query-optimization

I am re-iterating the question asked by Mongus Pong Why would using a temp table be faster than a nested query? which doesn't have an answer that works for me. Most of us at some point find that when a nested query reaches a certain complexity it needs to broken into temp tables to keep it performative. It is absurd that this could ever be the most practical way forward and means these processes can no longer be made into a view. And often 3rd party BI apps will only play nicely with views so this is crucial. I am convinced there must be a simple queryplan setting to make the engine just spool

I'm having some problems trying to perform a query. I have two tables, one with elements information, and another one with records related with the elements of the first table. The idea is to get in the same row the element information plus several records information. Structure could be explain like this: table [ id, name ] [1, '1'], [2, '2'] table2 [ id, type, value ] [1, 1, '2009-12-02'] [1, 2, '2010-01-03'] [1, 4, '2010-01-03'] [2, 1, '2010-01-02'] [2, 2, '2010-01-02'] [2, 2, '2010-01-03'] [2, 3, '2010-01-07'] [2, 4, '2010-01-07'] And this is want I would like to achieve: result [id, name,

What's the difference in a clause done the two following ways? SELECT * FROM table1 INNER JOIN table2 ON ( table2.col1 = table1.col2 AND table2.member_id = 4 ) I've compared them both with basic queries and EXPLAIN EXTENDED and don't see a difference. I'm wondering if someone here has discovered a difference in a more complex/processing intensive envornment. SELECT * FROM table1 INNER JOIN table2 ON ( table2.col1 = table1.col2 ) WHERE table2.member_id = 4 With an INNER join the two approaches give identical results and should produce the same query plan. However there is a semantic difference

I have huge table with 2 columns: Id and Title. Id is bigint and I'm free to choose type of Title column: varchar, char, text, whatever. Column Title contains random text strings like "abcdefg", "q", "allyourbasebelongtous" with maximum of 255 chars. My task is to get strings by given substring. Substrings also have random length and can be start, middle or end of strings. The most obvious way to perform it: SELECT * FROM t LIKE '%abc%' I don't care about INSERT, I need only to do fast selects. What can I do to perform search as fast as possible? I use MS SQL Server 2008 R2, full text search

My situation: the query searches around 90,000 vehicles the query takes long each time I already have indexes on all the fields being JOINed. How can I optimise it? Here is the query: SELECT vehicles.make_id, vehicles.fuel_id, vehicles.body_id, vehicles.transmission_id, vehicles.colour_id, vehicles.mileage, vehicles.vehicle_year, vehicles.engine_size, vehicles.trade_or_private, vehicles.doors, vehicles.model_id, Round(3959 * Acos(Cos(Radians(51.465436)) * Cos(Radians(vehicles.gps_lat)) * Cos( Radians(vehicles.gps_lon) - Radians( -0.296482)) + Sin( Radians(51.465436)) * Sin( Radians(vehicles

I have a Sqlite database which I want to check the indexes are correct. MS SQL Analyser is great at breaking down the query execution and utilised indexes. Is there a similar tool for Sqlite? I know of no pretty graphical tools, but all of the information you seek is available from the EXPLAIN keyword. Consider this database: sqlite> create table users (name, email); sqlite> create index user_names on users (name); A query predicated on email will not use an index: sqlite> explain select * from users where email='foo'; 0|Trace|0|0|0||00| 1|String8|0|1|0|foo|00| 2|Goto|0|13|0||00| 3|OpenRead|0

I want to get a subtree from a table by tree path. the path column stores strings like: foo/ foo/bar/ foo/bar/baz/ If I try to select all records that start with a certain path: EXPLAIN QUERY PLAN SELECT * FROM f WHERE path LIKE "foo/%" it tells me that the table is scanned, even though the path column is indexed :( Is there any way I could make LIKE use the index and not scan the table? I found a way to achieve what I want with closure table, but it's harder to maintain and writes are extremely slow... To be able to use an index for LIKE in SQLite, the table column must have TEXT affinity , i