NHibernate taking a long time to run query - nhibernate

This is being done using Fluent NHibernate
I've got a NHibernate lookup that is retrieving data from one table. If i take the generated sql and run it through query analyzer, it takes ~18ms to run.
Using NHProfiler, i'm getting the duration of this query as ~1800ms - 100 times longer than sql !
Query duration
- Database only:1800ms
- Total: 1806ms
The object that is being populated contains a child class, but this child is being loaded from the NHibernate 2nd level cache
The data that is being returned is paged (50 per query) although as far as i can tell, this shouldn't make any difference
I've also got a count running, and again, this is taking ~4ms in query analyzer and ~1800ms according to NHProfiler.
Is NH Profiler displaying the query execution time, or the complete time to retrieve, map the classes and construct the object graph? And if it's the former - why's it taking so much longer than running the query directly?
EDIT: Just found this post by Ayende about the Query Duration value given in NH Profiler: http://ayende.com/Blog/archive/2009/06/28/nh-prof-query-duration.aspx - so it is definitely the query of the database that is taking a long time

Finally managed to track down the problem.
The primary key for the object is a varchar in the database. NHibernate was converting the value to an nvarchar when it ran the query. Unfortunately this wasn't obvious when looking at the generated sql in NH Profiler. The slowdown was caused by sql converting the nvarchar back to a varchar
I've specified the mapping to use a custom type
map.Id(x => x.Id).CustomType("AnsiString");
and the problem is solved
Cheers for all the help people :)

generally these problems resolve to the network between you and your data base. QA usually connects directly to the data base and all it has to send is the raw data back where its formatted. Your app is probably converting your result set into a data set or similar construct. To prove this, change a bit of code (not your entire data layer) to use a SQL Data Reader to read your data. Just read all of the records without trying to parse out all of the columns and save the data. It will likely perform as fast as your network will let it.

Related

Query fast with literal but slow with variable

I am using Typeorm for SQL Server in my application. When I pass the native query like connection.query(select * from user where id = 1), the performance is really good and it less that 0.5 seconds.
If we use the findone or QueryBuilder method, it is taking around 5 seconds to get a response.
On further debugging, we found that passing value directly to query like this,
return getConnection("vehicle").createQueryBuilder()
.select("vehicle")
.from(Vehicle, "vehicle")
.where("vehicle.id='" + id + "'").getOne();
is faster than
return getConnection("vehicle").createQueryBuilder()
.select("vehicle")
.from(Vehicle, "vehicle")
.where("vehicle.id =:id", {id:id}).getOne();
Is there any optimization we can do to fix the issue with parameterized query?
I don't know Typeorm but it seems to me clear the difference. In one case you query the database for the whole table and filter it locally and in the other you send the filter to the database and it filters the data before it sends it back to the client.
Depending on the size of the table this has a big impact. Consider picking one record from 10 million. Just the time to transfer the data to the local machine is 10 million times slower.

Pre-calculated JOIN queries as map in ignite

I am new to ignite and POCing currently.
I have a question regarding ways to store/load data in map. It's bit tricky and strange requirement.
Example:
I have Employee, Department, Project [Tables in database] + [Entity classes in application].
But I don't want to store each of these in a separate map in memory but rather I want to store pre-calculated join results in a designated map.
Dynamic Query : select employeeId,employeeName,departmentName,projectName,projectStart,projectEnd from Employee,Department,Project where $JOIN
I know at least before hand that, what would be key fields and what would be value fields. From above example, I can denote my "Map" as shown below,
Key : Set (employeeId,departmentId)
Value : List (employeeName,value),(departmentName,value),(projectName,value),(projectStart,value),(projectEnd,value)
So you can see with every pair of (employeeId,departmentId) I would be having multiple values associates with it. But dilemma is I don't have domain model/entity pojos before hand. Such dynamic views/maps can be added flexibly so that we don't have to go and change domain/entity model every time. We don't want to do joins/calculations every time for thousands of such client request on every call.
Is it possible to fire such join queries using MapLoader or by any other means?
I can think of Map with (Key=Set, Value = List)as data structure to store final results.Any other better alternative?
Could there be any performance issues while retrieving values from such map based on keys?
Any memory optimizations I should take care of?
Thanks,
Dharam
You are not required to use SQL queries. It's fine to use Ignite as a simple caching mechanism for DB query results. Each time a query is executed, save the result in IgniteCache and then use this cached result is the same query is requested. You can also use expirations [1] and/or evictions [2] to make sure that you don't have too much data in the cache and don't run out of memory.
[1] https://apacheignite.readme.io/docs/expiry-policies
[2] https://apacheignite.readme.io/docs/evictions

Need for long and dynamic select query/view sqlite

I have a need to generate a long select query of potentially thousands of where conditions like (table1.a = ? OR table1.a = ? OR ...) AND (table2.b = ? OR table2.b = ? ...) AND....
I initially started building a class to make this more bearable, but have since stopped to wonder if this will work well. This query is going to be hammering a table of potentially 10s of millions of rows joined with 2 more tables with thousands of rows.
A number of concerns are stemming from this:
1.) I wanted to use these statements to generate a temp view so I could easily transfer over existing code base, the point here is I want to filter data that I have down for analysis based on selected parameters in a GUI, so how poorly will a view do in this scenario?
2.) Can sqlite even parse a query with thousands of binds?
3.) Isn't there a framework that can make generating this query easier other than with string concatenation?
4.) Is the better solution to dump all of the WHERE variables into hash sets in memory and then just write a wrapper for my DB query object that gets next() until a query is encountered this satisfies all my conditions? My concern here is, the application generates graphs procedurally on scrolls, so waiting to draw while calling query.next() x 100,000 might cause an annoying delay? Ideally I don't want to have to wait on the next row that satisfies everything for more than 30ms at a time.
edit:
New issue, it came to my attention that sqlite3 is limited to 999 bind values(host parameters) at compile time.
So it seems as if the only way to accomplish what I had originally intended is to
1.) Generate the entire query via string concatenations(my biggest concern being, I don't know how slow parsing all the data inside sqlite3 will be)
or
2.) Do the blanket query method(select * from * where index > ? limit ?) and call next() until I hit what valid data in my compiled code(including updating index variable and re-querying repeatedly)
I did end up writing a wrapper around the QSqlQuery object that will walk a table using index > variable and limit to allow "walking" the table.
Consider dumping the joined results without filters (denormalized) into a flat file and index it with Fastbit, a bitmap index engine.

django objects...values() select only some fields

I'm optimizing the memory load (~2GB, offline accounting and analysis routine) of this line:
l2 = Photograph.objects.filter(**(movie.get_selectors())).values()
Is there a way to convince django to skip certain columns when fetching values()?
Specifically, the routine obtains all rows of the table matching certain criteria (db is optimized and performs it very quickly), but it is a bit too much for python to handle - there is a long string referenced in each row, storing the urls for thumbnails.
I only really need three fields from each row, but, if all the fields are included, it suddenly consumes about 5kB/row which sadly pushes the RAM to the limit.
The values(*fields) function allows you to specify which fields you want.
Check out the QuerySet method, only. When you declare that you only want certain fields to be loaded immediately, the QuerySet manager will not pull in the other fields in your object, till you try to access them.
If you have to deal with ForeignKeys, that must also be pre-fetched, then also check out select_related
The two links above to the Django documentation have good examples, that should clarify their use.
Take a look at Django Debug Toolbar it comes with a debugsqlshell management command that allows you to see the SQL queries being generated, along with the time taken, as you play around with your models on a django/python shell.

SQL server string manipulation in a view... Or in XSLT

I have been passed a piece of work that I can either do in my application or perhaps in SQL:
I have to get a date out of a string that may look like this:
1234567-DSP-01/01-VER-01/01
or like this:
1234567-VER-01/01-DSP-01/01
but may look like this:
00 12345 DISCH 01/01-VER-01/01 XXX X XXXXX
Yay. if it is a "DSP" then I want that date, if a "DISCH" then that date.
I am pulling the data out in a SQL Server view and would be happy to have the view transform the data for me. My application could do it but would add processor time. I could also see if the data could be manipulated before it is entered into the DB, I suppose.
Thank you for your time.
An option would be to check for the presence of DSP or DISCH then substring out the date as necessary.
For example (I don't have sqlserver today so I can verify syntax, sorry)
select
date = case date_attribute
when charindex('DSP',date_attribute) > 0 then substring(date_attribute,beg,end)
when charindex('DISCH',date_attribute) > 0 then substring(date_attribute,beg,end)
else 'unknown'
end
from myTable
don't store multiple items in the same column!
store the date in its own column when inserting the row!
add a new nullable column for the date
write an update that pulls the date out and sets the new column
alter the column to be not nullable
fix your save routine to pull the date out and insert it in for you
If you do it in the view your adding processing time on SQL which in general a more expensive resource then an app, web or some other type of client.
I'd recommend you try and format the data out when you insert the data, or you handle in the application tier. Scaling horizontally an app tier is so much easier then scalling your SQL.
Edit
I am talking the database server's physical resources are usually more expensive then a properly designed applications server's physical resources. This is because it is very easy to scale an application horizontally, it is in my opinion an order of magnitude more expensive to scale a DB server horizontally. Especially if your dealing with a transactional database and need to manage merging
I am not saying it is not possible just that scaling a database server horizontally is a much more difficult task, hence it's more expensive. The only reason I pointed this out is the OP raised a concern about using CPU cycles on the app server vs the database server. Most applications I have worked with have been data centric applications which processed through GB's of data to get a user an answer. We initially put everything on the database server because it was easier then doing it in classic asp and vb6 at the time. Over time the DB server was more and more loaded until scaling veritcally was no longer an option.
Database Servers are also designed at retrieving and joining data together. You should leave the formating of the data to the application and business rules (in general of course)