sphinx | 易学教程

Laravel: order by where in

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问题 I am using SphinxSearch to query some contents and have the ids of my objects that I want to query with MySQL. The array of my ids are sorted depending on their rank Sphinx gives. Thus, I would like to make a MySQL like so: SELECT * FROM table WHERE id IN (1,17,2) ORDER BY FIELD(id,1,17,2) I know I can do: Table::whereIn('id', $ids)->get(); But I can't get the order I had. How can I do that in a proper way with Laravel ? 回答1: Using the solution found on http://laravelsnippets.com/snippets/get

php mysql fulltext search: lucene, sphinx, or?

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问题 This is admittedly similar to (but not a duplicate of) Comparison of full text search engine - Lucene, Sphinx, Postgresql, MySQL?, however what I am looking for are specific, supported, recommendations from the benefit of experience with more than one of the available systems (there seems to be a lot of: "I've used lucene, but not sphinx", and vice a versa). The setup: Standard LAMP (Mysql 5.0, PHP 5). MySQL: tables are using the InnoDB engine for foreign key constraints We are looking at

linux安装php sphinx出错

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安装sphinx的php客户端 # wget -c http://pecl.php.net/get/sphinx-1.3.0.tgz # tar zxvf sphinx-1.3.0.tgz # cd sphinx-1.3.0 # phpize # ./configure --with-php-config=/usr/local/php5410/bin/php-config # make && make install ./configure的时候出错，提示checking for libsphinxclient headers in default path... not found configure: error: Cannot find libsphinxclient headers 。找了下libsphinxclient，在/www/soft/csft-3.2.13/api/libsphinxclient，之前安装的是coreseek3.2.13版。进入该目录，重新编译 cd libsphinxclient/ ./configure make && make install 然后再次编译sphinx的php客户端就可以了来源： http://www.cnblogs.com/zl0372/p/sphinx_php.html

ElasticSearch, Sphinx, Lucene, Solr, Xapian. Which fits for which usage? [closed]

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I'm currently looking at other search methods rather than having a huge SQL query. I saw elasticsearch recently and played with whoosh (a Python implementation of a search engine). Can you give reasons for your choice(s)? kimchy As the creator of ElasticSearch, maybe I can give you some reasoning on why I went ahead and created it in the first place :). Using pure Lucene is challenging. There are many things that you need to take care for if you want it to really perform well, and also, its a library, so no distributed support, it's just an embedded Java library that you need to maintain. In

How to evaluate hosted full text search solutions?

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问题 What are the options when it comes to SaaS/hosted full text search? How should I evaluate the different options available? I\'m looking for something that uses Lucene, solr, or sphinx on the backend, and provides a REST API for submitting documents to index, and running searches. I could build my own EC2 AMI, but I\'d have to configure EBS and other stuff, monitor it, etc. 回答1: Websolr provides a cloud-based Solr with a control panel. It's in private beta as of this writing, but you can get

Choosing a stand-alone full-text search server: Sphinx or SOLR? [closed]

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I'm looking for a stand-alone full-text search server with the following properties: Must operate as a stand-alone server that can serve search requests from multiple clients Must be able to do "bulk indexing" by indexing the result of an SQL query: say "SELECT id, text_to_index FROM documents;" Must be free software and must run on Linux with MySQL as the database Must be fast (rules out MySQL's internal full-text search) The alternatives I've found that have these properties are: Solr (based on Lucene) ElasticSearch (also based on Lucene) Sphinx My questions: How do they compare? Have I

Comparison of full text search engine - Lucene, Sphinx, Postgresql, MySQL?

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问题 I\'m building a Django site and I am looking for a search engine. A few candidates: Lucene/Lucene with Compass/Solr Sphinx Postgresql built-in full text search MySQl built-in full text search Selection criteria: result relevance and ranking searching and indexing speed ease of use and ease of integration with Django resource requirements - site will be hosted on a VPS, so ideally the search engine wouldn\'t require a lot of RAM and CPU scalability extra features such as \"did you mean?\",