Data Access from single table in sql server 2005 is too slow -


The script of the table below is very slow to access the data from this table.

  Go to set QUOTED_IDENTIFIER on ANSI_NULLS GO CREATE TABLE [dbo]. [Email] ([id] [int] identified (1,1) NOT NULL, [DateCreated] [datetime] NULL restriction [DF_Emails_datecreated] default (getdate ()), [UID] [nvarchar] (250) Impedance Latin1_General_CI_AS zero, [the] [nvarchar] (100) Impedance Latin1_General_CI_AS zero, [to] [Nvarchar] (100) cOLLATE Latin1_General_CI_AS nULL, [subject] [nvarchar] (maximum) cOLLATE Latin 1_General_CI_AS nULL, [body] [nvarchar] (maximum ) COLLATE Latin 1_General_CI_AS nULL, [HTML] [nvarchar] (maximum) COLLATE Latin1_General_CI_AS nULL, [Atacmentkount] [int] zero [date] [datetime] to zero) [primary]  

It takes 50 seconds to fetch query data After Land.

  • ID unique cluster
  • non-exclusive

  • Non-unique non-compressed
  • Tabls currently has 180000+ records.

    There can be 100,000 records per month, so it will slow down during the time.

    Will partition data solve the problem in two tables? What other indexes should be?

This is almost certainly the amount of data that is causing a problem. For this reason, you should not have to bring the topic column until you need it. Even the difficulty of getting SUBSTRING (subject to submission, 100) can be quite fast.

It may be irrelevant, but if the previous columns of the previous SQL Server were not in the Blob columns, then just as an experiment I had the step for [AttachmentCount] and [date] three nvarchar (max) above the column.


Comments

Popular posts from this blog

windows - Heroku throws SQLITE3 Read only exception -

lex - Building a lexical Analyzer in Java -

python - rename keys in a dictionary -