query-optimization

问题 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 回答1: With an INNER join the two

问题 CREATE TABLE `files` ( `did` int(10) unsigned NOT NULL DEFAULT '0', `filename` varbinary(200) NOT NULL, `ext` varbinary(5) DEFAULT NULL, `fsize` double DEFAULT NULL, `filetime` datetime DEFAULT NULL, PRIMARY KEY (`did`,`filename`), KEY `fe` (`filetime`,`ext`), -- This? KEY `ef` (`ext`,`filetime`) -- or This? ) ENGINE=InnoDB DEFAULT CHARSET=utf8 ; There are a million rows in the table. The filetimes are mostly distinct. There are a finite number of ext values. So, filetime has a high

问题 CREATE TABLE `files` ( `did` int(10) unsigned NOT NULL DEFAULT '0', `filename` varbinary(200) NOT NULL, `ext` varbinary(5) DEFAULT NULL, `fsize` double DEFAULT NULL, `filetime` datetime DEFAULT NULL, PRIMARY KEY (`did`,`filename`), KEY `fe` (`filetime`,`ext`), -- This? KEY `ef` (`ext`,`filetime`) -- or This? ) ENGINE=InnoDB DEFAULT CHARSET=utf8 ; There are a million rows in the table. The filetimes are mostly distinct. There are a finite number of ext values. So, filetime has a high

问题 I have following queries First one using inner join SELECT item_ID,item_Code,item_Name FROM [Pharmacy].[tblitemHdr] I INNER JOIN EMR.tblFavourites F ON I.item_ID=F.itemID WHERE F.doctorID = @doctorId AND F.favType = 'I' second one using sub query like SELECT item_ID,item_Code,item_Name from [Pharmacy].[tblitemHdr] WHERE item_ID IN (SELECT itemID FROM EMR.tblFavourites WHERE doctorID = @doctorId AND favType = 'I' ) In this item table [Pharmacy].[tblitemHdr] Contains 15 columns and 2000 records

问题 Database System Concepts introduce several ways to implement a join operation. Two of them are merge join and hash join. I was wondering when the optimizer decides to use a merge join and when a hash join? In particular, from https://stackoverflow.com/a/1114288/156458 hash joins can only be used for equi-joins, but merge joins are more flexible. But Database System Concepts says both are used only for equi joins and natural joins. The merge-join algorithm (also called the sort-merge-join

问题 I need to add a new non-null column to an existing SQL table and set it to a default value. I understand that there are two different approaches to this: ALTER TABLE Foo ADD Col CHAR(1) NOT NULL DEFAULT('N') ALTER TABLE Foo ADD Col CHAR(1) GO UPDATE Foo SET Col = 'N' GO ALTER TABLE Foo ALTER COLUMN Col CHAR(1) NOT NULL DEFAULT('N') That is, in the second approach, there are three separate batches: first the column is created, then the default value is backfilled, and then the not null

问题 I'm doing some test to see the capability of Postgresql query performance. And my plan is to disable/enable different query optimizations, such as disable (automatic) index, disable re-order joins etc. is there some configuration to achieve this quickly or what part source code should I revise? thanks. 回答1: PostgreSQL provides debug parameters for exactly this. See the enable_ params in the docs. Please don't use them in production; it might seem like a good idea at the time, but those

问题 I have this query, Declare @Prcocessrate float declare @item varchar(20) declare @process varchar(20) declare @branch varchar(20) set @item = 'shirt' set @process = 'kt' set @branch = '1' select @Prcocessrate = ProcessPrice from itemwiseprocessrate where itemname=@Item and Process=@process and branchid=@branch when I run it single handed, the execution plan only shows 3 steps , see for youself.. but I have this procedure sp_newBooking as ALTER PROC sp_newbooking -- other arguements-- AS BEGIN

问题 I have a 1 GB mysql table with three colums (german bigrams): create table sortedindex (source varchar(60),target varchar(60),score float) engine=myisam character set utf8 collate utf8_bin; I also created a composite index: create index sortedstd_ix on sortedindex (source(60), target(60), score); additionally I compressed the table and made it read only and sorted the index using: myisamchk --keys-used=0 -rq sortedindex myisampack sortedindex myisamchk -rq sortedindex --sort_buffer=3G --sort

问题 I'm trying to run what I believe to be a simple query on a fairly large dataset, and it's taking a very long time to execute -- it stalls in the "Sending data" state for 3-4 hours or more. The table looks like this: CREATE TABLE `transaction` ( `id` bigint(20) unsigned NOT NULL AUTO_INCREMENT, `uuid` varchar(36) NOT NULL, `userId` varchar(64) NOT NULL, `protocol` int(11) NOT NULL, ... A few other fields: ints and small varchars `created` datetime NOT NULL, PRIMARY KEY (`id`), KEY `uuid` (