Profiling queries

In this article we discuss the tools available for profiling queries in Manticore Search.


By default the SHOW META command provides statistics about the keywords used in the match.  For each keyword we get the number of documents in which the keywords was found and total number of hits. High values - for example docs are almost as high as the total documents in the index -  can indicate the keyword is a candidate for being a stopword.

SHOW META output can […]

Suggestions on phrases using a single SUGGEST call

In this article we discuss how a single CALL QSUGGEST can be used to correct phrases in particular cases.

CALL QSUGGEST was introduced in the last version of Sphinx 2.x. The statement allows finding close matches of an input word from the dictionary of an index with infixing enabled. The most common use case for this feature is implementing a "Did you mean ...?" functionality.

Before the introduction of QSUGGEST […]

Percolate queries: Manticore Search vs Luwak

In this article we test how percolate queries perform in Manticore Search and Luwak.


Recently we tested the performance of Percolate Queries in Manticore Search and Elasticsearch. Today we are looking at Luwak, a stored query engine based on Lucene search library.

When we developed Percolate Queries […]

Building 1M docs index having no one real doc


Just want to share an interesting trick on how to easily index something with Sphinx / Manticore Search for test purposes without need of populating database with a lot of data or doing smth like that. The below is a full Sphinx / Mantocore Search config which lets you build a 1M docs index consisting of random 3-char words and geo coordinates, an example of command to build the index and an exampe of a sphinxql query which does search in the index. All you need is just any connection to any db (in this case ‘mysql -u root’ works).


Basics of Manticore Indexes

In this article, we discuss an introduction to Manticore indexes.

Manticore Search supports two storage index types:

  • plain (also called offline or disk) index. Data is indexed once at creation, it supports online rebuilding and online updates for non-text attributes
  • RealTime index. Similar to a database table, online updates are possible at any given time

In addition […]