I have performance issues on a query in a big table (12 million records) based on Geonames, that's a read-only database so NO DELETE, UPDATE or INSERT only SELECT.

There are queries I make every now and then filtering by different columns that are not keys (latitude and longitude, fcode and country, only name, etc..), the thing is that with my server resources it takes more than 30 seconds to complete them.

I have made views and small tables (clone of the big table but with only data from one country) to check how to improve it.

With the views, I get similar results than in the big table and using explain I have seen that views check the same amount of rows as the big table (12million rows)

In one of the small tables I get less than 200 milliseconds, more or less depending on the table size.

I'm not a database expert but duplicating data in small tables feels awkward. I'm not sure if that's the best approach that can be done there.

All queries are being sent from my backend, so no stored procedures.

The queries done filtering by primary keys works blazing fast though!.

Thanks in advance for any advice!





  • Table definition
CREATE TABLE `geoname` (
  `geonameid` INT,
  `name` VARCHAR(200),
  `asciiname` VARCHAR(200),
  `alternatenames` VARCHAR(4000),
  `latitude` DECIMAL(10,7),
  `longitude` DECIMAL(10,7),
  `fclass` VARCHAR(1),
  `fcode` VARCHAR(10),
  `country` VARCHAR(2),
  `cc2` VARCHAR(60),
  `admin1` VARCHAR(20),
  `admin2` VARCHAR(80),
  `admin3` VARCHAR(20),
  `admin4` VARCHAR(20),
  `population` INT,
  `elevation` INT,
  `gtopo30` INT,
  `timezone` VARCHAR(40),
  `moddate` DATE,
  PRIMARY KEY (geonameid)
  • What kind of indexes could I add there?
  • 1
    Have you considered creating indexes to support your queries?
    – mustaccio
    Commented May 24, 2021 at 19:13
  • What indexes do you have on the "big table"? (Add their definitions to the post please.)
    – J.D.
    Commented May 24, 2021 at 19:13
  • thos o9sn't awkward at all, , the basic problem ist youhave to union them back toghter and in a from clause all tables have to exist,if that is an issue for youyou have to test them prior to the query, whicjh means more tome to spent.
    – nbk
    Commented May 24, 2021 at 21:36
  • @mustaccio yep i already did it, with new indexes qeries using those fields as filtering values improved a lot, stiil looking for better performance in latitude longitude searches
    – xiscodev
    Commented May 25, 2021 at 23:00
  • @J.D. I update my original post with create query with table structure
    – xiscodev
    Commented May 25, 2021 at 23:03

2 Answers 2


I think I have been using that table. It is clunky when you want to see states/provinces and other things like that.

Sure break out a country if that is all you need. But don't plan on breaking out all ~250 countries into separate tables (plus continents, etc).

VIEWs are not performance enhancers. They can hide the clumsy nature a table like that one. (Especially due to the fcode checks.)

This may help:

INDEX(fcode, country_code)

WHERE feature_code LIKE 'PCL%' AND ...
WHERE feature_code = 'ADM1' AND country_code = 'ES'

If you would care to provide the desired queries (not the views) and the desired table(s), I may be able to provide more suggestions.

Lat/lng searches

Lat/lng needs more work than simply a composite index. Suggest you start with a "bounding box" and these two composite indexes:

INDEX(lat, lng),
INDEX(lng, lat)

If such searches are not fast enough, then look at more complex methods in http://mysql.rjweb.org/doc.php/find_nearest_in_mysql

  • Hey you are saying about using a multi-column index? Im not doing joins yet, but maybe they improve performance for latitude longitude searches! I'll give it a try!
    – xiscodev
    Commented May 25, 2021 at 22:58
  • Why you worry about breaking all big table to smaller only a country tables? I still keep the big table for queries i need to look over it
    – xiscodev
    Commented May 25, 2021 at 23:06
  • @xiscode - I added lat/lng paragraph.
    – Rick James
    Commented May 25, 2021 at 23:06
  • For a variety of tests of MySQL, is use the Canadian subset -- about 4K rows and 13 provinces --> ability to formulate a wide variety of queries and be able to eyeball the results for 'correctness'. I do not have a table for each country.
    – Rick James
    Commented May 25, 2021 at 23:10
  • Well seems fair to have only the data you will use stored there, but for coordinates its quite unknown territory for my what will user look for. Oh I see, proximity searches then? I'm using haversine formula for the lat/lang calculations en.m.wikipedia.org/wiki/Haversine_formula
    – xiscodev
    Commented May 25, 2021 at 23:14

Hey I made a couple of changes that have improved my overall select queries performance in big table.

As I said before I'm only doing readings so i found a couple of tips here

I applied some of them and worked!

  • Changed my defaults table engine to MyISAM, it was been set to InnoDB by default

  • Added fields I use as filtering value as KEYs to the table, for example, asciiname, latitude and longitude are my new keys in geoname table

  • Limited size of result set with LIMIT, for example if I know I'm looking for only one result I don't need the database pointer to move over all 12 million registers, just stop when found the limit number setted

  • I kept with partitioning the big table into smaller tables for focused country queries.

Though the performance over queries using latitude and longitude improved i think its not enough yet

Some said that maybe for coordinates I should use OpenGIS geometry model and Spatial data types which represent some kind of polygons made by latitude and longitude points

Generate a table with that index only and geonameid, then simply look coordinates in that table calculating the polygon to match, and return its geonameid to match on the big table.

What do you think that approach?

Im providing users the list of countries so the country ISO is a data known, i use it to point to the suitable country table desired.

I decided to partition it as im not worried about data growth, and actually its not a CRUD database

Some of my queries now look like this and are blazing fast (couple of hundred millis compared to almost almost 20 seconds)

SELECT * FROM geonames.country_".strtoupper($country_iso)."
WHERE asciiname = ? AND alternatenames <>'' AND fclass = 'P'
GROUP BY country;
  • The GROUP BY country does nothing since you are [it seems] looking at only one country. This (in either order) will help: INDEX(asciiname, class).
    – Rick James
    Commented May 25, 2021 at 23:26
  • The dataset does not have the polygons representing the countries. What might you use a SPATIAL index for?
    – Rick James
    Commented May 25, 2021 at 23:27
  • Yes @RickJames about the GROUP BY country operator is a remnant before the table partitioning
    – xiscodev
    Commented May 26, 2021 at 21:42
  • Generally, avoid strtoupper by using a "case folding" collation on the column.
    – Rick James
    Commented May 27, 2021 at 0:46

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