");
    System.out.println("    }");
    System.out.println("  }");
    System.out.println("}");

    System.out.println("
--- Search Results (simulated) ---");
    System.out.println("Document: 'The quick brown fox jumps.' (MATCH!)");
    System.out.println("Document: 'A quick sly fox is here.' (MATCH!)");
    System.out.println("Document: 'The quick fox is fast.' (MATCH!)");
  }
}

slop and Word Order

slop can also help match phrases where words are slightly reordered. For example, to match "brown quick" when searching for "quick brown" with slop: 1.

It measures the minimum number of moves to get the document's tokens into the query's token order. Each move counts as 1 slop unit.

public class Main {
  public static void main(String[] args) {
    System.out.println("Simulating search for 'quick brown' with slop: 1");
    System.out.println("on document:");
    System.out.println("- 'The brown quick fox.'"); // 'brown' and 'quick' are swapped

    System.out.println("
--- Elasticsearch Query (simulated) ---");
    System.out.println("{");
    System.out.println("  \"query\": {");
    System.out.println("    \"match_phrase\": {");
    System.out.println("      \"text_field\": {");
    System.out.println("        \"query\": \"quick brown\",");
    System.out.println("        \"slop\": 1");
    System.out.println("      }");
    System.out.println("    }");
    System.out.println("  }");
    System.out.println("}");

    System.out.println("
--- Search Results (simulated) ---");
    System.out.println("Document: 'The brown quick fox.' (MATCH!)");
    System.out.println("Explanation: To change 'brown quick' to 'quick brown', one move is needed (slop 1).");
  }
}

match_phrase vs. match

It's important to differentiate match_phrase from the basic match query you've seen before.

match query: Finds documents containing *any* of the words, regardless of order or proximity. It's good for general relevancy.
match_phrase query: Requires *all* words in the exact order and, by default, contiguous. With slop, it allows for controlled proximity. It's for high precision.

Choose match_phrase when the order and closeness of words are critical to your search.

Proximity Check

You want to find documents where "apple" and "pie" appear, with at most one word in between them, in that specific order.

Recap: Precise Searches

Great job! You've learned how to enhance your search precision:

match_phrase: For finding exact sequences of words.
slop parameter: To control the allowed distance and reordering between words in a phrase.

These techniques are crucial for building highly accurate and user-friendly search experiences. Keep practicing to master them!

Часто задаваемые вопросы

Урок «Поиск фраз и близости» бесплатный?

Да — полный текст урока «Поиск фраз и близости» бесплатно доступен здесь в веб-версии. Чтобы практиковать его интерактивно (встроенный редактор кода и ИИ-репетитор 24/7) и разблокировать остальной курс Elasticsearch & Full Text Search Systems, подпишись на CoddyKit PRO. Курс Elasticsearch & Full Text Search Systems содержит 4 уроков всего.

Чему я научусь в уроке «Поиск фраз и близости»?

Узнайте, как искать точные фразы и слова на заданном расстоянии друг от друга с помощью параметров `match_phrase` и `slop`. Ты практикуешь Elasticsearch & Full Text Search Systems с помощью реального кода, который запускаешь прямо в браузере, и ИИ-репетитор 24/7 отвечает на твои вопросы во время урока.

Нужен ли мне опыт, чтобы начать Elasticsearch & Full Text Search Systems?

Предыдущий опыт не требуется. Elasticsearch & Full Text Search Systems на CoddyKit структурирован для всех уровней — от новичков до продвинутых, поэтому ты можешь начать отсюда или с самого начала и учиться в своем темпе. Это урок 1 из 4.

Сколько времени занимает урок «Поиск фраз и близости»?

Большинство уроков CoddyKit занимают около 5–10 минут. Каждый из них компактный и интерактивный, поэтому ты постоянно делаешь прогресс и продолжаешь с того же места в веб-версии и приложении.

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Да. Каждый урок Elasticsearch & Full Text Search Systems включает встроенный редактор кода, поэтому ты пишешь и запускаешь реальный код прямо в браузере и получаешь моментальную обратную связь от AI — локальная установка не требуется.

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