When inserting large sets of data into a table (from another table, in no particular order), how do you optimize a multi-column index so that the index is updated in the fastest possible way?
Assume the index is never used in any SELECT, DELETE or UPDATE query.* Assume also that the distinct counts for the columns as follows (for example):
COLUMN | DISTINCT COUNT
col1 | 634
col2 | 9,923
col3 | 2,357
col4 | 3
* Reason for not using the index in selecting data is this is a primary key index or a unique constraint index. The index is in place so that inserts violating the constraint should fail.
I have read that the most selective column should come first. Is that correct, and is the index then to be created as follows?
(col2, col3, col1, col4)
If that is wrong, how do you determine the best order for column in an index which will only see bulk INSERTs into the corresponding table? The goal is to speed up the updating of the index during the bulk INSERT.
The quickest way is to DROP INDEX, then do the bulk inserts and CREATE INDEX when you are done inserting.
The proper structure of the index does not have so much to do with the distribution of values in the columns but with the retrieval strategies, presumably for UPDATE and DELETE only, and then specifically when you do partial filtering on some but not all always all columns of the index. Those more frequent filters should come first in your index columns. But you probably want to reconsider your indexing strategy more radically if this is the case: it may be better to have two or more indexes to match your typical retrieval strategies.
Ignoring your call for ignorance: why would you not apply the index to SELECT statements? Indexes are useful only for selecting subsets of data from your tables, whether that is for SELECT or a qualified UPDATE or DELETE. There is no functional difference for using indexes in any of these three operations.
Addendum after comments from OP: Indexes are useful for many purposes but their maintenance is relatively expensive, where "relatively" becomes "impossibly" very quickly with increasing table size. In your case you have to compare every record from your source table with every record in your destination table, or O(m*n) order. That is unworkable with tables of a large size, even with an index. Your best bet is to drop the index, do the inserts, create an index which is not unique, find and delete all duplicates, drop the index, finally create a new unique index.
The order of the columns is not terribly important for a uniqueness enforcement purposes. But it would be unusual for a unique index to not also happen to be useful for some queries, and so I would order the columns to take advantage of that.
For bulk inserting into this index rapidly, I'd try inserting in index order. So add an order by (col2, col3, col1, col4) to the select part of your insert. This leads to more efficient IO.
Related
I am new to query optimization in T-SQL and I am a bit confused with one of the implementations.
The scenario has been explained here: I have this table (Table A) on which regular inserts are happening, no updates - only inserts as data is being moved to another table (Table B) based on a filter on a particular column in Table A (Col-1).
Two columns in Table A which I am focusing on are Col-1 (identity column) and Col-2 (nvarchar(20) -- and has duplicates).
Col-2 is on which I am filtering my records when moving my data from Table A to Table B.
Should I be defining a clustered index on Col-1 and a nonclustered index on Col-2, since I am filtering on Col-2; or should I only define a nonclustered index on Col-2 to speed up query performance?
Or should I keep the table as Heap and only define nonclustered index on the Col-2.
Moreover, would defining a clustered index and storing the table as a B-Tree degrade performance as we are appending data into Table -A weekly through inserts.
Thanks for the help.
As many here have said, it's hard to say definitively what will be the best solution without testing. However, you say that you are filtering by col2 before choosing to move data. Depending on what percentage of those records are moved, I would suggest starting with clustering on the unique col1. Then create a non-clustered index on col2. One advantage of the non-clustered index is that you can make it a filtered index with a WHERE clause. So, for example, if only 10% of your records have a col2 value from a few choices that you care about, the index 'WHERE col2 IN (val, val2, val3) will be 10x smaller and therefore faster to access.
If you go this route, make sure the WHERE clause in your SELECT matches the WHERE clause you specify on the index.
In Oracle, if I make a composite index on 2 columns, then in which situation this index will be used to search the record ?
a) If my query has a WHERE clause which involves first column
e.g. WHERE first_column = 'John'
b) If my query has a WHERE clause which involves second column
e.g. WHERE second_column = 'Sharma'
c) Either a or b
d) Both a and b
e) Not specifically these 2 columns but it could be any column in the WHERE clause.
f) Only column a or both columns a and b
I happen to think that MySQL does a pretty good job of describing how composite indexes are used. The documentation is here.
The basic idea is that the index would normally be used in the following circumstances:
When the where condition is an equality on col1 (col1 = value).
When the where condition is an inequality or in on col1 (col1 in (list), col1 < value)
When the where condition is an equality on col1 and col2, connected by an and (col1 = val1 and col2 = val2)
When the where condition is an equality on col1 and an inequality or in on col2.
Any of the above four cases where additional columns are used with additional conditions on other columns, connected by an and.
In addition, the index would normally be used if col1 and col2 are the only columns referenced in the query. This is called a covering index, and -- assuming there are other columns in the table -- it is faster to read the index than the original table because the index is smaller.
Oracle has a pretty smart optimizer, so it might also use the index in some related circumstances, for instance when col1 uses an in condition along with a condition on col2.
In general, a condition will not qualify for an index if the column is an argument to a function. So, these clauses would not use a basic index:
where month(col1) = 3
where trunc(col1) = trunc(sysdate)
where abs(col1) < 1
Oracle supports functional indexes, so if these constructs are actually important, you can create an index on month(col1), trunc(col1), or abs(col1).
Also, or tends to make the use of indexes less likely.
d) Both a or b
If the leading column is used, Oracle will likely use a regular index range scan and just ignore the unused columns.
If a non-leading column is used, Oracle can use an index skip scan. In practice a skip scan is not used very often.
There are two completely different questions here: when can Oracle use an index and when will Oracle use an index. The above explains that Oracle can use an index in either case, and you can test that out with a hint: /*+ index(table_name index_name) */.
Determining when Oracle will use an index is much trickier. Oracle uses multi-block reads for full table scans and fast full index scans, and uses single-block reads for other index scans. This means a full table scan is more efficient when reading a larger percent of the data. But there are a lot of factors involved: the percentage of data, how big is the index, system statistics that tell Oracle how fast single- and multi-block IO are, the number of distinct values (especially important for choosing a skip scan), index clustering factor (how ordered is the table by the index columns), etc.
The optimizer will use indexes in several scenarios. Even if not "perfect".
Optimaly, if you are querying using the first columns in the index, then the index will be used. Even if you're referencing only the first column, then it will still use the index if the optimizer deems it filters out enough data.
If the indexed columns aren't answering the query requirement (for instance only referencing the second column in the where clause), the optimizer could still use the index for a full (table) index scan, if it holds all of the data required, because the index is smaller than the full table.
In your example, if you are only querying from that table, and you only have that one index, (a) will use the index, (b) will use it if you are only querying columns in the index, while the table itself has more.
If you have other indexes, or join other tables, then that could affect the explain plan compeltely.
Check out http://docs.oracle.com/cd/B19306_01/server.102/b14231/indexes.htm
While studying for the 70-433 exam I noticed you can create a covering index in one of the following two ways.
CREATE INDEX idx1 ON MyTable (Col1, Col2, Col3)
-- OR --
CREATE INDEX idx1 ON MyTable (Col1) INCLUDE (Col2, Col3)
The INCLUDE clause is new to me. Why would you use it and what guidelines would you suggest in determining whether to create a covering index with or without the INCLUDE clause?
If the column is not in the WHERE/JOIN/GROUP BY/ORDER BY, but only in the column list in the SELECT clause is where you use INCLUDE.
The INCLUDE clause adds the data at the lowest/leaf level, rather than in the index tree.
This makes the index smaller because it's not part of the tree
INCLUDE columns are not key columns in the index, so they are not ordered.
This means it isn't really useful for predicates, sorting etc as I mentioned above. However, it may be useful if you have a residual lookup in a few rows from the key column(s)
Another MSDN article with a worked example
You would use the INCLUDE to add one or more columns to the leaf level of a non-clustered index, if by doing so, you can "cover" your queries.
Imagine you need to query for an employee's ID, department ID, and lastname.
SELECT EmployeeID, DepartmentID, LastName
FROM Employee
WHERE DepartmentID = 5
If you happen to have a non-clustered index on (EmployeeID, DepartmentID), once you find the employees for a given department, you now have to do "bookmark lookup" to get the actual full employee record, just to get the lastname column. That can get pretty expensive in terms of performance, if you find a lot of employees.
If you had included that lastname in your index:
CREATE NONCLUSTERED INDEX NC_EmpDep
ON Employee(DepartmentID)
INCLUDE (Lastname, EmployeeID)
then all the information you need is available in the leaf level of the non-clustered index. Just by seeking in the non-clustered index and finding your employees for a given department, you have all the necessary information, and the bookmark lookup for each employee found in the index is no longer necessary --> you save a lot of time.
Obviously, you cannot include every column in every non-clustered index - but if you do have queries which are missing just one or two columns to be "covered" (and that get used a lot), it can be very helpful to INCLUDE those into a suitable non-clustered index.
This discussion is missing out on the important point: The question is not if the "non-key-columns" are better to include as index-columns or as included-columns.
The question is how expensive it is to use the include-mechanism to include columns that are not really needed in index? (typically not part of where-clauses, but often included in selects). So your dilemma is always:
Use index on id1, id2 ... idN alone or
Use index on id1, id2 ... idN plus include col1, col2 ... colN
Where:
id1, id2 ... idN are columns often used in restrictions and col1, col2 ... colN are columns often selected, but typically not used in restrictions
(The option to include all of these columns as part of the index-key is just always silly (unless they are also used in restrictions) - cause it would always be more expensive to maintain since the index must be updated and sorted even when the "keys" have not changed).
So use option 1 or 2?
Answer: If your table is rarely updated - mostly inserted into/deleted from - then it is relatively inexpensive to use the include-mechanism to include some "hot columns" (that are often used in selects - but not often used on restrictions) since inserts/deletes require the index to be updated/sorted anyway and thus little extra overhead is associated with storing off a few extra columns while already updating the index. The overhead is the extra memory and CPU used to store redundant info on the index.
If the columns you consider to add as included-columns are often updated (without the index-key-columns being updated) - or - if it is so many of them that the index becomes close to a copy of your table - use option 1 I'd suggest! Also if adding certain include-column(s) turns out to make no performance-difference - you might want to skip the idea of adding them:) Verify that they are useful!
The average number of rows per same values in keys (id1, id2 ... idN) can be of some importance as well.
Notice that if a column - that is added as an included-column of index - is used in the restriction: As long as the index as such can be used (based on restriction against index-key-columns) - then SQL Server is matching the column-restriction against the index (leaf-node-values) instead of going the expensive way around the table itself.
Basic index columns are sorted, but included columns are not sorted. This saves resources in maintaining the index, while still making it possible to provide the data in the included columns to cover a query. So, if you want to cover queries, you can put the search criteria to locate rows into the sorted columns of the index, but then "include" additional, unsorted columns with non-search data. It definitely helps with reducing the amount of sorting and fragmentation in index maintenance.
One reason to prefer INCLUDE over key-columns if you don't need that column in the key is documentation. That makes evolving indexes much more easy in the future.
Considering your example:
CREATE INDEX idx1 ON MyTable (Col1) INCLUDE (Col2, Col3)
That index is best if your query looks like this:
SELECT col2, col3
FROM MyTable
WHERE col1 = ...
Of course you should not put columns in INCLUDE if you can get an additional benefit from having them in the key part. Both of the following queries would actually prefer the col2 column in the key of the index.
SELECT col2, col3
FROM MyTable
WHERE col1 = ...
AND col2 = ...
SELECT TOP 1 col2, col3
FROM MyTable
WHERE col1 = ...
ORDER BY col2
Let's assume this is not the case and we have col2 in the INCLUDE clause because there is just no benefit of having it in the tree part of the index.
Fast forward some years.
You need to tune this query:
SELECT TOP 1 col2
FROM MyTable
WHERE col1 = ...
ORDER BY another_col
To optimize that query, the following index would be great:
CREATE INDEX idx1 ON MyTable (Col1, another_col) INCLUDE (Col2)
If you check what indexes you have on that table already, your previous index might still be there:
CREATE INDEX idx1 ON MyTable (Col1) INCLUDE (Col2, Col3)
Now you know that Col2 and Col3 are not part of the index tree and are thus not used to narrow the read index range nor for ordering the rows. Is is rather safe to add another_column to the end of the key-part of the index (after col1). There is little risk to break anything:
DROP INDEX idx1 ON MyTable;
CREATE INDEX idx1 ON MyTable (Col1, another_col) INCLUDE (Col2, Col3);
That index will become bigger, which still has some risks, but it is generally better to extend existing indexes compared to introducing new ones.
If you would have an index without INCLUDE, you could not know what queries you would break by adding another_col right after Col1.
CREATE INDEX idx1 ON MyTable (Col1, Col2, Col3)
What happens if you add another_col between Col1 and Col2? Will other queries suffer?
There are other "benefits" of INCLUDE vs. key columns if you add those columns just to avoid fetching them from the table. However, I consider the documentation aspect the most important one.
To answer your question:
what guidelines would you suggest in determining whether to create a covering index with or without the INCLUDE clause?
If you add a column to the index for the sole purpose to have that column available in the index without visiting the table, put it into the INCLUDE clause.
If adding the column to the index key brings additional benefits (e.g. for order by or because it can narrow the read index range) add it to the key.
You can read a longer discussion about this here:
https://use-the-index-luke.com/blog/2019-04/include-columns-in-btree-indexes
The reasons why (including the data in the leaf level of the index) have been nicely explained. The reason that you give two shakes about this, is that when you run your query, if you don't have the additional columns included (new feature in SQL 2005) the SQL Server has to go to the clustered index to get the additional columns which takes more time, and adds more load to the SQL Server service, the disks, and the memory (buffer cache to be specific) as new data pages are loaded into memory, potentially pushing other more often needed data out of the buffer cache.
An additional consideraion that I have not seen in the answers already given, is that included columns can be of data types that are not allowed as index key columns, such as varchar(max).
This allows you to include such columns in a covering index. I recently had to do this to provide a nHibernate generated query, which had a lot of columns in the SELECT, with a useful index.
There is a limit to the total size of all columns inlined into the index definition. That said though, I have never had to create index that wide.
To me, the bigger advantage is the fact that you can cover more queries with one index that has included columns as they don't have to be defined in any particular order. Think about is as an index within the index.
One example would be the StoreID (where StoreID is low selectivity meaning that each store is associated with a lot of customers) and then customer demographics data (LastName, FirstName, DOB):
If you just inline those columns in this order (StoreID, LastName, FirstName, DOB), you can only efficiently search for customers for which you know StoreID and LastName.
On the other hand, defining the index on StoreID and including LastName, FirstName, DOB columns would let you in essence do two seeks- index predicate on StoreID and then seek predicate on any of the included columns. This would let you cover all possible search permutationsas as long as it starts with StoreID.
Suppose that I created a compound primary key on col1, col2, col3, will indices be created on each of the column?
I know that the primary key constraint will create index for the combination of (col1, col2, col3) so that the search on these 3 columns will be faster. But I'm not sure if the database will create index on each of the column so that the search on individual column, like search on column2, will be speed up.
Can anybody tell me what happens on these columns in term of index?
It depends. Generally one index will be created so only queries using the "left most" columns can make use of it, i.e. in your example "SELECT * from T where COL2='x'" will not use the index. That said, Oracle can use an index "skip" where the first column is kind of compressed and the plan can jump past it looking at the next column in.
Your best approach would be to look at the manual and try it in the DBMS of your choice then look at the query plan.
Summary: it depends.
I am not db guy. But I need to create tables and do CRUD operations on them. I get confused should I create the index on all columns by default
or not? Here is my understanding which I consider while creating index.
Index basically contains the memory location range ( starting memory location where first value is stored to end memory location where last value is
stored). So when we insert any value in table index for column needs to be updated as it has got one more value but update of column
value wont have any impact on index value. Right? So bottom line is when my column is used in join between two tables we should consider
creating index on column used in join but all other columns can be skipped because if we create index on them it will involve extra cost of
updating index value when new value is inserted in column.Right?
Consider this scenario where table mytable contains two three columns i.e col1,col2,col3. Now we fire this query
select col1,col2 from mytable
Now there are two cases here. In first case we create the index on col1 and col2. In second case we don't create any index.** As per my understanding
case 1 will be faster than case2 because in case 1 we oracle can quickly find column memory location. So here I have not used any join columns but
still index is helping here. So should I consider creating index here or not?**
What if in the same scenario above if we fire
select * from mytable
instead of
select col1,col2 from mytable
Will index help here?
Don't create Indexes in every column! It will slow things down on insert/delete/update operations.
As a simple reminder, you can create an index in columns that are common in WHERE, ORDER BY and GROUP BY clauses. You may consider adding an index in colums that are used to relate other tables (through a JOIN, for example)
Example:
SELECT col1,col2,col3 FROM my_table WHERE col2=1
Here, creating an index on col2 would help this query a lot.
Also, consider index selectivity. Simply put, create index on values that has a "big domain", i.e. Ids, names, etc. Don't create them on Male/Female columns.
but update of column value wont have any impact on index value. Right?
No. Updating an indexed column will have an impact. The Oracle 11g performance manual states that:
UPDATE statements that modify indexed columns and INSERT and DELETE
statements that modify indexed tables take longer than if there were
no index. Such SQL statements must modify data in indexes and data in
tables. They also create additional undo and redo.
So bottom line is when my column is used in join between two tables we should consider creating index on column used in join but all other columns can be skipped because if we create index on them it will involve extra cost of updating index value when new value is inserted in column. Right?
Not just Inserts but any other Data Manipulation Language statement.
Consider this scenario . . . Will index help here?
With regards to this last paragraph, why not build some test cases with representative data volumes so that you prove or disprove your assumptions about which columns you should index?
In the specific scenario you give, there is no WHERE clause, so a table scan is going to be used or the index scan will be used, but you're only dropping one column, so the performance might not be that different. In the second scenario, the index shouldn't be used, since it isn't covering and there is no WHERE clause. If there were a WHERE clause, the index could allow the filtering to reduce the number of rows which need to be looked up to get the missing column.
Oracle has a number of different tables, including heap or index organized tables.
If an index is covering, it is more likely to be used, especially when selective. But note that an index organized table is not better than a covering index on a heap when there are constraints in the WHERE clause and far fewer columns in the covering index than in the base table.
Creating indexes with more columns than are actually used only helps if they are more likely to make the index covering, but adding all the columns would be similar to an index organized table. Note that Oracle does not have the equivalent of SQL Server's INCLUDE (COLUMN) which can be used to make indexes more covering (it's effectively making an additional clustered index of only a subset of the columns - useful if you want an index to be unique but also add some data which you don't want to be considered in the uniqueness but helps to make it covering for more queries)
You need to look at your plans and then determine if indexes will help things. And then look at the plans afterwards to see if they made a difference.