Sql Server 2005 novice query - sql-server

I am very beginner in SQL Server 2005 and I am learning it from online tutorial, here is some of my question:
1: What is the difference between Select * from XYZ and Select ALL * from XYZ.
2: The purpose of Clustered index is like to make the search easier by physically sorting the table [as far as I kknow :-)]. Let say if have primary column on a table than is it good to create a clustered index on the table? because we have already a column which is sorted.
3: Why we can create 1 Clustered Index + 249 Nonclustered Index = 250 Index on a table? I understand the requirement of 1 clustered index. But why 249?? Why not more than 249?

No difference SELECT ALL is the default as opposed to SELECT DISTINCT
Opinion varies. For performance reasons Clustered indexes should ideally be small, stable, unique, and monotonically increasing. Primary keys should also be stable and unique so there is an obvious fit there. However clustered indexes are well suited for range queries. Looking up individual records by PK can perform well if the PK is nonclustered so some authors suggest not "wasting" the clustered index on the PK.
In SQL Server 2008 you can create up to 999 NCIs on a table. I can't imagine ever doing so but I think the limit was raised as potentially with "filtered indexes" there might be a viable case for this many. Indexes add a cost to data modification operations though as the changes need to be propagated in multiple places so I would imagine it would only be largely read only (e.g. reporting) databases that ever achieve even double figures of non clustered non filtered indexes.

For 3:
Everytime when you insert/delete record in the table ALL indexes must be updated. If you will have too many indexes it takes too long time.
If your table have more then 5-6 indexes I think you need take the time and check yourself.

Related

What is the best choice for clustered index when the primary key can't be used?

Given an application where the primary key for most tables is uuid, what is the best choice for a clustered index on these tables?
The clustered index is required because the back-end database is Azure SQL Server and Azure requires a clustered index.
The uuid was a design choice to satisfy the need for n clients to create entities in a disconnected state and then sync when connected.
We are not using the primary key as the clustered index in order to avoid fragmentation issues due to the randomness of uuids.
Considering the following data types:
int or bigint. Easy - can be auto incrementing (good/bad) but seems so arbitrary and has limited utility. Feels most like a hack.
datetime - increased utility - could be a createdOnServer column. but would result in some dupes and thus require uniqueifiers (how big a problem this is, I don't know)
datetime2 - wider than datetime but greater precision and less dupes.
Looking for comments on which is best, things to consider, or alternative ideas.
I am not sure why you dismiss auto incrementing int. Anything that is widely used, works very well and as long as you are not planning on merging the table (via a Union) with other versions of the table why wouldn't you want to use it? It will provide a very good key (not too wide) for a balanced B Tree that clustered indexes are behind the curtain. Remember that in a table, that has a clustered index, all the other indexes will use the clustered index column to get to the desired page and row so you want to make it as small as possible.
If you don't want to create an index you can consider to upgrade/move to a V12 Azure SQL Database. These don't have the requirement for a clustered index.
On the index itself: You should create it on the columns that you query on. If you do lookups on the UUIDs + a date for example, you should create the index on the two to supported your queries.

SQL Server Indexing best practice (SQL Server 2008) [closed]

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I have some doubts on choosing the right index and have some questions:
Clustered index
What is the best candidate?
Usually is the primary key but if the primary key is not used in the search by eg CustomerNo is used to search on customers should the clustered index put on CustomerNo?
Views with SchemaBinding
If have a view with indexes I read that these are not used but those on tables are.
Pointless no? Or am I missing the point? Will it make a difference using "NOExpand" to force to read the index from the view rather than the table?
Nonclustered indexes
Is it good practice when adding a nonclustered index to include every possible column till you reach the limit?
Many thanks for your time. I am reading massive database and speed is a must
The clustered index is the index that (a) defines the storage layout of your table (the table data is physically sorted by the clustering key), and (b) is used as the "row locator" in every single nonclustered index on that table.
Therefore, the clustered index should be
narrow (4 byte is ideal, 8 byte OK - anything else is too much)
unique (if you don't use a unique clustered index, SQL Server will add a 4 byte uniqueifier to your table)
static (shouldn't change)
optimally it should be ever-increasing
fixed with - e.g. don't use large Varchar(x) columns in your clustered index
Out of these requirements, the INT IDENTITY seems to be the most logical, most obvious choice. Don't use variable length columns, don't use multiple columns (if ever possible), don't use GUID (that's a horribly bad choice because of it's size and randomness)
For more background info on clustering keys and clustered indexes - read everything that Kimberly Tripp ever publishes! She's the Queen of Indexing in SQL Server - she knows her stuff extremely well!
See e.g. these blog posts:
GUIDs as PRIMARY KEYs and/or the clustering key
The Clustered Index Debate Continues...
Ever-increasing clustering key - the Clustered Index Debate..........again!
Disk space is cheap - that's not the point!
In general: don't overindex! too many indices is often worse than none!
For non-clustered indexes: I would typically index foreign key columns - those indexes help with JOINs and other operations and make things faster.
Other than that: don't put too many indexes in your database ! Every index must be maintained on every CRUD operation on your table! This is overhead - don't excessively index!
An index with all columns of a table is an especially bad idea since it really cannot be used for much - but carries a lot of administrative overhead.
Run your app, profile it - see which operations are slow, try to optimize those by adding a few selective indexes to your table.
Clustered Indexes
Just to add to marc_s good answer, one exception to the standard INT IDENTITY PK approach to Clustered Indexes is when you have Parent Child tables, where all the children are frequently always retrieved at the same time as the parent. In this case, clustering by Child table by the Parent PK will reduce the number of pages read when the children are retrieved. For example:
CREATE TABLE Invoice
(
-- Use the default MS Approach on the parent, viz Clustered by Surrogate PK
InvoiceID INT IDENTITY(1,1) PRIMARY KEY CLUSTERED,
-- Index Fields here
);
CREATE TABLE InvoiceLineItem
(
-- Own Surrogate Key
InvoiceLineItemID INT IDENTITY(1,1) PRIMARY KEY NONCLUSTERED,
InvoiceID INT NOT NULL FOREIGN KEY REFERENCES Invoice(InvoiceID),
-- Line Item Fields Here
);
-- But Cluster on the Parent FK
CREATE CLUSTERED INDEX CL_InvoiceLineItem ON InvoiceLineItem(InvoiceID);
NonClustered Indexes
No, never just include columns without careful thought - the index tree needs to be as narrow as possible. The ordering of the index columns is critical, and always ensure that the index is designed with selectivity of the data in mind - you will need to have a good understanding of the distribution of your data in order to choose optimal indexes.
You can consider using covering indexes to include (at most, a few) columns which would otherwise have required a bookmark lookup from the Nonclustered index back into the table when tuning performance-critical queries.
As a very basic rule of thumb I use, is to use nonclustered indexes when small amounts of data will be returned and clustered indexes when larger resultsets will be returned by your query.
I recomend you read Clustered Index Design Guidelines
As for indexing views: indexing views works the same as indexing the table. It can improve preformance but like indexing tables it can also slow things down.
I recomend you read Improving Performance with SQL Server 2008 Indexed Views
In genral when indexing i find less is better. You need to research your data not just slap indexes on everthing. Check what you are linking on, add indexes and check the Execution plan. Sometimes what you think would make a good index actualy can make thing slower.
Views with SchemaBinding
...
Pointless no? Or am I missing the point?
(More properly, indexed views, schemabinding is a means to an end here, and the rest of the text is more talking about indexed views)
There can be (at least) two reasons for creating an indexed view. Without seeing your database, it's impossible to tell which of those reasons apply.
The first is to compute intermediate results which are expensive to compute from the base table. In order to benefit from that computation, you need to ensure your query uses the indexes. To use the indexes you either need to be querying the view and specifying NOEXPAND, or be using Enterprise or Developer edition (On Ent/Dev editions the index might be used even if the base table is queried and the view isn't mentioned)
The second reason is to enforce a constraint that isn't enforceable in a simpler manner, by implementing e.g. a unique constraint on the view, this may be enforcing some form of conditional uniqueness on the base table.
An example of the second - say you want table T to be able to contain multiple rows with the same U value - but of those rows, only one may be marked as the Default. Before filtered indexes were available, this was commonly achieved as:
CREATE VIEW DRI_T_OneDefault
WITH SCHEMABINDING
AS
SELECT U
FROM S.T
WHERE Default = 1
GO
CREATE UNIQUE CLUSTERED INDEX IX_DRI_T_OneDefault on DRI_T_OneDefault (U)
The point is that these indexes enforce a constraint. It doesn't matter (in such a case) whether any query every actually uses the index. In the same way that any unique constraint may be declared on a base table but never actually used in any queries.

Difference between clustered and nonclustered index [duplicate]

This question already has answers here:
What are the differences between a clustered and a non-clustered index?
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Closed 7 years ago.
I need to add proper index to my tables and need some help.
I'm confused and need to clarify a few points:
Should I use index for non-int columns? Why/why not
I've read a lot about clustered and non-clustered index yet I still can't decide when to use one over the other. A good example would help me and a lot of other developers.
I know that I shouldn't use indexes for columns or tables that are often updated. What else should I be careful about and how can I know that it is all good before going to test phase?
A clustered index alters the way that the rows are stored. When you create a clustered index on a column (or a number of columns), SQL server sorts the table’s rows by that column(s). It is like a dictionary, where all words are sorted in alphabetical order in the entire book.
A non-clustered index, on the other hand, does not alter the way the rows are stored in the table. It creates a completely different object within the table that contains the column(s) selected for indexing and a pointer back to the table’s rows containing the data. It is like an index in the last pages of a book, where keywords are sorted and contain the page number to the material of the book for faster reference.
You really need to keep two issues apart:
1) the primary key is a logical construct - one of the candidate keys that uniquely and reliably identifies every row in your table. This can be anything, really - an INT, a GUID, a string - pick what makes most sense for your scenario.
2) the clustering key (the column or columns that define the "clustered index" on the table) - this is a physical storage-related thing, and here, a small, stable, ever-increasing data type is your best pick - INT or BIGINT as your default option.
By default, the primary key on a SQL Server table is also used as the clustering key - but that doesn't need to be that way!
One rule of thumb I would apply is this: any "regular" table (one that you use to store data in, that is a lookup table etc.) should have a clustering key. There's really no point not to have a clustering key. Actually, contrary to common believe, having a clustering key actually speeds up all the common operations - even inserts and deletes (since the table organization is different and usually better than with a heap - a table without a clustering key).
Kimberly Tripp, the Queen of Indexing has a great many excellent articles on the topic of why to have a clustering key, and what kind of columns to best use as your clustering key. Since you only get one per table, it's of utmost importance to pick the right clustering key - and not just any clustering key.
GUIDs as PRIMARY KEY and/or clustered key
The clustered index debate continues
Ever-increasing clustering key - the Clustered Index Debate..........again!
Disk space is cheap - that's not the point!
Marc
You should be using indexes to help SQL server performance. Usually that implies that columns that are used to find rows in a table are indexed.
Clustered indexes makes SQL server order the rows on disk according to the index order. This implies that if you access data in the order of a clustered index, then the data will be present on disk in the correct order. However if the column(s) that have a clustered index is frequently changed, then the row(s) will move around on disk, causing overhead - which generally is not a good idea.
Having many indexes is not good either. They cost to maintain. So start out with the obvious ones, and then profile to see which ones you miss and would benefit from. You do not need them from start, they can be added later on.
Most column datatypes can be used when indexing, but it is better to have small columns indexed than large. Also it is common to create indexes on groups of columns (e.g. country + city + street).
Also you will not notice performance issues until you have quite a bit of data in your tables. And another thing to think about is that SQL server needs statistics to do its query optimizations the right way, so make sure that you do generate that.
A comparison of a non-clustered index with a clustered index with an example
As an example of a non-clustered index, let’s say that we have a non-clustered index on the EmployeeID column. A non-clustered index will store both the value of the
EmployeeID
AND a pointer to the row in the Employee table where that value is actually stored. But a clustered index, on the other hand, will actually store the row data for a particular EmployeeID – so if you are running a query that looks for an EmployeeID of 15, the data from other columns in the table like
EmployeeName, EmployeeAddress, etc
. will all actually be stored in the leaf node of the clustered index itself.
This means that with a non-clustered index extra work is required to follow that pointer to the row in the table to retrieve any other desired values, as opposed to a clustered index which can just access the row directly since it is being stored in the same order as the clustered index itself. So, reading from a clustered index is generally faster than reading from a non-clustered index.
In general, use an index on a column that's going to be used (a lot) to search the table, such as a primary key (which by default has a clustered index). For example, if you have the query (in pseudocode)
SELECT * FROM FOO WHERE FOO.BAR = 2
You might want to put an index on FOO.BAR. A clustered index should be used on a column that will be used for sorting. A clustered index is used to sort the rows on disk, so you can only have one per table. For example if you have the query
SELECT * FROM FOO ORDER BY FOO.BAR ASCENDING
You might want to consider a clustered index on FOO.BAR.
Probably the most important consideration is how much time your queries are taking. If a query doesn't take much time or isn't used very often, it may not be worth adding indexes. As always, profile first, then optimize. SQL Server Studio can give you suggestions on where to optimize, and MSDN has some information1 that you might find useful
faster to read than non cluster as data is physically storted in index order
we can create only one per table.(cluster index)
quicker for insert and update operation than a cluster index.
we can create n number of non cluster index.

Cluster the index on ever-increasing datetime column on logging table?

I'm not a DBA ("Good!", you'll be thinking in a moment.)
I have a table of logging data with these characteristics and usage patterns:
A datetime column for storing log timestamps whose value is ever-increasing and mostly (but only mostly) unique
Frequent-ish inserts (say, a dozen a minute), only at the end of the timestamp range (new data being logged)
Infrequent deletes, in bulk, from the beginning of the timestamp range (old data being cleared)
No updates at all
Frequent-ish selects using the timestamp column as the primary criterion, along with secondary criteria on other columns
Infrequent selects using other columns as the criteria (and not including the timestamp column)
A good amount of data, but nowhere near enough that I'm worried much about storage space
Additionally, there is currently a daily maintenance window during which I could do table optimization.
I frankly don't expect this table to challenge the server it's going to be on even if I mis-index it a bit, but nevertheless it seemed like a good opportunity to ask for some input on SQL Server clustered indexes.
I know that clustered indexes determine the storage of the actual table data (the data is stored in the leaf nodes of the index itself), and that non-clustered indexes are separate pointers into the data. So in query terms, a clustered index is going to be faster than a non-clustered index -- once we've found the index value, the data is right there. There are costs on insert and delete (and of course an update changing the clustered index column's value would be particularly costly).
But I read in this answer that deletes leave gaps that don't get cleaned up until/unless the index is rebuilt.
All of this suggests to me that I should:
Put a clustered index on the timestamp column with a 100% fill-factor
Put non-clustered indexes on any other column that may be used as a criterion in a query that doesn't also involve the clustered column (which may be any of them in my case)
Schedule the bulk deletes to occur during the daily maintenance interval
Schedule a rebuild of the clustered index to occur immediately after the bulk delete
Relax and get out more
Am I wildly off base there? Do I need to frequently rebuild the index like that to avoid lots of wasted space? Are there other obvious (to a DBA) things I should be doing?
Thanks in advance.
Contrary to what a lot of people believe, having a good clustered index on a table can actually make operations like INSERTs faster - yes, faster!
Check out the seminal blog post The Clustered Index Debate Continues.... by Kimberly Tripp - the ultimate indexing queen.
She mentions (about in the middle of the article):
Inserts are faster in a clustered
table (but only in the "right"
clustered table) than compared to a
heap. The primary problem here is that
lookups in the IAM/PFS to determine
the insert location in a heap are
slower than in a clustered table
(where insert location is known,
defined by the clustered key). Inserts
are faster when inserted into a table
where order is defined (CL) and where
that order is ever-increasing.
The crucial point is: only with the right clustered index will you be able to reap the benefits - when a clustered index is unique, narrow, stable and optimally ever-increasing. This is best served with an INT IDENTITY column.
Kimberly Tripp also has a great article on how to pick the best possible clustering key for your tables, and what criteria it should fulfil - see her post entitled Ever-increasing clustering key - the Clustered Index Debate..........again!
If you have such a column - e.g. a surrogate primary key - use that for your clustering key and you should see very nice performance on your table - even on lots of INSERTs.
I agree with putting the clustered index on the timestamp column. My query would be on the fillfactor - 100% gives best read performance at the expense of write performance. you may be hurt by page splits. Choosing a lower fillfactor will delay page splitting at the expense of read performance so its a fine balancing act to get the best for your situation.
After the bulk deletes its worth rebuilding the indexes and updating statistics. This not only keeps performance up but also resets the indexes to the specified fillfactor.
Finally, yes put nonclustered indexes on other appropriate columns but only ones that are very select e.g not bit fields. But remember the more indexes, the more this affects write performance
There's two "best practice" ways to index a high traffic logging table:
an integer identity column as a primary clustered key
a uniqueidentifier colum as primary key, with DEFAULT NEWSEQUENTIALID()
Both methods allow SQL Server to grow the table efficiently, because it knows that the index tree will grow in a particular direction.
I would not put any other indexes on the table, or schedule rebuilds of the index, unless there is a specific performance issue.
The obvious answer is it depends on how you will query it. The point of the index is to lessen the quantity of compares when selecting data. The clustered index helps when you consider what data you will load together and the blocking factor of the storage (you can load a bunch of data in a 64k block with one read). If you include an ID and a datetime as the primary key, but not use them in your selection criteria, they will do nothing but hinder your performance. This is why people usually drop indexes upon bulk inserts before loading data.

Should I get rid of clustered indexes on Guid columns

I am working on a database that usually uses GUIDs as primary keys.
By default SQL Server places a clustered index on primary key columns. I understand that this is a silly idea for GUID columns, and that non-clustered indexes are better.
What do you think - should I get rid of all the clustered indexes and replace them with non-clustered indexes?
Why wouldn't SQL's performance tuner offer this as a recommendation?
A big reason for a clustered index is when you often want to retrieve rows for a range of values for a given column. Because the data is physically arranged in that order, the rows can be extracted very efficiently.
Something like a GUID, while excellent for a primary key, could be positively detrimental to performance, as there will be additional cost for inserts and no perceptible benefit on selects.
So yes, don't cluster an index on GUID.
As to why it's not offered as a recommendation, I'd suggest the tuner is aware of this fact.
You almost certainly want to establish a clustered index on every table in your database.
If a table does not have a clustered index it is what is referred to as a "Heap" and performance of most types of common queries is less for a heap than for a clustered index table.
Which fields the clustered index should be established on depend on the table itself, and the expected usage patterns of queries against the table. In almost every case you probably want the clustered index to be on a column or a combination of columns that is unique, i.e., (an alternate key), because if it isn't, SQL will add a unique value to the end of whatever fields you select anyway. If your table has a column or columns in it that will be frequently used by queries to select or filter multiple records, (for example if your table contains sales transactions, and your application will frequently request sales transactions by product Id, or even better, a Invoice details table, where in almost every case you will be retrieving all the detail records for a specific invoice, or an invoice table where you often retrieve all the invoices for a particular customer... This is true whether you will be selected large numbers of records by a single value, or by a range of values)
These columns are candidates for the clustered index. The order of the columns in the clustered index is critical.. The first column defined in the index should be the column that will be selected or filtered on first in expected queries.
The reason for all this is based on understanding the internal structure of a database index. These indices are called balanced-tree (B-Tree) indices. they are kinda like a binary tree, except that each node in the tree can have an arbitrary number of entries, (and child nodes), instead of just two. What makes a clustered index different is that the leaf nodes in a clustered index are the actual physical disk data pages of the table itself. whereas the leaf nodes of the non-clustered index just "point" to the tables' data pages.
When a table has a clustered index, therefore, the tables data pages are the leaf level of that index, and each one has a pointer to the previous page and the next page in the index order (they form a doubly-linked-list).
So if your query requests a range of rows that is in the same order as the clustered index... the processor only has to traverse the index once (or maybe twice), to find the start page of the data, and then follow the linked list pointers to get to the next page and the next page, until it has read all the data pages it needs.
For a non-clustered index, it has to traverse the index once for every row it retrieves...
NOTE: EDIT
To address the sequential issue for Guid Key columns, be aware that SQL2k5 has NEWSEQUENTIALID() that does in fact generate Guids the "old" sequential way.
or you can investigate Jimmy Nielsens COMB guid algotithm that is implemented in client side code:
COMB Guids
The problem with clustered indexes in a GUID field are that the GUIDs are random, so when a new record is inserted, a significant portion of the data on disk has to be moved to insert the records into the middle of the table.
However, with integer-based clustered indexes, the integers are normally sequential (like with an IDENTITY spec), so they just get added to the end an no data needs to be moved around.
On the other hand, clustered indexes are not always bad on GUIDs... it all depends upon the needs of your application. If you need to be able to SELECT records quickly, then use a clustered index... the INSERT speed will suffer, but the SELECT speed will be improved.
While clustering on a GUID is normally a bad idea, be aware that GUIDs can under some circumstances cause fragmentation even in non-clustered indexes.
Note that if you're using SQL Server 2005, the newsequentialid() function produces sequential GUIDs. This helps to prevent the fragmentation problem.
I suggest using a SQL query like the following to measure fragmentation before making any decisions (excuse the non-ANSI syntax):
SELECT OBJECT_NAME (ips.[object_id]) AS 'Object Name',
si.name AS 'Index Name',
ROUND (ips.avg_fragmentation_in_percent, 2) AS 'Fragmentation',
ips.page_count AS 'Pages',
ROUND (ips.avg_page_space_used_in_percent, 2) AS 'Page Density'
FROM sys.dm_db_index_physical_stats
(DB_ID ('MyDatabase'), NULL, NULL, NULL, 'DETAILED') ips
CROSS APPLY sys.indexes si
WHERE si.object_id = ips.object_id
AND si.index_id = ips.index_id
AND ips.index_level = 0;
If you are using NewId(), you could switch to NewSequentialId(). That should help the insert perf.
Yes, there's no point in having a clustered index on a random value.
You probably do want clustered indexes SOMEWHERE in your database. For example, if you have a "Author" table and a "Book" table with a foreign key to "Author", and if you have a query in your application that says, "select ... from Book where AuthorId = ..", then you would be reading a set of books. It will be faster if those book are physically next to each other on the disk, so that the disk head doesn't have to bounce around from sector to sector gathering all the books of that author.
So, you need to think about your application, the ways in which it queries the database.
Make the changes.
And then test, because you never know...
As most have mentioned, avoid using a random identifier in a clustered index-you will not gain the benefits of clustering. Actually, you will experience an increased delay. Getting rid of all of them is solid advice. Also keep in mind newsequentialid() can be extremely problematic in a multi-master replication scenario. If database A and B both invoke newsequentialid() prior to replication, you will have a conflict.
Yes you should remove the clustered index on GUID primary keys for the reasons Galwegian states above. We have done this on our applications.
It depends if you're doing a lot of inserts, or if you need very quick lookup by PK.

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