Пример реализации. Живой поиск на Битрикс. Пример реализации Как называется мужчина search item php i

Основные задачи:

• реализовать поиск таким образом, чтобы после ввода поискового запроса в строку, ниже этой строки появились результаты поиска
• запрос на получение результата должен происходить только после окончания ввода поискового запроса

Окей, поехали!

Примерная вёрстка самого блока с поисковой строкой и div-ником, куда будем добавлять результаты поиска:

Т.к. поиск доступен в шапке сайта, добавим соответствующие скрипты поиска и стилизации результатов:

//подрубаем поиск: $APPLICATION->AddHeadScript("/search/ajax_search.js"); $APPLICATION->AddHeadScript("/search/jquery.mCustomScrollbar.js"); $APPLICATION->SetAdditionalCSS(SITE_TEMPLATE_PATH . "/css/ajax_search.css"); $APPLICATION->SetAdditionalCSS(SITE_TEMPLATE_PATH . "/css/jquery.mCustomScrollbar.min.css");

Теперь посмотрим, что лежит в нашем ajax_search.js:

Function get_result (){ //очищаем результаты поиска $("#search_result").html(""); //пока не получили результаты поиска - отобразим прелоадер $("#search_result").append(""); $.ajax({ type: "POST", url: "/search/ajax_search.php", data: "q="+q, dataType: "json", success: function(json){ //очистим прелоадер $("#search_result").html(""); $("#search_result").append(""); //добавляем каждый элемент массива json внутрь div-ника с class="live-search" (вёрстку можете использовать свою) $.each(json, function(index, element) { $("#search_result").find(".live-search").append(""+element.TITLE+""+element.BODY_FORMATED+""); //console.log (element.BODY_FORMATED); }); //стилизуем скроллинг $(".live-search").mCustomScrollbar({ scrollInertia: 500 }); } }); } var timer = 0; var q = ""; $(document).ready(function() { $("#q").keyup(function() { q = this.value; clearTimeout(timer); timer = setTimeout(get_result, 1000); }); $("#reset_live_search").click(function() { $("#search_result").html(""); }); });

keyup функция осуществляем вызов функции get_result(), которая собственно и заполняет div-ник с id=»search_result» по аяксу.

mCustomScrollbar — это просто вызов стилизации (можете отключить).

Данные от /search/ajax_search.php мы получаем в формате JSON.

С JS составляющей всё понятно, теперь посмотрим, что происходит в ajax_search.php:

В данном случае поиск осуществляется методом Search Битриксового класса CSearch. В PARAM2 пишем в каком инфоблоке ищем. Результаты поиска запихиваем в массив $result. Обратите внимание, что в $res[‘ITEM_ID’] может быть как элемент, так и раздел. В зависимости от того, что нашли, в $result_item[‘BODY_FORMATED’] пихаем либо название раздела, либо кусок текста из найдённого элемента инфоблока.

By Ibrahim Diallo

Search is an important feature on a website. When my few readers want to look for a particular passage on my blog, they use the search box. It used to be powered by Google Search, but I have since then changed it to my own home-brewed version not because I can do better but because it was an interesting challenge.

If you are in a hurry and just want your site to be searchable, well do what I did before, use Google.

// In search.php file $term = isset($_GET["query"])?$_GET["query"]: ""; $term = urlencode($term); $website = urlencode("www.yourwebsite.com"); $redirect = "https://www.google.com/search?q=site%3A{$website}+{$term}"; header("Location: $redirect"); exit;

What it does is pretty simple. Get the term passed by the user, and forward it to Google search page. Limit the search result to our current domain using the site: keyword in the search query. All your pages that are indexed by Google will be available through search now. If you do want to handle your search in house however, then keep reading.

Before we go any further, try using the search box on this blog. It uses the same process that I will describe below. If you feel that this is what you want then please continue reading.

This solution is catered to small websites. I make use of LIKE with wild cards on both ends, meaning your search cannot be indexed. This means the solution will work fine for your blog or personal website that doesn"t contain tons of data. Port it to a bigger website and it might become very slow. MySQL offers Full Text Search which is not what we are doing here.

Note: If you have 5000 blog posts you are still fine. .

We will take the structure of this blog as a reference. Each blog post has:

• A title p_title
• A url p_url
• A summary p_summary
• A post content p_content
• And catergories category.tagname

For every field that matches with our search term, we will give it a score. The score will be based on the importance of the match:

// the exact term matches is found in the title $scoreFullTitle = 6; // match the title in part $scoreTitleKeyword = 5; // the exact term matches is found in the summary $scoreFullSummary = 5; // match the summary in part $scoreSummaryKeyword = 4; // the exact term matches is found in the content $scoreFullDocument = 4; // match the document in part $scoreDocumentKeyword = 3; // matches a category $scoreCategoryKeyword = 2; // matches the url $scoreUrlKeyword = 1;

Before we get started, there are a few words that do not contribute much to a search that should be removed. Example "in","it","a","the","of" ... . We will filter those out and feel free to add any word you think is irrelevant. Another thing is, we want to limit the length of our query. We don"t want a user to write a novel in the search field and crash our MySQL server.

// Remove unnecessary words from the search term and return them as an array function filterSearchKeys($query){ $query = trim(preg_replace("/(\s+)+/", " ", $query)); $words = array(); // expand this list with your words. $list = array("in","it","a","the","of","or","I","you","he","me","us","they","she","to","but","that","this","those","then"); $c = 0; foreach(explode(" ", $query) as $key){ if (in_array($key, $list)){ continue; } $words = $key; if ($c >= 15){ break; } $c++; } return $words; } // limit words number of characters function limitChars($query, $limit = 200){ return substr($query, 0,$limit); }

Our helper functions can now limit character count and filter useless words. The way we will implement our algorithm is by giving a score every time we find a match. We will match words using the if statement and accumulate points as we match more words. At the end we can use that score to sort our results

Note: I will not be showing how to connect to MySQL database. If you are having problems to efficiently connect to the database I recommend reading this .

Let"s give our function a structure first. Note I left placeholders so we can implement sections separately.

Function search($query){ $query = trim($query); if (mb_strlen($query)===0){ // no need for empty search right? return false; } $query = limitChars($query); // Weighing scores $scoreFullTitle = 6; $scoreTitleKeyword = 5; $scoreFullSummary = 5; $scoreSummaryKeyword = 4; $scoreFullDocument = 4; $scoreDocumentKeyword = 3; $scoreCategoryKeyword = 2; $scoreUrlKeyword = 1; $keywords = filterSearchKeys($query); $escQuery = DB::escape($query); // see note above to get db object $titleSQL = array(); $sumSQL = array(); $docSQL = array(); $categorySQL = array(); $urlSQL = array(); /** Matching full occurrences PLACE HOLDER **/ /** Matching Keywords PLACE HOLDER **/ $sql = "SELECT p.p_id,p.p_title,p.p_date_published,p.p_url, p.p_summary,p.p_content,p.thumbnail, ((-- Title score ".implode(" + ", $titleSQL).")+ (-- Summary ".implode(" + ", $sumSQL).")+ (-- document ".implode(" + ", $docSQL).")+ (-- tag/category ".implode(" + ", $categorySQL).")+ (-- url ".implode(" + ", $urlSQL).")) as relevance FROM post p WHERE p.status = "published" HAVING relevance >

In the query, all scores will be summed up as the relevance variable and we can use it to sort the results.

We make sure we have some keywords first then add our query.

If (count($keywords) > 1){ $titleSQL = "if (p_title LIKE "%".$escQuery."%",{$scoreFullTitle},0)"; $sumSQL = "if (p_summary LIKE "%".$escQuery."%",{$scoreFullSummary},0)"; $docSQL = "if (p_content LIKE "%".$escQuery."%",{$scoreFullDocument},0)"; }

Those are the matches with higher score. If the search term matches an article that contains these, they will have higher chances of appearing on top.

We loop through all keywords and check if they match any of the fields. For the category match, I used a sub-query since a post can have multiple categories.

Foreach($keywords as $key){ $titleSQL = "if (p_title LIKE "%".DB::escape($key)."%",{$scoreTitleKeyword},0)"; $sumSQL = "if (p_summary LIKE "%".DB::escape($key)."%",{$scoreSummaryKeyword},0)"; $docSQL = "if (p_content LIKE "%".DB::escape($key)."%",{$scoreDocumentKeyword},0)"; $urlSQL = "if (p_url LIKE "%".DB::escape($key)."%",{$scoreUrlKeyword},0)"; $categorySQL = "if ((SELECT count(category.tag_id) FROM category JOIN post_category ON post_category.tag_id = category.tag_id WHERE post_category.post_id = p.post_id AND category.name = "".DB::escape($key)."") > 0,{$scoreCategoryKeyword},0)"; }

Also as pointed by a commenter below, we have to make sure that the these variables are not empty arrays or the query will fail.

// Just incase it"s empty, add 0 if (empty($titleSQL)){ $titleSQL = 0; } if (empty($sumSQL)){ $sumSQL = 0; } if (empty($docSQL)){ $docSQL = 0; } if (empty($urlSQL)){ $urlSQL = 0; } if (empty($tagSQL)){ $tagSQL = 0; }

At the end the queries are all concatenated and added together to determine the relevance of the post to the search term.

// Remove unnecessary words from the search term and return them as an array function filterSearchKeys($query){ $query = trim(preg_replace("/(\s+)+/", " ", $query)); $words = array(); // expand this list with your words. $list = array("in","it","a","the","of","or","I","you","he","me","us","they","she","to","but","that","this","those","then"); $c = 0; foreach(explode(" ", $query) as $key){ if (in_array($key, $list)){ continue; } $words = $key; if ($c >= 15){ break; } $c++; } return $words; } // limit words number of characters function limitChars($query, $limit = 200){ return substr($query, 0,$limit); } function search($query){ $query = trim($query); if (mb_strlen($query)===0){ // no need for empty search right? return false; } $query = limitChars($query); // Weighing scores $scoreFullTitle = 6; $scoreTitleKeyword = 5; $scoreFullSummary = 5; $scoreSummaryKeyword = 4; $scoreFullDocument = 4; $scoreDocumentKeyword = 3; $scoreCategoryKeyword = 2; $scoreUrlKeyword = 1; $keywords = filterSearchKeys($query); $escQuery = DB::escape($query); // see note above to get db object $titleSQL = array(); $sumSQL = array(); $docSQL = array(); $categorySQL = array(); $urlSQL = array(); /** Matching full occurences **/ if (count($keywords) > 1){ $titleSQL = "if (p_title LIKE "%".$escQuery."%",{$scoreFullTitle},0)"; $sumSQL = "if (p_summary LIKE "%".$escQuery."%",{$scoreFullSummary},0)"; $docSQL = "if (p_content LIKE "%".$escQuery."%",{$scoreFullDocument},0)"; } /** Matching Keywords **/ foreach($keywords as $key){ $titleSQL = "if (p_title LIKE "%".DB::escape($key)."%",{$scoreTitleKeyword},0)"; $sumSQL = "if (p_summary LIKE "%".DB::escape($key)."%",{$scoreSummaryKeyword},0)"; $docSQL = "if (p_content LIKE "%".DB::escape($key)."%",{$scoreDocumentKeyword},0)"; $urlSQL = "if (p_url LIKE "%".DB::escape($key)."%",{$scoreUrlKeyword},0)"; $categorySQL = "if ((SELECT count(category.tag_id) FROM category JOIN post_category ON post_category.tag_id = category.tag_id WHERE post_category.post_id = p.post_id AND category.name = "".DB::escape($key)."") > 0,{$scoreCategoryKeyword},0)"; } // Just incase it"s empty, add 0 if (empty($titleSQL)){ $titleSQL = 0; } if (empty($sumSQL)){ $sumSQL = 0; } if (empty($docSQL)){ $docSQL = 0; } if (empty($urlSQL)){ $urlSQL = 0; } if (empty($tagSQL)){ $tagSQL = 0; } $sql = "SELECT p.p_id,p.p_title,p.p_date_published,p.p_url, p.p_summary,p.p_content,p.thumbnail, ((-- Title score ".implode(" + ", $titleSQL).")+ (-- Summary ".implode(" + ", $sumSQL).")+ (-- document ".implode(" + ", $docSQL).")+ (-- tag/category ".implode(" + ", $categorySQL).")+ (-- url ".implode(" + ", $urlSQL).")) as relevance FROM post p WHERE p.status = "published" HAVING relevance > 0 ORDER BY relevance DESC,p.page_views DESC LIMIT 25"; $results = DB::query($sql); if (!$results){ return false; } return $results; }

Now your search.php file can look like this:

$term = isset($_GET["query"])?$_GET["query"]: ""; $search_results = search($term); if (!$search_results) { echo "No results"; exit; } // Print page with results here.

We created a simple search algorithm that can handle a fair amount of content. I arbitrarily chose the score for each match, feel free to tweak it to something that works best for you. And there is always room for improvement.

It is a good idea to track the search term coming from your users, this way you can see if most users search for the same thing. If there is a pattern, then you can save them a trip and just cache the results using Memcached .

If you want to see this search algorithm in action, go ahead and try looking for an article on the search box on top of the page. I have added extra features like returning the part where the match was found in the text. Feel free to add features to yours.

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It is time to deal with mysql_* functions once and for all. These methods are deprecated and slow. The time to upgrade has long passed yet we still see it everywhere. Since I cannot force every author to update their tutorial and blogs, I decided to write a post to hopefully rank better and provide the essential information to help new comers.

Making your own website shouldn"t be too difficult. Hosting companies like Godaddy or Hostgator make it super easy for anyone to get started; they allow you to create a whole website without ever writing code. For most people, it is plenty to run a WordPress blog. If this is what you are looking for you should head to Godaddy.com right now. We are done here. But on the other hand, if you want to have control and not be limited by the short comings of a shared hosting without busting your wallet, you have come to the right place.

Vim is my favorite text editor on the terminal. After playing for a little while with nano and emacs , I finally settled with vim for its simplicity (bare with me please). Although it can be customized and used like an entire IDE, I use it mostly for editing files on my servers and making small but crucial changes. Let"s not get into Editor war and get started.

Zaryel Aug 12 2015:

Ian Mustafa Sep 26 2015:

Rob Sep 29 2015:

adeem Feb 11 2016:

Ivan Venediktov Apr 9 2016.

В сегодняшнем уроке мы рассмотрим поиск php mysql​ . Скриптов поиска огромное множество, некоторые используют базу данных, другие обходятся без нее, есть расширенные поиски с точной сортировкой. Мы же остановимся на обычном простом поиске, который ищет информацию по двум таблицам из базы данных MySQL .

Первый шаг. База данных MySQL.

Создаем базу данных search_lite , в ней две таблицы news - новости и vac - вакансии.

Задаем привилегии:

Логин - "root ",

Пароль - "",

Хост - "localhost ".

Дамп таблицы news - новостей.

Table structure for table `news` -- CREATE TABLE IF NOT EXISTS `news` (`id` int(2) NOT NULL, `title` varchar(255) NOT NULL, `text` text NOT NULL, PRIMARY KEY (`id`)) ENGINE=MyISAM DEFAULT CHARSET=cp1251;

Дамп таблицы vac - вакансий.

Table structure for table `vac` -- CREATE TABLE IF NOT EXISTS `vac` (`id` int(2) NOT NULL AUTO_INCREMENT, `title` varchar(255) NOT NULL, `text` text NOT NULL, PRIMARY KEY (`id`)) ENGINE=MyISAM DEFAULT CHARSET=cp1251 AUTO_INCREMENT=3 ;

Второй шаг. HTML и PHP.

Подключаемся к базе данных. Задаем условие по переменной $search , в которой поисковый запрос не введен, либо он меньше 4-х символов, а также проверяем на слеши и обрезаем переменную. Создаем два запроса, которые ищут в базе данных две таблицы news и vac по условию поиска по полю text . (Вы можете сами уже выбирать, сколько таблиц нужно будет для поиска. К примеру, у Вас будут таблицы lessons , materials , articles и т.п.. Также можете менять условия поиска, вместо поля text , можно выбрать поле title или другое поле.) Затем указываем сколько символов в тексте при выводе поиска в переменной $symbolls. Если же в таблицах news и vac по поиску ничего не найдено, выводим сообщение. Если же найдено, выводим данные из двух таблиц news и vac по заданному запросу поиска.