Understanding SQL query complexity - postgresql

I'm currently having trouble understanding why a seemingly simple query is taking much longer to return results than a much more complicated (looking) query.
I have a view, performance_summary (which in turn selects from another view). Currently, within psql, when I run a query like
SELECT section
FROM performance_summary
LIMIT 1;
it takes a minute or so to return a result, whereas a query like
SELECT section, version, weighted_approval_rate
FROM performance_summary
WHERE version in ('1.3.10', '1.3.11') AND section ~~ '%WEST'
ORDER BY 1,2;
gets results almost instantly. Without knowing how the view is defined, is there any obvious or common reason why this is?

Not really, without knowing how the view is defined. It could be that the "more complex" query uses an index to select just two rows and then perform some trivial grouping sorting on the two. The query without the where clause might see postgres operating on millions of rows, trillions of operations and producing a single row out after discarding 999999999 rows, we just don't know unless you post the view definition and the explain plan output for both queries
You might be falling into the trap of thinking that a View is somehow a cache of info - it isn't. It's a stored query, that is inserted into the larger query when you select from it/include it in another query- this means that the whole thing must be planned and executed from scratch. There isn't a notion that creating a View does any pre planning etc, onto which other further improvement is done. It's more like the definition of the View is pasted into any query that uses it, then the query is run as if it were just written there and then

Related

kdb: getting one row from HDB

For a normal table, we can select one row using select[1] from t. How can I do this for HDB?
I tried select[1] from t where date=2021.02.25 but it gives error
Not yet implemented: it probably makes sense, but it’s not defined nor implemented, and needs more thinking about as the language evolves
select[n] syntax works only if table is already loaded in memory.
The easiest way to get 1st row of HDB table is:
1#select from t where date=2021.02.25
select[n] will work if applied on already loaded data, e.g.
select[1] from select from t where date=2021.02.25
I've done this before for ad-hoc queries by using the virtual index i, which should avoid the cost of pulling all data into memory just to select a couple of rows. If your query needs to map constraints in first before pulling a subset, this is a reasonable solution.
It will however pull N rows for each date partition selected due to the way that q queries work under the covers. So YMMV and this might not be the best solution if it was behind an API for example.
/ 5 rows (i[5] is the 6th row)
select from t where date=2021.02.25, sum=`abcd, price=1234.5, i<i[5]
If your table is date partitioned, you can simply run
select col1,col2 from t where date=2021.02.25,i=0
That will get the first record from 2021.02.25's partition, and avoid loading every record into memory.
Per your first request (which is different to above) select[1] from t, you can achieve that with
.Q.ind[t;enlist 0]

Using Views and CTE on DB2/AS400

a Generic question..
I have an employee Table(EMPMAST) which has the New as well old Employee data. There is a flag called Current? which is 'Y' if he/she is a current employee.
Now I have to select records in my SQLRPGLE with only the current records and also some other criteria's(For Example EMPNAME = 'SAM') .What is the best way to deal with it. (in terms of performance and system usage)
To create a View over the EMPMAST with Current? = 'Y'. Then use it in the program with other conditions.
Use a CTE(With AS) in the Program which would have the Condition Current = 'Y' and use it.
use the table directly without CTE and View
any other option
Options 1, 2 and 3 would all perform the same. They would likely all have the same optimized query and access plan.
A CTE vs. a View are two different things. A View would be appropriate for a query that is going to be used in multiple locations, A CTE is only available in the query in which it is defined. I usually don't use the CTE except to replace a complex subquery. In your case the condition is simple enough to be contained in the where clause so I don't see the need to introduce additional complexity.
Some folks will tell you not to query the table directly in the program, but to always use a view. That way you add an extra layer of insulation between the program and the database, and you can still define record structures with ExtName, and not have to worry about changes to the table unless they affect the view itself. In this case you would likely have a dedicated view for each program that uses the table.
I tend to just use a hybrid of these techniques. I query tables, CTE's, or Views depending on the situation, and define my record structures explicitly in the program. I prefer to just query the table, but if I have some complex query logic which is unique to the program, I will use a CTE. I do have a few Views, but these are limited to those queries that happen in multiple programs where I want to ensure the same logic is applied consistently.

SQL Query with a little bit more complicated WHERE clause performance issue

I have some performance issue in this case:
Very simplified query:
SELECT COUNT(*) FROM Items WHERE ConditionA OR ConditionB OR ConditionC OR ...
Simply I have to determine how many Items the user has access through some complicated conditions.
When there is a large number of records (100,000+) in the Items table and say ~10 complicated conditions concatenated in WHERE clause, I get the result about 2 seconds in my case. The problem is when a very few conditions are met, f.e. when I get only 10 Items from 100,000.
How can I improve the performace in this "Get my items" case?
Additional information:
the query is generated by EF 6.1
MS SQL 2012 Express
SQL Execution Plan
Add an additional table to your schema. Instead of building a long query, insert the value for each condition into this new table, along with a key for that user/session. Then, JOIN the two tables together.
This should perform much better, because it will allow the database engine to make better use of indexes on your Items table.
Additionally, this will position you to eventually pre-define sets of permissions for your users, such that you don't need to insert them right at the moment you do the check. The permission sets will already be in the table, and the new table can also be indexed, which will improve performance further.

T-SQL speed comparison between LEFT() vs. LIKE operator

I'm creating result paging based on first letter of certain nvarchar column and not the usual one, that usually pages on number of results.
And I'm not faced with a challenge whether to filter results using LIKE operator or equality (=) operator.
select *
from table
where name like #firstletter + '%'
vs.
select *
from table
where left(name, 1) = #firstletter
I've tried searching the net for speed comparison between the two, but it's hard to find any results, since most search results are related to LEFT JOINs and not LEFT function.
"Left" vs "Like" -- one should always use "Like" when possible where indexes are implemented because "Like" is not a function and therefore can utilize any indexes you may have on the data.
"Left", on the other hand, is function, and therefore cannot make use of indexes. This web page describes the usage differences with some examples. What this means is SQL server has to evaluate the function for every record that's returned.
"Substring" and other similar functions are also culprits.
Your best bet would be to measure the performance on real production data rather than trying to guess (or ask us). That's because performance can sometimes depend on the data you're processing, although in this case it seems unlikely (but I don't know that, hence why you should check).
If this is a query you will be doing a lot, you should consider another (indexed) column which contains the lowercased first letter of name and have it set by an insert/update trigger.
This will, at the cost of a minimal storage increase, make this query blindingly fast:
select * from table where name_first_char_lower = #firstletter
That's because most database are read far more often than written, and this will amortise the cost of the calculation (done only for writes) across all reads.
It introduces redundant data but it's okay to do that for performance as long as you understand (and mitigate, as in this suggestion) the consequences and need the extra performance.
I had a similar question, and ran tests on both. Here is my code.
where (VOUCHER like 'PCNSF%'
or voucher like 'PCLTF%'
or VOUCHER like 'PCACH%'
or VOUCHER like 'PCWP%'
or voucher like 'PCINT%')
Returned 1434 rows in 1 min 51 seconds.
vs
where (LEFT(VOUCHER,5) = 'PCNSF'
or LEFT(VOUCHER,5)='PCLTF'
or LEFT(VOUCHER,5) = 'PCACH'
or LEFT(VOUCHER,4)='PCWP'
or LEFT (VOUCHER,5) ='PCINT')
Returned 1434 rows in 1 min 27 seconds
My data is faster with the left 5. As an aside my overall query does hit some indexes.
I would always suggest to use like operator when the search column contains index. I tested the above query in my production environment with select count(column_name) from table_name where left(column_name,3)='AAA' OR left(column_name,3)= 'ABA' OR ... up to 9 OR clauses. My count displays 7301477 records with 4 secs in left and 1 second in like i.e where column_name like 'AAA%' OR Column_Name like 'ABA%' or ... up to 9 like clauses.
Calling a function in where clause is not a best practice. Refer http://blog.sqlauthority.com/2013/03/12/sql-server-avoid-using-function-in-where-clause-scan-to-seek/
Entity Framework Core users
You can use EF.Functions.Like(columnName, searchString + "%") instead of columnName.startsWith(...) and you'll get just a LIKE function in the generated SQL instead of all this 'LEFT' craziness!
Depending upon your needs you will probably need to preprocess searchString.
See also https://github.com/aspnet/EntityFrameworkCore/issues/7429
This function isn't present in Entity Framework (non core) EntityFunctions so I'm not sure how to do it for EF6.

Does DataReader.NextResult retrieves the result is always the same order

I have a SELECT query that yields multiple results and do not have any ORDER BY clause.
If I execute this query multiple times and then iterate through results using DataReader.NextResult(), would I be guaranteed to get the results in the same order?
For e.g. if I execute the following query that return 199 rows:
SELECT * FROM products WHERE productid < 200
would I always get the first result with productid = 1 and so on?
As far as I have observed it always return the results in same order, but I cannot find any documentation for this behavior.
======================================
As per my research:
Check out this blog Conor vs. SQL. I actually wanted to ask if the query-result changes even if the data in table remains the same (i.e no update or delete). But it seems like in case of large table, when SQL server employees parallelism, the order can be different
First of all, to iterate the rows in a DataReader, you should call Read, not NextResult.
Calling NextResult will move to the next result set if your query has multiple SELECT statements.
To answer your question, you must not rely on this.
A query without an ORDER BY clause will return rows in SQL Server's default iteration order.
For small tables, this will usually be the order in which the rows were added, but this is not guaranteed and is liable to change at any time. For example, if the table is indexed or partitioned, the order will be different.
No, DataReader will return the results in the order they come back from SQL. If you don't specify an ORDER BY clause, that will be the order that they exist in the table.
It is possible, perhaps even likely that they will always return in the same order, but this isn't guaranteed. The order is determined by the queryplan (at least in SQL Server) on the database server. If something changes that queryplan, the order could change. You should always use ORDER BY if the order of results is in anyway important to your processing of the data.