![]() So it's not about JOIN or WHERE, it's about the access methods, scan versus seek. For a fragmented index, regardless of data type, you'll see worse performance for scans than for a non-fragmented index. For a fragmented index, regardless of the data type, you'll see almost exactly the same performance for a single row lookup as you do for a non-fragmented index. It's not where they are in the query that matters. There is no real difference in the JOIN or the WHERE criteria between these two. ![]() Performance wise which is good in "join" condition and in "where" condition. Table consists of 2 columns col1 INT/GUID, col2 varchar(1000)Īvg_fragmentation_in_percent, fragment_count, page_count If i use NEWSEQUENTIALID() then there will be less fragmentation ok good, but how about the join behavioural ?įor the test of 1000 record on a table with INT/GUID here is the fragmentation information Why not just go with INT? That's 4 bytes, half the size of bigint and supports up to 2.1 billion values (double that if you seed your identity column at -2.1 billion). Except for the fragmentation, really, GUID isn't all that big a deal, assuming most of your queries are point lookups with minimal scans.īut, you're only talking about 10s of millions of values and a 50gb database. An index scan, and, under most circumstances, the bigint will work better. A point join, meaning an index seek with no or limited scanning, they'll be the same. For a JOIN, either will work as described. For scans, again, fewer records per page and possibly a lot more fragmentation means more reads for the GUID. For point lookups, they're pretty much the same as bigint. Because GUIDs are random (unless you can use NEWSEQUENTIALID to generate your GUIDs) you're likely to get a lot more fragmentation of the index, clustered or non-clustered. ![]() This means with the GUID, you'll have fewer values per page which can lead to a larger, deeper index. That alone affects the distribution of the data across the key pages in any b-tree of a clustered or non-clustered index. A GUID is 16 bytes while a bigint is 8 bytes. This will insert a default unique value to the Id column.Well, a lot of the information is right there in the SQL Server documentation. When inserting the records, we simply have to specify “default” as value for the first column. This will ensure that whenever a new record is inserted in the EngStudents1 table, by default, the NEWID() function generates a unique value for the Id column. To set a default value for the column we will use the default keyword and set the default value as the value returned by the ‘NEWID()’ function. Let’s create a table EngStudents1 within the EngDB but this time we change the data type of the Id column from INT to UNIQUEIDENTIFIER. Now, let’s see how GUID can be used to solve this issue This causes the violation of primary key constraint for the Students table. You can see that students Shane and Sally both have Ids of 1 while Jonny and Edward both have Ids of 2. This is when we need to use the GUID data type. However, what if we want records to have unique values across multiple databases? For instance, we want that the Id column of the EnglishStudents table and the MathStudents table to have unique values, even if they belong to different databases.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |