I created a non-clustered index on "last_name" column in the table "Persons"
Select * From Persons
Where last_name = 'Hogg'
So why is the index incapable of returning all the columns simultaneously and instead does a RID lookup?
How does indexing work here?
The index only covers the column last_name, and only contains data about that column. You can conceptually think about the index that you've described as a series of pairs: (last_name,row), where row is a reference to a particular row in the actual table. The index stores the pairs sorted by last_name, but stores no additional information about the table.
Your query requests all of the columns of Persons. The index is used to locate the row or rows where last_name is "Hogg", but the database has to reference the table to retrieve the additional columns.
What you appear to want is a covering index for the columns of interest. The term "RID lookup" implies SQL Server. Perhaps the question What are Covering Indexes and Covered Queries in SQL Server? and the page it points to: Using Covering Indexes to Improve Query Performance will help.
Related
I have a unique index on (id, name) columns. I have a date column that I want to add to the index since I want the uniqueness to be based on (id, name, date) columns. The date column contains a lot of null values. How would it affect the index?
If you are using SQL Server, so in SQL Server null values are not included in the index structure, But SQL Server has some new features, one of the filtering index. If a field has many null values so recommended creating an additional filtering index using where the field is null condition.
For more information about filtering index visit this link
Final result: You can do your add index operations comfortably, without problems, in many Databases null values don't affect performance.
We have big transaction tables, it has all the values (including duplicates), need to eliminate the duplicate values based on other table values.
Table A (Transaction table) has Store, Date, Index , Etc values
Table B maintain the Index ranges, it has Store, Date, Index Begin, Index End etc.
Based on Store, Date need to compare index from table A with Table B (Table B has index Range values), eliminate the ranges of index values from Table A, so I can avoid duplicate values.
If the given index is not in range of Index Begin and Index End, I can keep that. Indexes range starts from 1. But I need to keep 1, it's a header record.
It has to check from Index 2 onwards. If you could please help with SQL statement that would be great.
Tried with few statements, did not work.
Need to eliminate duplicate records based on Index ranges from table B
To eliminate the duplicates use the key word DISTINCT after SELECT, so SELECT DISTINCT. You'll need to write a JOIN statement that compares the two tables based on the common value.
I assume you already have a query so I won't write one unless you comment needing help:)
Assuming that the database is already populated with data, and that each of the following SQL statements is the one and only query that an application will perform, why is it better to use row-wise or column-wise record storage for the following queries?...
1) SELECT * FROM Person
2) SELECT * FROM Person WHERE id=5
3) SELECT AVG(YEAR(DateOfBirth)) FROM Person
4) INSERT INTO Person (ID,DateOfBirth,Name,Surname) VALUES(2e25,’1990-05-01’,’Ute’,’Muller’)
In those examples Person.id is the primary key.
The article Row Store and Column Store Databases gives a general discussion on this, but I am specifically concerned about the four queries above.
SELECT * FROM ... queries are better for row stores since it has to access numerous files.
Column store is good for aggregation over large volume of date or when you have quesries that only need a few fields from a wide table.
Therefore:
1st querie: row-wise
2nd query: row-wise
3rd query: column-wise
4th query: row-wise
I have no idea what you are asking. You have this statement:
INSERT INTO Person (ID, DateOfBirth, Name, Surname)
VALUES('2e25', '1990-05-01', 'Ute', 'Muller');
This suggests that you have a table with four columns, one of which is an id. Each person is stored in their own column.
You then have three queries. The first cannot be optimized. The second is optimized, assuming that id is a primary key (a reasonable assumption). The third requires a full table scan -- although that could be ameliorated with an index only on DateOfBirth.
If the data is already in this format, why would you want to change it?
This is a very simple data structure. Three of your four query examples access all columns. I see no reason why you would not use a regular row-store table structure.
Assuming I have a table in Azure SQL DB with a million rows. What are the ways I can optimize the table for performing queries using WHERE clause. Column 1 is for the id which is the primary key. Column 2 to 5 is for addresses (St, city, state, zip) and columns 6 to 8 are digits.
Look into indexes. If you are going to search by address, add an index on address fields. If most searches are by zip code, add an index on that field. For more info on indexes have a look at this document Index Table
I have a transaction table and a inventory table that I would like to 'JOIN' together. The tables need to 'JOIN' on three primary keys.
My question is: should I create a unique key (concatenation of the three fields) and create a 'INDEX' on the unique key or would I just create a non-clustered 'INDEX' on all three fields?
I'm currently using SQL Server 2014
I'm guessing the Transaction table is the biggest and the Inventory is the smaller. A lot depends on what proportion of the data would you expect to be returned by your join - If its most then a table scan will probably occur so an index wont help much. If your going to try and get a small subset of date then create an index on the 3 columns on both tables and create a foreign key from Trans to Inventory on the 3 cols. (SQL Server needs an index as well as a FK)
Pick the most granular column as the first in your index as this will encourage SQL servers Optimiser to use the index.