Ricerche per frase e prossimità
Scopra come cercare frasi esatte e parole entro una determinata prossimità usando i parametri `match_phrase` e `slop`.
Ricerche per frase e prossimità è una lezione Elasticsearch & Full Text Search Systems gratuita su CoddyKit. Questa è la lezione 1 di 4. Puoi leggere la lezione completa qui gratuitamente — poi esercitati direttamente nel browser con un editor di codice integrato e un tutor IA disponibile 24/7. Fa parte del percorso di apprendimento Elasticsearch & Full Text Search Systems, e i tuoi progressi si sincronizzano tra il web e l'app CoddyKit. Il corso Elasticsearch & Full Text Search Systems include 4 lezioni in totale.
Parti di questa lezione non sono ancora state tradotte e vengono mostrate in inglese.
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: 1allows one word to be skipped or reordered slightly.- Higher
slopvalues 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.
matchquery: Finds documents containing *any* of the words, regardless of order or proximity. It's good for general relevancy.match_phrasequery: Requires *all* words in the exact order and, by default, contiguous. Withslop, 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.slopparameter: 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!
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- Corsi
- 12
- Lezioni
- 48
Domande Frequenti
La lezione «Ricerche per frase e prossimità» è gratuita?
Sì — il testo completo di «Ricerche per frase e prossimità» è gratuito qui sul web. Per esercitarvi in modo interattivo (un editor di codice integrato e un tutor IA 24/7) e sbloccare il resto del corso Elasticsearch & Full Text Search Systems, passa a CoddyKit PRO. Il corso Elasticsearch & Full Text Search Systems include 4 lezioni in totale.
Cosa imparerò in «Ricerche per frase e prossimità»?
Scopra come cercare frasi esatte e parole entro una determinata prossimità usando i parametri `match_phrase` e `slop`. Eserciti Elasticsearch & Full Text Search Systems con codice pratico che esegui direttamente nel browser, e un tutor IA 24/7 risponde alle tue domande mentre lavori sulla lezione.
Ho bisogno di esperienza per iniziare Elasticsearch & Full Text Search Systems?
Non è richiesta alcuna esperienza precedente. Elasticsearch & Full Text Search Systems su CoddyKit è strutturato per principianti e studenti avanzati, quindi puoi iniziare da qui o dall'inizio e procedere al tuo ritmo. Questa è la lezione 1 di 4.
Quanto tempo richiede la lezione «Ricerche per frase e prossimità»?
La maggior parte delle lezioni CoddyKit richiede circa 5–10 minuti. Ogni lezione è breve e interattiva, quindi fai progressi costanti e riprendi esattamente da dove hai lasciato su web e app.
Posso scrivere ed eseguire codice in questa lezione Elasticsearch & Full Text Search Systems?
Sì. Ogni lezione Elasticsearch & Full Text Search Systems include un editor di codice integrato, quindi scrivi ed esegui codice reale direttamente nel tuo browser e ricevi feedback istantaneo dall'IA — nessuna configurazione locale necessaria.
Tutte le lezioni di questo corso
- Ricerche per frase e prossimità
- Query fuzzy e wildcard
- Evidenziazione dei risultati di ricerca
- Aggregazioni per la ricerca a faccette