I'm learning about Oracle Views and I got the concept of views but little confused about performance.
I was watching video and there I listen that oracle view can increase the performance. Suppose I have created view like below.
CREATE VIEW SALES_MAN
AS
SELECT * FROM EMP WHERE JOB='SALESMAN';
Ok now I have executed query to get SALES_MAN detail.
SELECT * FROM SALES_MAN
Ok now confusion start.
I listened in video that once the above query SELECT * FROM SALES_MAN will be executed the DATA/RECORD will be placed into cache memory after hitting the oracle DB. and if I will execute same query( IN Current Session/Login ) Oracle Engine will not hit to Database and will give you record from CACHED-MEMORY is it right?
But I have read on many websites that View add nothing to SQL performance more
Another Reference that says view not help in performance. Here
So Views increase performance too or not?
A view is just a kind of virtual table defined by a query. It has no proper data and performance will depend on the underlying table(s) and the query definition.
But you also have Materialized View wich stores the results from the view query definition. Data is synchronized automatically, and you can add indexes to the view. In this case, you can achieve better performances. The cost to pay is
more space (the view contains data dupplicated),
no access to the up to date data from the underlying tables
You (and perhaps the creator of the un-cited video) are confusing two different concepts. The reason the data that was in the cache was used on the second execution was NOT because it was the second execution of the view. As long as data remains in the cache, it is available for ANY query that needs it. The very fact that the first execution of the view had to get the data from disk should be a strong clue. And what if your second use of the view wasn't until hours or days later when the data was no longer in the cache? The answer remains. A view does NOT improve performance.
Related
My case is that a third party prepares a table in our schema domain on which we run different spring batch jobs that look for mutations (diff between the given third party table and our own tables). This table will contain about 200k records on average.
My question is simply: does generating a material view up front provide any benefits vs running the query at runtime?
Since the third party table will be populated on our command (basically it's a db boolean field that is set to 1, after which a scheduler picks it up to populate the table. Don't ask me why it's done this way), the query needs to run anyway.
Obviously from an application point of view, it seems more performant to query a flat material view. However, I'm not sure if there is any real performance benefit, since the material view needs to be built on db level.
Thanks.
The benefit of a materialized view here is if you are running the multiple times (more so if the query is expensive and / or there is a big drop in cardinality).
If you are only hitting the query once then you there isn't going to be a huge amount in it. You are running the same query either way and you have the overhead of inserting into the materialized view but you also have the benefit that you can tune this a lot easier than you could querying via JPA and could apply things like compression so less data is transferred back to the application but for 200k rows any difference is likely to be small.
All in all, unless you are running the same query multiple times then I wouldn't bother.
Update
One other thing to consider is coupling. Referencing a materialized view directly in JPA would allow you to update any logic without updating the application but the flip side of this is that logic is hidden outside the application which can make debugging a pain.
Also if you are just referencing a materialized view directly and not using any query rewrite or rollup features then am simple table created via CTAS would actually be better as you still have the precomputed data without the (small) overhead of maintaining the materialized view.
We have to create a materialised view in our database from a remote database which is currently in production. The view has about 5 crore records and is taking a long time. In between , the connection has snapped once and not even a single record persisted in our database. Since the remote database is production server, we get a very limited window to create the view.
My question is, can we have something like auto commit /auto start from where left at last time while the view is created so that we don't have to do the entire operation in one go ?
We are tying to make the query such that records can be fetched in smaller numbers as a alternate. But the data is read only for us and doesn't really have a where clause at this point which we can use.
Due to sensitive nature of data, I cannot post the view structure or the query.
No, you can not commit during the process of creating the view. But why don't you import the data to a table instead of a view? This would provide the possibility to commit in between. Furthermore this might provide the possibility, to load only the delta of changes maybe on daily basis - this would reduce the required time dramatically.
So I have a process to design where there are few base tables on which I have to create a view and from that view I will extract and derive data and insert into an another table.
we would use this last table for extracting reports
This process will run daily, since the data on the base tables have updates have everyday.
he whole purpose of this process is to make things "faster" for reporting,
So my concern here is with using the view. I am wondering if a materialized view would be better to use here in terms of performance instead the view or view itself would be the better.
Has anyone had to deal with such situation and found an approach that performs well and works efficiently??
Any leads on this would be highly appreciated
i have a crystal report that calls a function in Oracle. this function uses a select that selects a view as one of its' tables. this view uses multiple links to other databases(the view is a union of several queries). whenever this function runs, it appears as though the query for the view is run, and every link that creates the view seems to go into enq- DX contention.
is this related to this known issue?
http://surachartopun.com/2008/12/dbink-hangs-enq-dx-contention.html
the reason i ask is that my research seems to indicate that this problem should only happen when linking to different versiions of Oracle but all of the ones i am using are 10.2
Has this method ever worked? It does not sound like a good way to do things. I can just imagine the function causing an enormous amount of round trips as it processes each row.
Some other ways of doing this include putting the function as close to the biggest data table as possible and keeping the processing on that database. Only return what you need from the function.
You could create a table representing your desired data set from a query every morning and use Crystal to query that directly. Just refresh your data as required using stored procedures or advanced queues.
A materialized view on one of the database sources with a refresh would be another approach.
EDIT: yes, using database links can be resource intensive and cause the kind of problems you have seen. Has this ever worked or is there a new requirement you need a solution to.
If it used to work what changed?
If this is new I humbly suggest a different approach as I have suggested.
What is the best way in terms of speed of the platform and maintainability to access data (read only) on Dynamics CRM 4? I've done all three, but interested in the opinions of the crowd.
Via the API
Via the webservices directly
Via DB calls to the views
...and why?
My thoughts normally center around DB calls to the views but I know there are purists out there.
Given both requirements I'd say you want to call the views. Properly crafted SQL queries will fly.
Going through the API is required if you plan to modify data, but it isnt the fastest approach around because it doesnt allow deep loading of entities. For instance if you want to look at customers and their orders you'll have to load both up individually and then join them manually. Where as a SQL query will already have the data joined.
Nevermind that the TDS stream is a lot more effecient that the SOAP messages being used by the API & webservices.
UPDATE
I should point out in regard to the views and CRM database in general: CRM does not optimize the indexes on the tables or views for custom entities (how could it?). So if you have a truckload entity that you lookup by destination all the time you'll need to add an index for that property. Depending upon your application it could make a huge difference in performance.
I'll add to jake's comment by saying that querying against the tables directly instead of the views (*base & *extensionbase) will be even faster.
In order of speed it'd be:
direct table query
view query
filterd view query
api call
Direct table updates:
I disagree with Jake that all updates must go through the API. The correct statement is that going through the API is the only supported way to do updates. There are in fact several instances where directly modifying the tables is the most reasonable option:
One time imports of large volumes of data while the system is not in operation.
Modification of specific fields across large volumes of data.
I agree that this sort of direct modification should only be a last resort when the performance of the API is unacceptable. However, if you want to modify a boolean field on thousands of records, doing a direct SQL update to the table is a great option.
Relative Speed
I agree with XVargas as far as relative speed.
Unfiltered Views vs Tables: I have not found the performance advantage to be worth the hassle of manually joining the base and extension tables.
Unfiltered views vs Filtered views: I recently was working with a complicated query which took about 15 minutes to run using the filtered views. After switching to the unfiltered views this query ran in about 10 seconds. Looking at the respective query plans, the raw query had 8 operations while the query against the filtered views had over 80 operations.
Unfiltered Views vs API: I have never compared querying through the API against querying views, but I have compared the cost of writing data through the API vs inserting directly through SQL. Importing millions of records through the API can take several days, while the same operation using insert statements might take several minutes. I assume the difference isn't as great during reads but it is probably still large.