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Building a Search System with Filtering and Pagination

Learn how to build a scalable search system in Laravel and Vue.js that supports multi-model searching, filtering, pagination, and performance optimizations.

Published

Mon Oct 27 2025

Technologies Used

Laravel Vue.js Inertia.js PostgreSQL SQL PHP
Intermediate 44 minutes

Purpose

The Problem

Your application has thousands of records across multiple models: users, posts, products, articles. Users need to find specific content quickly. A naive search implementation looks like this:

// ❌ NAIVE APPROACH - Slow and inflexible
public function search(Request $request)
{
    $query = $request->get('q');
    
    // Searches everything, returns everything
    $results = Post::where('title', 'LIKE', "%{$query}%")
        ->orWhere('content', 'LIKE', "%{$query}%")
        ->get(); // No pagination!
    
    return view('search', ['results' => $results]);
}

Problems:

  • Performance nightmare: Full table scans on large datasets
  • No filtering: Can’t narrow results by category, date, or type
  • Memory issues: Loading thousands of results crashes the page
  • Poor UX: No pagination, no result counts, no sorting options
  • Case sensitivity: Misses results due to case differences
  • Single model: Can’t search across multiple content types

The Solution

A production-ready search system that handles:

  • Multi-model search: Search across groups, idols, albums, songs, users, and variety shows
  • Efficient queries: Case-insensitive search with proper indexing
  • Smart pagination: Limit results per category, lazy loading
  • Type filtering: Filter by content type (groups only, songs only, etc.)
  • Result ranking: Most relevant results first
  • Empty state handling: Graceful handling of no results

What we’re building: The universal search system from MyKpopLists that searches 6 different models simultaneously, returns categorized results, and handles edge cases like empty queries and special characters.

This tutorial demonstrates query optimization, N+1 prevention, pagination strategies, and building scalable search features—skills essential for senior backend engineers.

Prerequisites & Tooling

Knowledge Base

  • Laravel Eloquent: Advanced query building, relationships, eager loading
  • Database Indexing: Understanding of database indexes for performance
  • SQL: LIKE queries, LOWER() function, query optimization
  • Vue 3: Reactive search UI, debouncing, infinite scroll

Environment Setup

# Ensure database indexes exist for search columns
php artisan migrate

# Optional: Install Laravel Scout for full-text search (advanced)
composer require laravel/scout

Database Indexes for Performance

// Migration: Add indexes to searchable columns
Schema::table('groups', function (Blueprint $table) {
    $table->index('name'); // Speed up LIKE queries
});

Schema::table('idols', function (Blueprint $table) {
    $table->index('stage_name');
    $table->index('birth_name');
});

Schema::table('albums', function (Blueprint $table) {
    $table->index('title');
});

Schema::table('songs', function (Blueprint $table) {
    $table->index('title');
});

Why indexes matter: Without indexes, searching 100,000 songs requires a full table scan (slow). With indexes, the database uses a B-tree structure to find matches in milliseconds.

High-Level Architecture

Search System Flow

graph TD
    A[User Types Query] --> B{Query Length Check}
    B -->|< 2 chars| C[Return Empty]
    B -->|>= 2 chars| D[Normalize Query]
    
    D --> E[Parallel Model Searches]
    
    E --> F1[Search Groups]
    E --> F2[Search Idols]
    E --> F3[Search Albums]
    E --> F4[Search Songs]
    E --> F5[Search Variety Shows]
    E --> F6[Search Users]
    
    F1 --> G[Limit 5 per category]
    F2 --> G
    F3 --> G
    F4 --> G
    F5 --> G
    F6 --> G
    
    G --> H[Transform to Unified Format]
    H --> I[Combine Results]
    I --> J[Return JSON Response]
    
    J --> K[Vue Component]
    K --> L[Categorized Display]

Think of the search system as a library with multiple sections:

  1. Query Normalization: Clean and prepare the search term (lowercase, trim)
  2. Parallel Searches: Each model is a “section” searched independently
  3. Result Limiting: Take top 5 from each section to prevent overwhelming results
  4. Unified Format: Transform different models into a common structure
  5. Categorized Display: Present results grouped by type

Key Insight: Instead of one massive query, we run multiple focused queries in parallel, then combine results. This is faster and more maintainable than complex JOIN operations.

The Implementation

The Universal Search Controller

Let’s build the search controller step by step:

<?php

namespace App\Http\Controllers;

use App\Models\Album;
use App\Models\Group;
use App\Models\Idol;
use App\Models\Song;
use App\Models\User;
use App\Models\VarietyShow;
use Illuminate\Http\Request;

class SearchController extends Controller
{
    /**
     * Universal search across all content types.
     * 
     * Searches through groups, idols, albums, songs, variety shows, and users.
     * Returns up to 25 results total (5 per category) with type information
     * and navigation URLs for each result.
     */
    public function search(Request $request)
    {
        $query = $request->get('q', '');
        
        // Early return for empty queries
        if (empty(trim($query))) {
            return response()->json([
                'results' => [],
                'total' => 0
            ]);
        }

        // Normalize search term: lowercase for case-insensitive search
        $searchTerm = '%' . strtolower($query) . '%';
        
        // Search each model and combine results
        $results = $this->searchAllModels($searchTerm);

        return response()->json([
            'results' => $results->values(), // Re-index array
            'total' => $results->count(),
            'query' => $query
        ]);
    }
}

Key Decisions:

  • Early return: Avoid unnecessary database queries for empty input
  • Case-insensitive: Use strtolower() with LOWER() in SQL
  • Wildcard wrapping: %term% matches anywhere in the string
  • JSON response: Works with both Inertia and API requests

Searching Individual Models

Let’s implement search for each model type:

/**
 * Search all models and combine results.
 */
protected function searchAllModels(string $searchTerm)
{
    // Search Groups
    $groups = Group::whereRaw('LOWER(name) LIKE ?', [$searchTerm])
        ->limit(5)
        ->get()
        ->map(function ($group) {
            return [
                'id' => $group->id,
                'type' => 'group',
                'title' => $group->name,
                'image' => $group->image_url,
                'url' => route('groups.show', $group),
                'description' => $group->description 
                    ? substr($group->description, 0, 100) . '...' 
                    : null,
            ];
        });

    // Search Idols (multiple name fields)
    $idols = Idol::where(function ($q) use ($searchTerm) {
            $q->whereRaw('LOWER(birth_name) LIKE ?', [$searchTerm])
              ->orWhereRaw('LOWER(stage_name) LIKE ?', [$searchTerm]);
        })
        ->with('groups') // Eager load to prevent N+1
        ->limit(5)
        ->get()
        ->map(function ($idol) {
            return [
                'id' => $idol->id,
                'type' => 'idol',
                'title' => $idol->stage_name ?: $idol->birth_name,
                'subtitle' => $idol->groups->pluck('name')->join(', '),
                'image' => $idol->image_url,
                'url' => route('idols.show', $idol),
            ];
        });

    // Search Albums (with artist relationship)
    $albums = Album::whereRaw('LOWER(title) LIKE ?', [$searchTerm])
        ->withArtist() // Custom scope to load group or idol
        ->limit(5)
        ->get()
        ->map(function ($album) {
            return [
                'id' => $album->id,
                'type' => 'album',
                'title' => $album->title,
                'subtitle' => $album->artist ? $album->artist->name : null,
                'image' => $album->cover_image_url,
                'url' => route('albums.show', $album),
            ];
        });

    // Search Songs (with album and artist)
    $songs = Song::whereRaw('LOWER(title) LIKE ?', [$searchTerm])
        ->with(['album.group', 'album.idol']) // Nested eager loading
        ->limit(5)
        ->get()
        ->map(function ($song) {
            $artist = $song->artist ?: $song->album?->artist;
            return [
                'id' => $song->id,
                'type' => 'song',
                'title' => $song->title,
                'subtitle' => $artist ? ($artist->stage_name ?? $artist->name) : null,
                'image' => $song->album?->cover_image_url,
                'url' => route('songs.show', $song),
            ];
        });

    // Search Variety Shows
    $varietyShows = VarietyShow::whereRaw('LOWER(title) LIKE ?', [$searchTerm])
        ->limit(5)
        ->get()
        ->map(function ($show) {
            return [
                'id' => $show->id,
                'type' => 'variety_show',
                'title' => $show->title,
                'image' => $show->poster_url,
                'url' => route('variety-shows.show', $show),
                'description' => $show->description 
                    ? substr($show->description, 0, 100) . '...' 
                    : null,
            ];
        });

    // Search Users (only if authenticated)
    $users = collect();
    if (auth()->check()) {
        $users = User::where(function ($q) use ($searchTerm) {
                $q->whereRaw('LOWER(name) LIKE ?', [$searchTerm])
                  ->orWhereRaw('LOWER(username) LIKE ?', [$searchTerm]);
            })
            ->limit(5)
            ->get()
            ->map(function ($user) {
                return [
                    'id' => $user->id,
                    'type' => 'user',
                    'title' => $user->name,
                    'subtitle' => '@' . $user->username,
                    'image' => $user->profile_picture,
                    'url' => route('users.show', $user->username),
                ];
            });
    }

    // Combine all results
    return $groups
        ->concat($idols)
        ->concat($albums)
        ->concat($songs)
        ->concat($varietyShows)
        ->concat($users)
        ->take(25); // Limit total results
}

Advanced Techniques:

  • whereRaw with LOWER(): Case-insensitive search across databases
  • Eager loading: with('groups') prevents N+1 queries
  • Nested eager loading: with(['album.group', 'album.idol']) loads deep relationships
  • Collection methods: concat() combines multiple collections
  • Conditional search: Users only searchable when authenticated
  • Unified format: All results have same structure (type, title, image, url)

Custom Query Scopes for Reusability

Add a scope to the Album model for loading artists:

// app/Models/Album.php

/**
 * Scope to eager load the artist (group or idol).
 */
public function scopeWithArtist($query)
{
    return $query->with(['group', 'idol']);
}

/**
 * Get the artist (group or idol) for this album.
 */
public function getArtistAttribute()
{
    return $this->group ?: $this->idol;
}

Why scopes? Reusable query logic that keeps controllers clean. Album::withArtist() is more readable than repeating with(['group', 'idol']) everywhere.

Adding Filters and Sorting

Extend the search to support filtering by type:

public function search(Request $request)
{
    $query = $request->get('q', '');
    $type = $request->get('type'); // Optional filter: 'group', 'idol', etc.
    $sort = $request->get('sort', 'relevance'); // 'relevance', 'name', 'date'
    
    if (empty(trim($query))) {
        return response()->json([
            'results' => [],
            'total' => 0
        ]);
    }

    $searchTerm = '%' . strtolower($query) . '%';
    
    // Filter by type if specified
    if ($type) {
        $results = $this->searchSingleType($type, $searchTerm, $sort);
    } else {
        $results = $this->searchAllModels($searchTerm);
    }

    return response()->json([
        'results' => $results->values(),
        'total' => $results->count(),
        'query' => $query,
        'filters' => [
            'type' => $type,
            'sort' => $sort,
        ]
    ]);
}

/**
 * Search a single model type with pagination.
 */
protected function searchSingleType(string $type, string $searchTerm, string $sort)
{
    $query = match($type) {
        'group' => Group::whereRaw('LOWER(name) LIKE ?', [$searchTerm]),
        'idol' => Idol::where(function ($q) use ($searchTerm) {
            $q->whereRaw('LOWER(birth_name) LIKE ?', [$searchTerm])
              ->orWhereRaw('LOWER(stage_name) LIKE ?', [$searchTerm]);
        })->with('groups'),
        'album' => Album::whereRaw('LOWER(title) LIKE ?', [$searchTerm])->withArtist(),
        'song' => Song::whereRaw('LOWER(title) LIKE ?', [$searchTerm])
            ->with(['album.group', 'album.idol']),
        'variety_show' => VarietyShow::whereRaw('LOWER(title) LIKE ?', [$searchTerm]),
        'user' => User::where(function ($q) use ($searchTerm) {
            $q->whereRaw('LOWER(name) LIKE ?', [$searchTerm])
              ->orWhereRaw('LOWER(username) LIKE ?', [$searchTerm]);
        }),
        default => throw new \InvalidArgumentException("Invalid type: {$type}"),
    };

    // Apply sorting
    $query = match($sort) {
        'name' => $query->orderBy('name'),
        'date' => $query->latest(),
        default => $query, // Relevance (database default order)
    };

    // Paginate for single-type searches
    return $query->paginate(20);
}

New Features:

  • Type filtering: Search only groups, only idols, etc.
  • Sorting options: By name, date, or relevance
  • Pagination: When filtering by type, return paginated results
  • Match expression: Clean type-to-model mapping

Frontend Integration with Vue

Create a reactive search component:

<script setup lang="ts">
import { ref, watch } from 'vue'
import { router } from '@inertiajs/vue3'
import { useDebounceFn } from '@vueuse/core'

const searchQuery = ref('')
const results = ref([])
const isSearching = ref(false)
const selectedType = ref<string | null>(null)

// Debounce search to avoid excessive API calls
const performSearch = useDebounceFn(async () => {
  if (searchQuery.value.length < 2) {
    results.value = []
    return
  }

  isSearching.value = true

  try {
    const response = await fetch(
      `/search?q=${encodeURIComponent(searchQuery.value)}` +
      (selectedType.value ? `&type=${selectedType.value}` : '')
    )
    const data = await response.json()
    results.value = data.results
  } catch (error) {
    console.error('Search failed:', error)
  } finally {
    isSearching.value = false
  }
}, 300) // Wait 300ms after user stops typing

// Watch for query changes
watch(searchQuery, () => {
  performSearch()
})

// Group results by type
const groupedResults = computed(() => {
  const grouped = {}
  results.value.forEach(result => {
    if (!grouped[result.type]) {
      grouped[result.type] = []
    }
    grouped[result.type].push(result)
  })
  return grouped
})

const typeLabels = {
  group: 'Groups',
  idol: 'Idols',
  album: 'Albums',
  song: 'Songs',
  variety_show: 'Variety Shows',
  user: 'Users',
}
</script>

<template>
  <div class="search-container">
    <!-- Search Input -->
    <input
      v-model="searchQuery"
      type="search"
      placeholder="Search groups, idols, songs..."
      class="search-input"
    />

    <!-- Loading State -->
    <div v-if="isSearching" class="loading">
      Searching...
    </div>

    <!-- Results -->
    <div v-else-if="results.length > 0" class="results">
      <!-- Grouped by Type -->
      <div
        v-for="(items, type) in groupedResults"
        :key="type"
        class="result-group"
      >
        <h3>{{ typeLabels[type] }}</h3>
        
        <a
          v-for="result in items"
          :key="`${result.type}-${result.id}`"
          :href="result.url"
          class="result-item"
        >
          <img
            v-if="result.image"
            :src="result.image"
            :alt="result.title"
            class="result-image"
          />
          
          <div class="result-content">
            <div class="result-title">{{ result.title }}</div>
            <div v-if="result.subtitle" class="result-subtitle">
              {{ result.subtitle }}
            </div>
            <div v-if="result.description" class="result-description">
              {{ result.description }}
            </div>
          </div>
        </a>
      </div>
    </div>

    <!-- Empty State -->
    <div v-else-if="searchQuery.length >= 2" class="empty-state">
      No results found for "{{ searchQuery }}"
    </div>
  </div>
</template>

Frontend Patterns:

  • Debouncing: Wait 300ms after user stops typing before searching
  • Loading states: Show feedback while searching
  • Grouped display: Results organized by type
  • Empty state: Helpful message when no results found
  • Minimum query length: Only search when query is 2+ characters

Under the Hood

Without Index:

-- Full table scan: checks every row
SELECT * FROM songs WHERE LOWER(title) LIKE '%love%';
-- Execution time: 2.5 seconds (100,000 rows)

With Index:

-- Uses B-tree index: logarithmic lookup
CREATE INDEX idx_songs_title ON songs(title);
SELECT * FROM songs WHERE LOWER(title) LIKE '%love%';
-- Execution time: 0.05 seconds (same 100,000 rows)

Why it’s faster:

  • B-tree structure: Index organizes data in a tree, allowing binary search
  • Reduced I/O: Only reads relevant index pages, not entire table
  • Query planner: Database optimizer uses index automatically

Limitation: Indexes don’t help with leading wildcards (%term). For full-text search, use Laravel Scout with Meilisearch or Algolia.

Query Optimization: N+1 Prevention

The N+1 Problem:

// ❌ BAD: N+1 queries
$idols = Idol::whereRaw('LOWER(stage_name) LIKE ?', [$searchTerm])->get();

foreach ($idols as $idol) {
    echo $idol->groups->pluck('name')->join(', '); // Queries groups for EACH idol
}
// Total queries: 1 (idols) + N (groups) = 51 queries for 50 idols

The Solution: Eager Loading

// ✅ GOOD: 2 queries total
$idols = Idol::whereRaw('LOWER(stage_name) LIKE ?', [$searchTerm])
    ->with('groups') // Loads all groups in one query
    ->get();

foreach ($idols as $idol) {
    echo $idol->groups->pluck('name')->join(', '); // No additional queries
}
// Total queries: 1 (idols) + 1 (groups) = 2 queries for 50 idols

How with() works:

  1. Executes main query: SELECT * FROM idols WHERE ...
  2. Collects all idol IDs: [1, 2, 3, ..., 50]
  3. Executes relationship query: SELECT * FROM groups WHERE idol_id IN (1,2,3,...,50)
  4. Attaches groups to idols in memory

Memory Management: Pagination vs. Limiting

Limiting (for multi-model search):

$groups = Group::whereRaw('LOWER(name) LIKE ?', [$searchTerm])
    ->limit(5) // Only fetch 5 rows from database
    ->get();

Pagination (for single-model search):

$groups = Group::whereRaw('LOWER(name) LIKE ?', [$searchTerm])
    ->paginate(20); // Fetch 20 rows, track total count

Key Differences:

  • Limit: Faster, no total count, used for preview results
  • Paginate: Slower (counts total), provides page navigation, used for full results

Memory Impact:

  • get() loads all results into memory (dangerous for large datasets)
  • limit() caps memory usage
  • paginate() loads one page at a time

Case-Insensitive Search Across Databases

The Challenge: Different databases handle case sensitivity differently.

MySQL (case-insensitive by default):

SELECT * FROM groups WHERE name LIKE '%bts%'; -- Matches "BTS", "Bts", "bts"

PostgreSQL (case-sensitive by default):

SELECT * FROM groups WHERE name LIKE '%bts%'; -- Only matches "bts"
SELECT * FROM groups WHERE LOWER(name) LIKE LOWER('%bts%'); -- Matches all

Laravel Solution (database-agnostic):

// Works on MySQL, PostgreSQL, SQLite
Group::whereRaw('LOWER(name) LIKE ?', [strtolower($searchTerm)])

Performance Note: LOWER() prevents index usage. For production, consider:

  1. Generated columns: Create a lowercase column with an index
  2. Full-text search: Use Laravel Scout with Meilisearch
  3. Elasticsearch: For complex search requirements

Edge Cases & Pitfalls

SQL Injection with Raw Queries

Problem: Concatenating user input into SQL.

// ❌ DANGEROUS: SQL injection vulnerability
$query = $request->get('q');
Group::whereRaw("LOWER(name) LIKE '%{$query}%'")->get();

// Attacker input: "'; DROP TABLE groups; --"
// Resulting SQL: LOWER(name) LIKE '%'; DROP TABLE groups; --%'

Solution: Always use parameter binding.

// ✅ SAFE: Parameter binding prevents injection
$searchTerm = '%' . strtolower($query) . '%';
Group::whereRaw('LOWER(name) LIKE ?', [$searchTerm])->get();

// Laravel escapes the parameter, preventing injection

Searching Without Minimum Length

Problem: Searching for single characters returns too many results.

// ❌ BAD: Searching for "a" returns thousands of results
if ($query) {
    $results = $this->searchAllModels($query);
}

Solution: Enforce minimum query length.

// ✅ GOOD: Require at least 2 characters
if (strlen(trim($query)) < 2) {
    return response()->json([
        'results' => [],
        'message' => 'Please enter at least 2 characters',
    ]);
}

Not Limiting Results

Problem: Returning unlimited results crashes the browser.

// ❌ BAD: Could return 10,000 songs
$songs = Song::whereRaw('LOWER(title) LIKE ?', [$searchTerm])->get();

Solution: Always limit or paginate.

// ✅ GOOD: Limit to 5 per category for overview
$songs = Song::whereRaw('LOWER(title) LIKE ?', [$searchTerm])
    ->limit(5)
    ->get();

// ✅ GOOD: Paginate for full results
$songs = Song::whereRaw('LOWER(title) LIKE ?', [$searchTerm])
    ->paginate(20);

Handle special characters that have meaning in SQL LIKE:

/**
 * Escape special LIKE characters.
 */
protected function escapeLikeValue(string $value): string
{
    // Escape %, _, and \ characters
    $value = str_replace(['\\', '%', '_'], ['\\\\', '\\%', '\\_'], $value);
    return '%' . strtolower($value) . '%';
}

// Usage
$searchTerm = $this->escapeLikeValue($request->get('q'));
Group::whereRaw('LOWER(name) LIKE ? ESCAPE ?', [$searchTerm, '\\'])->get();

Empty Results for Each Category

When searching all models, some categories might have no results:

// Handle empty collections gracefully
$groups = Group::whereRaw('LOWER(name) LIKE ?', [$searchTerm])
    ->limit(5)
    ->get();

// $groups is an empty collection, not null
if ($groups->isEmpty()) {
    // Still safe to concat
}

$results = $groups
    ->concat($idols)
    ->concat($albums); // Works even if some are empty

Debouncing Search Requests

Prevent excessive API calls from rapid typing:

// Frontend: Debounce with VueUse
import { useDebounceFn } from '@vueuse/core'

const performSearch = useDebounceFn(async () => {
  // Search logic
}, 300) // Wait 300ms after last keystroke

Why 300ms? Research shows this is the sweet spot:

  • Fast enough to feel instant
  • Slow enough to avoid excessive requests
  • Typical typing speed: 200-300ms between keystrokes

Conclusion

What You’ve Learned

You’ve built a production-grade search system with:

  1. Multi-Model Search: Search across 6 different models simultaneously
  2. Query Optimization: Eager loading, indexes, and efficient queries
  3. Flexible Filtering: Filter by type, sort by relevance/name/date
  4. Pagination Strategies: Limiting for previews, pagination for full results
  5. Frontend Integration: Debounced search with reactive Vue components
  6. Security: SQL injection prevention with parameter binding

The Production Pattern

Search System Architecture
├── Controller
│   ├── Validate query (min length, sanitize)
│   ├── Normalize search term (lowercase, wildcards)
│   ├── Search each model (parallel queries)
│   ├── Limit results per category (5 each)
│   └── Transform to unified format
├── Database
│   ├── Indexes on searchable columns
│   ├── Case-insensitive queries (LOWER)
│   └── Eager loading for relationships
└── Frontend
    ├── Debounced input (300ms)
    ├── Loading states
    ├── Grouped display by type
    └── Empty state handling

Real-World Impact

In MyKpopLists, this search system:

  • Handles 100,000+ records: Searches across 6 models in under 100ms
  • Prevents N+1 queries: Eager loading reduces queries by 95%
  • Scales gracefully: Limiting results keeps memory usage constant
  • Great UX: Debouncing and loading states provide smooth experience

Next Steps

  • Tutorial 9: Implement soft deletes with cascade logic and content moderation
  • Advanced: Integrate Laravel Scout with Meilisearch for full-text search
  • Performance: Add Redis caching for popular search queries
  • Analytics: Track search queries to improve content discovery

Remember: Search is often the most-used feature in content-heavy applications. Optimize early, limit results, and always use indexes.

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