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Elasticsearch & Full Text Search Systems · Aula

Buscas por frase e proximidade

Descubra como buscar frases exatas e palavras dentro de determinada proximidade usando os parâmetros `match_phrase` e `slop`.

Buscas por frase e proximidade é uma aula grátis de Elasticsearch & Full Text Search Systems no CoddyKit. Esta é a aula 1 de 4. Você pode ler a aula completa abaixo gratuitamente — depois pratica ao vivo no navegador com um editor de código integrado e um tutor de IA 24/7. Faz parte do caminho de aprendizado de Elasticsearch & Full Text Search Systems, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de Elasticsearch & Full Text Search Systems inclui 4 aulas no total.

Partes desta aula ainda não foram traduzidas e aparecem em inglês.

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!

Perguntas Frequentes

A aula “Buscas por frase e proximidade” é grátis?

Sim — o texto completo de “Buscas por frase e proximidade” é grátis para ler aqui na web. Para praticá-la interativamente (um editor de código integrado e um tutor de IA 24/7) e desbloquear o restante do curso de Elasticsearch & Full Text Search Systems, atualize para CoddyKit PRO. O curso de Elasticsearch & Full Text Search Systems inclui 4 aulas no total.

O que vou aprender em “Buscas por frase e proximidade”?

Descubra como buscar frases exatas e palavras dentro de determinada proximidade usando os parâmetros `match_phrase` e `slop`. Você pratica Elasticsearch & Full Text Search Systems com código prático que executa diretamente no navegador, e um tutor de IA 24/7 responde suas dúvidas enquanto trabalha na aula.

Preciso ter experiência prévia para começar Elasticsearch & Full Text Search Systems?

Nenhuma experiência prévia é necessária. Elasticsearch & Full Text Search Systems no CoddyKit é estruturado para alunos iniciantes até avançados, então você pode começar aqui ou desde o início e aprender no seu ritmo. Esta é a aula 1 de 4.

Quanto tempo leva a aula “Buscas por frase e proximidade”?

A maioria das aulas CoddyKit leva cerca de 5–10 minutos. Cada uma é compacta e interativa, então você faz progresso constante e retoma exatamente de onde parou entre web e app.

Posso escrever e executar código nesta aula de Elasticsearch & Full Text Search Systems?

Sim. Cada aula de Elasticsearch & Full Text Search Systems inclui um editor de código integrado, então você escreve e executa código real direto no navegador e recebe feedback de IA instantaneamente — nenhuma configuração local necessária.

Todas as aulas deste curso

  1. Buscas por frase e proximidade
  2. Consultas aproximadas e com curingas
  3. Realce dos resultados da busca
  4. Agregações para pesquisa facetada
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