It's my understanding that nulls are not indexable in DB2, so assuming we have a huge table (Sales) with a date column (sold_on) which is normally a date, but is occasionally (10% of the time) null.
Furthermore, let's assume that it's a legacy application that we can't change, so those nulls are staying there and mean something (let's say sales that were returned).
We can make the following query fast by putting an index on the sold_on and total columns
Select * from Sales
where
Sales.sold_on between date1 and date2
and Sales.total = 9.99
But an index won't make this query any faster:
Select * from Sales
where
Sales.sold_on is null
and Sales.total = 9.99
Because the indexing is done on the value.
Can I index nulls? Maybe by changing the index type? Indexing the indicator column?
From where did you get the impression that DB2 doesn't index NULLs? I can't find anything in documentation or articles supporting the claim. And I just performed a query in a large table using a IS NULL restriction involving an indexed column containing a small fraction of NULLs; in this case, DB2 certainly used the index (verified by an EXPLAIN, and by observing that the database responded instantly instead of spending time to perform a table scan).
So: I claim that DB2 has no problem with NULLs in non-primary key indexes.
But as others have written: Your data may be composed in a way where DB2 thinks that using an index will not be quicker. Or the database's statistics aren't up-to-date for the involved table(s).
I'm no DB2 expert, but if 10% of your values are null, I don't think an index on that column alone will ever help your query. 10% is too many to bother using an index for -- it'll just do a table scan. If you were talking about 2-3%, I think it would actually use your index.
Think about how many records are on a page/block -- say 20. The reason to use an index is to avoid fetching pages you don't need. The odds that a given page will contain 0 records that are null is (90%)^20, or 12%. Those aren't good odds -- you're going to need 88% of your pages to be fetched anyway, using the index isn't very helpful.
If, however, your select clause only included a few columns (and not *) -- say just salesid, you could probably get it to use an index on (sold_on,salesid), as the read of the data page wouldn't be needed -- all the data would be in the index.
The rule of thumb is that an index is useful for values up on to 15% of the records. ... so an index might be useful here.
If DB2 won't index nulls, then I would suggest adding a boolean field, IsSold, and set it to true whenever the sold_on date gets set (this could be done in a trigger).
That's not the nicest solution, but it might be what you need.
Troels is correct; even rows with a SOLD_ON value of NULL will benefit from an index on that column. If you're doing ranged searches on SOLD_ON, you may benefit even more by creating a clustered index that begins with SOLD_ON. In this particular example, it may not require much additional overhead to maintain the clustering order based on SOLD_ON, since newer rows added will most likely have a newer SOLD_ON date.
Related
I need to filter out data that exceeds a certain length but the column that contains the data is an indexed column. If I apply a function to the column I lose the benefit of the index.
I cannot create a new index or alter the column as I am not an admin to the database.
I would prefer not to drop the data after the fact.
I know of a few ways to filter the column but all would use some kind of function.
select
table.name
from
table
where
length(table.name)>12
;
The field table.name is not nullable.
If I apply a function to the column I lose the benefit of the index.
Ah, but what is the benefit of an index?
Consider these two values:
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
Are they both longer than 12 characters? Yes. Are they likely to be adjacent in the index? Of course not. Therefore the only way for Oracle to use an index to find those values is to execute a Full Fast Scan over the index and evaluate the length of each entry. Now Oracle can do that, but is it worthwhile?
Your posted query is selecting just name. In a comment you say name is not nullable. In that case it would be efficient for Oracle to use the index, because there is no need to read the table records: the index has sufficient information to satisfy the query.
However.
In that comment you also say:
the query is not that simple
If your actual query includes other columns in the projection then the database does have to visit the table to get those values. At which point the rule of thumb for indexed reads kicks in: if the result set of the query is greater than 1-2% of all the rows in the table it's more efficient to do a Full Table Scan than use an index. So the number of records in the table becomes pertinent, and especially the proportion of records where length(name) > 12. If 99% of the records have short names then it is probably still more efficient to Full Fast Scan the index. But if it's only 90% using the index would probably be deadly to performance.
Likewise, if your actual query applies additional criteria in the WHERE clause it may be more efficient to do a Full Table Scan (because the database needs to read the records to evaluate those filters) to to use a different index, if there is an appropriate one.
So, while the index would be useful for the toy query you posted in your question it may not help with your actual query, and indeed could lead to a sub-optimal access path.
is it a case by case situation depending on query complexity?
Yes. The answer is always, it depends. That's why database tuning professionals can charge the fat consultancy fees they do. If you don't provide the whole query the best we can do is point you at this post which explains to ask performance tuning questions and wish you good luck.
If the column is NOT NULL, then Oracle can answer the query using a full index scan. It will need to read every row in the index in order to find only those rows with the length greater than 12. If the index is smaller than the table this is faster than a full scan.
You are only selecting the indexed column so Oracle would not need to visit the table but can get the result entirely from the index. If you were to select other columns there were not in that index Oracle would also need to read the table row having first located the row in the index.
There is no way around this without adding a more suitable index or otherwise changing the database schema.
I have an sql query which fetch the first N rows in a table which is designed as a low-level queue.
select top N * from my_table where status = 0 order by date asc
The intention behind this query is as follows:
First, this question is intended to be database agnostic, as my implementation will support sql server, oracle, DB2 and sybase. The sql syntax above of "top N" is just an example.
The table can contain millions of rows.
N is a relatively small number in comparison, e.g. 100.
status is 0 when the row is in the queue. Later it is changed to 1 to indicate that it is in processing. After processing it is deleted. So it is expected that at least 90% of the rows in the table will be with status 0.
rows in the table should be fetched according to their date, hence the order by clause.
What is the optimal index to make this query works fastest?
I initially thought the index should be on (date, status), but I am not sure about it anymore. Since the status column will contain mostly zeros, is there an added-value to it? Will it be sufficient to index by (date) alone?
Or maybe it should be (status, date)?
I don't think there is an efficient solution that will be RDMS independent. For example, Oracle has bitmap indexes, SQLServer has partial indexes, and I don't see reasons not to use them if, for instance, Mysql or Sqlite has nothing similar. Also, historically SQLServer implements clustered tables (or IOT in Oracle world) way better than Oracle does, so having clustered index on date column may work perfectly for SQLServer, but not for Oracle.
I'd rather change approach a bit. If you say 90% of rows don't satisfy status=0 condition, why not try refactoring schema, and adding a new table (or materialized view) that holds only records you are interested in ? The number of new programmable objects required for keeping that table up-to-date and merging data with original table is relatively small even if RDMS doesn't support materialized view directly. Also, if it's possible to redesign underlying logic, so rows never updated, only inserted or deleted, then it will help avoiding lock contentions , and as a result , the whole system will have a better performance .
Have a clustered index on Date and a non clustered index on Status.
I would like to add index(s) to my table.
I am looking for general ideas how to add more indexes to a table.
Other than the PK clustered.
I would like to know what to look for when I am doing this.
So, my example:
This table (let's call it TASK table) is going to be the biggest table of the whole application. Expecting millions records.
IMPORTANT: massive bulk-insert is adding data in this table
table has 27 columns: (so far, and counting :D )
int x 9 columns = id-s
varchar x 10 columns
bit x 2 columns
datetime x 5 columns
INT COLUMNS
all of these are INT ID-s but from tables that are usually smaller than Task table (10-50 records max), example: Status table (with values like "open", "closed") or Priority table (with values like "important", "not so important", "normal")
there is also a column like "parent-ID" (self - ID)
join: all the "small" tables have PK, the usual way ... clustered
STRING COLUMNS
there is a (Company) column (string!) that is something like "5 characters long all the time" and every user will be restricted using this one. If in Task there are 15 different "Companies" the logged in user would only see one. So there's always a filter on this one. Might be a good idea to add an index to this column?
DATE COLUMNS
I think they don't index these ... right? Or can / should be?
I wouldn't add any indices - unless you have specific reasons to do so, e.g. performance issues.
In order to figure out what kind of indices to add, you need to know:
what kind of queries are being used against your table - what are the WHERE clauses, what kind of ORDER BY are you doing?
how is your data distributed? Which columns are selective enough (< 2% of the data) to be useful for indexing
what kind of (negative) impact do additional indices have on your INSERTs and UPDATEs on the table
any foreign key columns should be part of an index - preferably as the first column of the index - to speed up JOINs to other tables
And sure you can index a DATETIME column - what made you think you cannot?? If you have a lot of queries that will restrict their result set by means of a date range, it can make total sense to index a DATETIME column - maybe not by itself, but in a compound index together with other elements of your table.
What you cannot index are columns that hold more than 900 bytes of data - anything like VARCHAR(1000) or such.
For great in-depth and very knowledgeable background on indexing, consult the blog by Kimberly Tripp, Queen of Indexing.
in general an index will speed up a JOIN, a sort operation and a filter
SO if the columns are in the JOIN, the ORDER BY or the WHERE clause then an index will help in terms of performance...but there is always a but...with every index that you add UPDATE, DELETE and INSERT operations will be slowed down because the indexes have to be maintained
so the answer is...it depends
I would say start hitting the table with queries and look at the execution plans for scans, try to make those seeks by either writing SARGable queries or adding indexes if needed...don't just add indexes for the sake of adding indexes
Step one is to understand how the data in the table will be used: how will it be inserted, selected, updated, deleted. Without knowing your usage patterns, you're shooting in the dark. (Note also that whatever you come up with now, you may be wrong. Be sure to compare your decisions with actual usage patterns once you're up and running.) Some ideas:
If users will often be looking up individual items in the table, an index on the primary key is critical.
If data will be inserted with great frequency and you have multiple indexes, over time you well have to deal with index fragmentation. Read up on and understand clustered and non-clustered indexes and fragmentation (ALTER INDEX...REBUILD).
But, if performance is key in situations when you need to retrieve a lot of rows, you might consider using your clustered indexe to support that.
If you often want a set of data based on Status, indexing on that column can be good--particularly if 1% of your rows are "Active" vs. 99% "Not Active", and all you want are the active ones.
Conversely, if your "PriorityId" is only used to get the "label" stating what PriorityId 42 is (i.e. join into the lookup table), you probably don't need an index on it in your main table.
A last idea, if everyone will always retrieve data for only one Company at a time, then (a) you'll definitely want to index on that, and (b) you might want to consider partitioning the table on that value, as it can act as a "built in filter" above and beyond conventional indexing. (This is perhaps a bit extreme and it's only available in Enterprise edition, but it may be worth it in your case.)
I have created script to find selectivity of each columns for every tables. In those some tables with less than 100 rows but selectivity of column is more than 50%.
where Selectivity = Distinct Values / Total Number Rows
So, is those column are eligible for index?
Or, can you tell, how much minimum rows require for eligibility for creating index?
I think I understand what you are trying to accomplish by calculating a 'Selectivity' value for your data but you cannot apply the rule blindly.
In fact in for certain queries the 'Selectivity' value might be really low an index will still be very beneficial. For example:
Assume a 'inbox' table with millions of rows, these rows have a 'Read' boolean field. In this case the distinct values over the number of rows will be really low. If most items are read most of the time then finding unread items with an index on this field will be very efficient.
Creating indexes index come at a cost. Although you get the benefit for reads, you pay for writes and disk usage.
I would rather recommend you profile your queries and index accordingly. You can also look at the data from sys.dm_db_missing_index_group_stats and other Dynamic management views that will give you insight on indexes usage (or missing) ones.
You can create a index on a table with 0 rows, 1 row or a 100 million rows. You can create an index where every column has the same value or unique values.
So you can create an index. The question is really should you create an index and no tool is going to tell you that because indexes can also be multi-value and it depends on what queries you run. Creating indexes is something done when performance tuning queries or preemptively when you know that you'll be creating queries that are using it.
Every index comes with a cost in terms of space and time required to do updates, inserts and deletes. You don't want to be creating them spuriously so you're really going to have to do this by hand, not as a result of a script to see how unique the value of a column is.
A general rule of thumb says that if you have a very large table (over 1 million rows), you should only use an index if a WHERE clause based on that index selects at most something in the neighborhood of 1-2% of the data.
If you have a "gender" column and roughly 50% of values are "male" and roughly 50% "female", then having an index on that really doesn't give you much - SQL Server and most other RDBMS will most likely still do a full table scan in this case, since on average, they'd have to scan at least half the table anyway, so the "detour" by using an index first and then looking up the actual full data based on that index value is just not worth it.
An index is excellent if you have something like unique keys (customer number), or a value that is quite selective. An index is not without cost - it uses up disk space, it needs to be maintained, it will slightly slow down all operations besides the SELECT - so thread carefully, it's not the best idea to just blindly index everything. Having too few indices is bad - but having too many, and the wrong ones, can be even worse! :-) Nobody ever claimed getting your indices right was easy.... :-)
But there's definitely help out there - the best source I know are Kimberly Tripp's excellent blog posts on SQL Server indexing (and many other topics).
Marc
If I have a query like:
Select EmployeeId
From Employee
Where EmployeeTypeId IN (1,2,3)
and I have an index on the EmployeeTypeId field, does SQL server still use that index?
Yeah, that's right. If your Employee table has 10,000 records, and only 5 records have EmployeeTypeId in (1,2,3), then it will most likely use the index to fetch the records. However, if it finds that 9,000 records have the EmployeeTypeId in (1,2,3), then it would most likely just do a table scan to get the corresponding EmployeeIds, as it's faster just to run through the whole table than to go to each branch of the index tree and look at the records individually.
SQL Server does a lot of stuff to try and optimize how the queries run. However, sometimes it doesn't get the right answer. If you know that SQL Server isn't using the index, by looking at the execution plan in query analyzer, you can tell the query engine to use a specific index with the following change to your query.
SELECT EmployeeId FROM Employee WITH (Index(Index_EmployeeTypeId )) WHERE EmployeeTypeId IN (1,2,3)
Assuming the index you have on the EmployeeTypeId field is named Index_EmployeeTypeId.
Usually it would, unless the IN clause covers too much of the table, and then it will do a table scan. Best way to find out in your specific case would be to run it in the query analyzer, and check out the execution plan.
Unless technology has improved in ways I can't imagine of late, the "IN" query shown will produce a result that's effectively the OR-ing of three result sets, one for each of the values in the "IN" list. The IN clause becomes an equality condition for each of the list and will use an index if appropriate. In the case of unique IDs and a large enough table then I'd expect the optimiser to use an index.
If the items in the list were to be non-unique however, and I guess in the example that a "TypeId" is a foreign key, then I'm more interested in the distribution. I'm wondering if the optimiser will check the stats for each value in the list? Say it checks the first value and finds it's in 20% of the rows (of a large enough table to matter). It'll probably table scan. But will the same query plan be used for the other two, even if they're unique?
It's probably moot - something like an Employee table is likely to be small enough that it will stay cached in memory and you probably wouldn't notice a difference between that and indexed retrieval anyway.
And lastly, while I'm preaching, beware the query in the IN clause: it's often a quick way to get something working and (for me at least) can be a good way to express the requirement, but it's almost always better restated as a join. Your optimiser may be smart enough to spot this, but then again it may not. If you don't currently performance-check against production data volumes, do so - in these days of cost-based optimisation you can't be certain of the query plan until you have a full load and representative statistics. If you can't, then be prepared for surprises in production...
So there's the potential for an "IN" clause to run a table scan, but the optimizer will
try and work out the best way to deal with it?
Whether an index is used doesn't so much vary on the type of query as much of the type and distribution of data in the table(s), how up-to-date your table statistics are, and the actual datatype of the column.
The other posters are correct that an index will be used over a table scan if:
The query won't access more than a certain percent of the rows indexed (say ~10% but should vary between DBMS's).
Alternatively, if there are a lot of rows, but relatively few unique values in the column, it also may be faster to do a table scan.
The other variable that might not be that obvious is making sure that the datatypes of the values being compared are the same. In PostgreSQL, I don't think that indexes will be used if you're filtering on a float but your column is made up of ints. There are also some operators that don't support index use (again, in PostgreSQL, the ILIKE operator is like this).
As noted though, always check the query analyser when in doubt and your DBMS's documentation is your friend.
#Mike: Thanks for the detailed analysis. There are definately some interesting points you make there. The example I posted is somewhat trivial but the basis of the question came from using NHibernate.
With NHibernate, you can write a clause like this:
int[] employeeIds = new int[]{1, 5, 23463, 32523};
NHibernateSession.CreateCriteria(typeof(Employee))
.Add(Restrictions.InG("EmployeeId",employeeIds))
NHibernate then generates a query which looks like
select * from employee where employeeid in (1, 5, 23463, 32523)
So as you and others have pointed out, it looks like there are going to be times where an index will be used or a table scan will happen, but you can't really determine that until runtime.
Select EmployeeId From Employee USE(INDEX(EmployeeTypeId))
This query will search using the index you have created. It works for me. Please do a try..