I'm using selectbox for your to choose multiple username. The username are retrieved from database and i use select username from users. Data are loaded all when the page rendered.
For now it worked because doesn't have many users, I assume that the table has 1 millions records then loading all of the table will take plenty of time. If i send request for query when user starts typing, it will not fast enough to retrieve data.
So how to solve this?
You'll need to ensure a minimum of 3-4 characters are supplied to the backend query (delay the query until 3-4 chars are entered), then perform a 'starts with' lookup on an INDEXED column in your database.
This should restrict the data searched/returned. Ensure the query is indexed!
Use pagination technique. Run the query to retrieve 100 records. Then if still scrolling, can retrieve more. Must be possible.
Related
I have an angular 4 UI, web API and SQL server in the back-end. I use a third party grid from ag grid (https://www.ag-grid.com/).
Here are some info about my scenario :
I have total 1 million records in SQL server
I need to group the data based on user selection from the UI. Typically, after the grouping, the number of records to fetch from DB becomes something around 200 thousands.
3.User will do some filtering from the UI as well which makes the number of records to fetch will become something around 4000 to 5000.
I implemented paging (page size 100) at server side. I send offset and number of records to fetch from DB . The problem in this case is, since it is a huge data , my grouping at the database takes 15 seconds to finish which is quite a lot of time.
Another approach I tried is, get the paged data from DB without grouping and do the grouping in the API which is kind of finishing in milliseconds. The problem here is, I am showing some values in the UI based on groups such as count and sum of the some fields , the data shown in the currently fetched data might not be correct/complete as the the current group may span to the other pages in the DB which are not fetched yet.
Any recommendations to deal with this kind of scenario would be appreciated.
Thanks.
We want to know what rows in a certain table is used frequently, and which are never used. We could add an extra column for this, but then we'd get an UPDATE for every SELECT, which sounds expensive? (The table contains 80k+ rows, some of which are used very often.)
Is there a better and perhaps faster way to do this? We're using some old version of Microsoft's SQL Server.
This kind of logging/tracking is the classical application server's task. If you want to realize your own architecture (there tracking architecture) do it on your own layer.
And in any case you will need application server there. You are not going to update tracking field it in the same transaction with select, isn't it? what about rollbacks? so you have some manager who first run select than write track information. And what is the point to save tracking information together with entity info sending it back to DB? Save it into application server file.
You could either update the column in the table as you suggested, but if it was me I'd log the event to another table, i.e. id of the record, datetime, userid (maybe ip address etc, browser version etc), just about anything else I could capture and that was even possibly relevant. (For example, 6 months from now your manager decides not only does s/he want to know which records were used the most, s/he wants to know which users are using the most records, or what time of day that usage pattern is etc).
This type of information can be useful for things you've never even thought of down the road, and if it starts to grow large you can always roll-up and prune the table to a smaller one if performance becomes an issue. When possible, I log everything I can. You may never use some of this information, but you'll never wish you didn't have it available down the road and will be impossible to re-create historically.
In terms of making sure the application doesn't slow down, you may want to 'select' the data from within a stored procedure, that also issues the logging command, so that the client is not doing two roundtrips (one for the select, one for the update/insert).
Alternatively, if this is a web application, you could use an async ajax call to issue the logging action which wouldn't slow down the users experience at all.
Adding new column to track SELECT is not a practice, because it may affect database performance, and the database performance is one of major critical issue as per Database Server Administration.
So here you can use one very good feature of database called Auditing, this is very easy and put less stress on Database.
Find more info: Here or From Here
Or Search for Database Auditing For Select Statement
Use another table as a key/value pair with two columns(e.g. id_selected, times) for storing the ids of the records you select in your standard table, and increment the times value by 1 every time the records are selected.
To do this you'd have to do a mass insert/update of the selected ids from your select query in the counting table. E.g. as a quick example:
SELECT id, stuff1, stuff2 FROM myTable WHERE stuff1='somevalue';
INSERT INTO countTable(id_selected, times)
SELECT id, 1 FROM myTable mt WHERE mt.stuff1='somevalue' # or just build a list of ids as values from your last result
ON DUPLICATE KEY
UPDATE times=times+1
The ON DUPLICATE KEY is right from the top of my head in MySQL. For conditionally inserting or updating in MSSQL you would need to use MERGE instead
I'm new to pagination, so I'm not sure I fully understand how it works. But here's what I want to do.
Basically, I'm creating a search engine of sorts that generates results from a database (MySQL). These results are merged together algorithmically, and then returned to the user.
My question is this: When the results are merged on the backend, do I need to create a temporary view with the results that is then used by the PHP pagination? Or do I create a table? I don't want a bunch of views and/or tables floating around for each and every query. Also, if I do use temporary tables, when are they destroyed? What if the user hits the "Back" button on his/her browser?
I hope this makes sense. Please ask for clarification if you don't understand. I've provided a little bit more information below.
MORE EXPLANATION: The database contains English words and phrases, each of which is mapped to a concept (Example: "apple" is 0.67 semantically-related to the concept of "cooking"). The user can enter in a bunch of keywords, and find the closest matching concept to each of those keywords. So I am mathematically combining the raw relational scores to find a ranked list of the most semantically-related concepts for the set of words the user enters. So it's not as simple as building a SQL query like "SELECT * FROM words WHERE blah blah..."
It depends on your database engine (i.e. what kind of SQL), but nearly each SQL flavor has support for paginating a query.
For example, MySQL has LIMIT and MS SQL has ROW_NUMBER.
So you build your SQL as usual, and then you just add the database engine-specific pagination stuff and the server automatically returns only, say, row 10 to 20 of the query result.
EDIT:
So the final query (which selects the data that is returned to the user) selects data from some tables (temporary or not), as I expected.
It's a SELECT query, which you can page with LIMIT in MySQL.
Your description sounds to me as if the actual calculation is way more resource-hogging than the final query which returns the results to the user.
So I would do the following:
get the individual results tables for the entered words, and save them in a table in a way that you can get the data for this specifiy query later (for example, with an additional column like SessionID or QueryID). No pagination here.
query these result tables again for the final query that is returned to the user.
Here you can do paging by using LIMIT.
So you have to do the actual calculation (the resource-hogging queries) only once when the user "starts" the query. Then you can return paginated results to the user by just selecting from the already populated results table.
EDIT 2:
I just saw that you accepted my answer, but still, here's more detail about my usage of "temporary" tables.
Of course this is only one possible way to do it. If the expected result is not too large, returning the whole resultset to the client, keeping it in memory and doing the paging client side (as you suggested) is possible as well.
But if we are talking about real huge amounts of data of which the user will only view a few (think Google search results), and/or low bandwidth, then you only want to transfer as little data as possible to the client.
That's what I was thinking about when I wrote this answer.
So: I don't mean a "real" temporary table, I'm talking about a "normal" table used for saving temporary data.
I'm way more proficient in MS SQL than in MySQL, so I don't know much about temp tables in MySQL.
I can tell you how I would do it in MS SQL, but maybe there's a better way to do this in MySQL that I don't know.
When I'd have to page a resource-intensive query, I want do the actual calculation once, save it in a table and then query that table several times from the client (to avoid doing the calculation again for each page).
The problem is: in MS SQL, a temp table only exists in the scope of the query where it is created.
So I can't use a temp table for that because it would be gone when I want to query it the second time.
So I use "real" tables for things like that.
I'm not sure whether I understood your algorithm example correct, so I'll simplify the example a bit. I hope that I can make my point clear anyway:
This is the table (this is probably not valid MySQL, it's just to show the concept):
create table AlgorithmTempTable
(
QueryID guid,
Rank float,
Value float
)
As I said before - it's not literally a "temporary" table, it's actually a real permanent table that is just used for temporary data.
Now the user opens your application, enters his search words and presses the "Search" button.
Then you start your resource-heavy algorithm to calculate the result once, and store it in the table:
insert into AlgorithmTempTable (QueryID, Rank, Value)
select '12345678-9012-3456789', foo, bar
from Whatever
insert into AlgorithmTempTable (QueryID, Rank, Value)
select '12345678-9012-3456789', foo2, bar2
from SomewhereElse
The Guid must be known to the client. Maybe you can use the client's SessionID for that (if he has one and if he can't start more than one query at once...or you generate a new Guid on the client each time the user presses the "Search" button, or whatever).
Now all the calculation is done, and the ranked list of results is saved in the table.
Now you can query the table, filtering by the QueryID:
select Rank, Value
from AlgorithmTempTable
where QueryID = '12345678-9012-3456789'
order by Rank
limit 0, 10
Because of the QueryID, multiple users can do this at the same time without interfering each other's query. If you create a new QueryID for each search, the same user can even run multiple queries at once.
Now there's only one thing left to do: delete the temporary data when it's not needed anymore (only the data! The table is never dropped).
So, if the user closes the query screen:
delete
from AlgorithmTempTable
where QueryID = '12345678-9012-3456789'
This is not ideal in some cases, though. If the application crashes, the data stays in the table forever.
There are several better ways. Which one is the best for you depends on your application. Some possibilities:
You can add a datetime column with the current time as default value, and then run a nightly (or weekly) job that deletes everything older than X
Same as above, but instead of a weekly job you can delete everything older than X every time someone starts a new query
If you have a session per user, you can save the SessionID in an additional column in the table. When the user logs out or the session expires, you can delete everything with that SessionID in the table
Paging results can be very tricky. They way I have done this is as follows. Set an upperbound limit for any query that may be run. For example say 5,000. If a query returns more than 5,000 then limit the results to 5,000.
This is best done using a stored procedure.
Store the results of the query into a temp table.
Select Page X's amount of data from the temp table.
Also return back the current page and total number of pages.
I have an interesting issue happening in Microsoft SQL when searching a TEXT field. I have a table with two fields, Id (int) and Memo (text), populated with hundreds of thousands of rows of data. Now, imagine a query, such as:
SELECT Id FROM Table WHERE Id=1234
Pretty simple. Let's assume there is a field with Id 1234, so it returns one row.
Now, let's add one more condition to the WHERE clause.
SELECT Id FROM Table WHERE Id=1234 AND Memo LIKE '%test%'
The query should pull one record, and then check to see if the word 'test' exists in the Memo field. However, if there is enough data, this statement will hang, as if it were searching the Memo field first, and then cross referencing the results with the Id field.
While this is what it is appearing to do, I just discovered that it is actually trying to create a statistic on the Memo field. If I turn off "auto create statistics", the query runs instantly.
So my quesiton is, how can you disable auto create statistics, but only for one query? Perhaps something like:
SET AUTO_CREATE_STATISTICS OFF
(I know, any normal person would just create a full text index on this field and call it a day. The reason I can't necessarily do this is because our data center is hosting an application for over 4,000 customers using the same database design. Not to mention, this problem happens on a variety of text fields in the database. So it would take tens of thousands of full text indexes if I went that route. Not to mention, adding a full text index would add storage requirements, backup changes, disaster recovery procedure changes, red tape paperwork, etc...)
I don't think you can turn this off on a per query basis.
Best you can do would be to identify all potentially problematic columns and then CREATE STATISTICS on them yourself with 0 ROWS or 0 PERCENT specified and NORECOMPUTE.
If you have a maintenance window you can run this in it would be best to run without this 0 ROWS qualifier but still leave the NORECOMPUTE in place.
You could also consider enabling AUTO_UPDATE_STATISTICS_ASYNC instead so that they are still rebuilt automatically but this happens in the background rather than holding up compilation of the current query but this is a database wide option.
I couldn't find a proper discussion thread on this topic, so I'm going to go ahead and ask here.
Problem: I have a select query that returns a result of size 100,000+. The user wants to view all this data, but obviously I can't give it to him all at once. I also don't want to store so much data on the client's memory. I want the user to be able to "page through" the results, being able to view the data in pages of 500 records.
So, how can I ask the database to only send me back 500 records at a time?
This depends on the database you are using, but in MySql you could try something like:
SELECT * FROM MyTable LIMIT <start>, 500
and replace <start> with the index you would like to start on (e.g. 0 for the first page, 501 for the second page).
You can use a combination of rownumber and top (atleast in SQL server)