I have a confusion in redis or memcached in which (stutivation or data) want to cache the database record.
Doing the accounting project it have more then 10k users, while application hit more means my database execution takes more time to response.
I used the index and query optimization in better.
Can anyone please help me to use the cache like a boss.
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I have a new idea and question about that I would like to ask you.
We have a CRM application on-premise / in house. We use that application kind of 24X7. We also do billing and payroll on the same CRM database which is OLTP and also same thing with SSRS reports.
It looks like whenever we do operation in front end which does inserts and updates to couple of entities at the same time, our application gets frozen until that process finishes. e.g. extracting payroll for 500 employees for their activities during last 2 weeks. Basically it summarize total working hours pulls that numbers from database and writes/updates that record where it says extract has been accomplished. so for 500 employees we are looking at around 40K-50K rows for Insert/Select/Update statements together.
Nobody can do anything while this process runs! We are considering the following options to take care of this issue.
Running this process in off-hours
OR make a copy of DB of Dyna. CRM and do this operations(extracting thousands of records and running multiple reports) on copy.
My questions are:
how to create first of all copy and where to create it (best practices)?
How to make it synchronize in real-time.
if we do select statement operation in copy DB than it's OK, but if we do any insert/update on copy how to reflect that on actual live db? , in short how to make sure both original and copy DB are synchronize to each other in real time.
I know I asked too many questions, but being SQL person, stepping into CRM team and providing suggestion, you know what I am trying to say.
Thanks folks for your any suggestion in advance.
Well to answer your question in regards to the live "copy" of a database a good solution is an alwayson availability group.
https://blogs.technet.microsoft.com/canitpro/2013/08/19/step-by-step-creating-a-sql-server-2012-alwayson-availability-group/
Though I dont think that is what you are going to want in this situation. Alwayson availability groups are typically for database instances that require very low failure time frames. For example: If the primary DB server goes down in the cluster it fails over to a secondary in a second or two at the most and the end users only notice a slight hiccup for a second.
What I think you would find better is to look at those insert statements that are hitting your database server and seeing why they are preventing you from pulling data. If they are truly locking the table maybe changing a large amount of your reads to "nolock" reads might help remedy your situation.
It would also be helpful to know what kind of resources you have allocated and also if you have proper indexing on the core tables for your DB. If you dont have proper indexing then a lot of the queries can take longer then normal causing the locking your seeing.
Finally I would recommend table partitioning if the tables you are pulling against are to large. This can help with a lot of disk speed issues potentially and also help optimize your querys if you partition by time segment (i.e. make a new partition every X months so when a query pulls from one time segment they only pull from that one data file).
https://msdn.microsoft.com/en-us/library/ms190787.aspx
I would say you need to focus on efficiency more then a "copy database" as your volumes arent very high to be needing anything like that from the sounds of it. I currently have a sql server transaction database running with 10 million+ inserts on it a day and I still have live reports hit against it. You just need the resources and proper indexing to accommodate.
currently as a single user, it takes the 260ms for a certain query to run from start to finish.
what will happen if I have 1000 queries sent at the same time? should I expect the same query to take ~4 minutes? (260ms*1000)
It is not possible to make predictions without any knowledge of the situation. There will be a number of factors which affect this time:
Resources available to the server (if it is able to hold data in memory, things run quicker than if disk is being accessed)
What is involved in the query (e.g. a repeated query will usually execute quicker the second time around, assuming the underlying data has not changed)
What other bottlenecks are in the system (e.g. if the webserver and database server are on the same system, the two processes will be fighting for available resource under heavy load)
The only way to properly answer this question is to perform load testing on your application.
What is the best way to paginate a FTS Query ? LIMIT and OFFSET spring to mind. However, I am concerned that by using limit and offset I'd be running the same query over and over (i.e., once for page 1, another time for page 2.... etc).
Will PostgreSQL be smart enough to transparently cache the query result ? Thus subsequently satisfying the pagination queries from a cache ? If not, how do I paginate efficiently ?
edit
The database is for single user desktop analytics. But, I still want to know what the best way is, if this were a live OLTP application. I have addressed the problem in the past with SQL Server by creating a ordered set of document id's and cache the query parameters against the IDs in a seperate table. Clearing the cache every few hours (so as to allow new documents to enter the result set).
Perhaps this approach is viable for postgres. But still I wanna know the mechanics present in the database and how best to leverage them. If I were a DB developer I'd enable the query-response cache to work with the FTS system.
A server-side SQL cursor can be effectively used for this if a client session can be tied to a specific db connection that stays open during the entire session. This is because cursors cannot be shared between different connections. But if it's a desktop app with a unique connection per running instance, that's fine.
The doc for DECLARE CURSOR explains how the resultset is going to be materialized when the cursor is declared WITH HOLD in a committed transaction.
Locking shouldn't be a concern at all. Should the data be modified while the cursor is already materialized, it wouldn't affect the reader nor block the writer.
Other than that, there is no implicit query cache in PostgreSQL. The LIMIT/OFFSET technique implies a new execution of the query for each page, which may be as slow as the initial query depending on the complexity of the execution plan and the effectiveness of the buffer cache and disk cache.
Well, to be honest, what you may want is for your query to return a live Cursor, that you can then reuse to fetch certain portions of the results that it (the Cursor) represents. Now, I don't know if PostGre supports this, Mongo DB does, and I've tried going down that road but it's not cool. For example: do you know how much time it will pass between when a query is done and a second page of results from that query are demanded? Can the cursor stay on for that amount if time? And if it can, what does it mean exactly, will it block resources, such that if you have many lazy users, who start queries but take a long time to navigate through pages, your server might be bogged down by locked cursors?
Honestly, I think redoing a paginated query each time someone asks for a certain page is ok. First of all, you'll be returning a small number of entries (no need to display more than 10-20 entries at a time) and that's gonna be pretty fast, and second, you should more likely tune up your server so that it executes frequent request fast (add indexes, put it behind a Solr server if necessary, etc.) rather than have those queries run slow, but caching them.
Finally, if you really want to speed up full text searches, and have fancy indexes like case insensitive, prefix and suffix enabled, etc, you should take a look at Lucene or better yet Solr (which is Lucene on steroids) as an in-between search and indexing solution between your users and your persistence tier.
I am doing some performance work in my unit tests and wondering if it was possible to get access to statistics for my RavenDb session (similar to NHibernate session statistics)?
I want to know things like total query count and number of trips to the server.
Berko,
Yes, you can.
Look at the session.Advanced property, you have a number of things there. The most important one of them is probably the NumberOfRequests that this session made.
Raven DB Profiler can give you some of the information you need.... Here
http://ayende.com/blog/38913/ravendb-mvc-profiler-support
is there a way to force mysql to cache a particular query, for say 5 minutes, so executing that query will always return the same result even if the underlying db changes ?
i'm running a dating site and i have a page that shows "newest matches" and it's hitting the db too much.
thanks in advance.
Caching in MySQL is not a good solution to this problem.
MySQL automatically caches a query until the table is updated.
For your problem, you need to use a cache in front of the database. You can then check the cache first, and if what you are looking for is not in the cache hit the database and add it to the cache.
Memcached is a good solution for this, especially if you have more than 1 web server.
APC is another good solution that can also cache your PHP bytecode, but it is a local cache on a single machine only.