Python --> SQLite --> ASP.NET C#
I am looking for an in memory database application that does not have to write the data it receives to disc. Basically, I'll be having a Python server which receives gaming UDP data and translates the data and stores it in the memory database engine.
I want to stay away from writing to disc as it takes too long. The data is not important, if something goes wrong, it simply flushes and fills up with the next wave of data sent by players.
Next, another ASP.NET server must be able to connect to this in memory database via TCP/IP at regular intervals, say once every second, or 10 seconds. It has to pull this data, and this will in turn update on a website that displays "live" game data.
I'm looking at SQlite, and wondering, is this the right tool for the job, anyone have any suggestions?
Thanks!!!
This sounds like a premature optimization (apologizes if you've already done the profiling). What I would suggest is go ahead and write the system in the simplest, cleanest way, but put a bit of abstraction around the database bits so they can easily by swapped out. Then profile it and find your bottleneck.
If it turns out it is the database, optimize the database in the usual way (indexes, query optimizations, etc...). If its still too slow, most databases support an in-memory table format. Or you can mount a RAM disk and mount individual tables or the whole database on it.
Totally not my field, but I think Redis is along these lines.
The application of SQlite depends on your data complexity.
If you need to perform complex queries on relational data, then it might be a viable option. If your data is flat (i.e. not relational) and processed as a whole, then some python-internal data structures might be applicable.
Perhaps AppFabric would work for you?
http://msdn.microsoft.com/en-us/windowsserver/ee695849.aspx
SQLite doesn't allow remote "connections" as far as I know, it only supports being invoked as an in-process library. However, you could try to use MySQL which, while heavier, supports remote connections and does have in-memory tables.
See http://dev.mysql.com/doc/refman/5.5/en/memory-storage-engine.html
Related
I am working on an application at the moment that is using as a caching strategy the reading and writing of data to text files in a read/write directory within the application.
My gut reaction is that this is sooooo wrong.
I am of the opinion that these values should be stored in the ASP.NET Cache or another dedicated in-memory cache such as Redis or something similar.
Can you provide any data to back up my belief that writing to and reading from text files as a form of cache on the webserver is the wrong thing to do? Or provide any data to prove me wrong and show that this is the correct thing to do?
What other options would you provide to implement this caching?
EDIT:
In one example, a complex search is performed based on a keyword. The result from this search is a list of Guids. This is then turned into a concatenated, comma-delimited string, usually less than 100,000 characters. This is then written to a file using that keyword as its name so that other requests using this keyword will not need to perform the complex search. There is an expiry - I think three days or something, but I don't think it needs to (or should) be that long
I would normally use the ASP.NET Server Cache to store this data.
I can think of four reasons:
Web servers are likely to have many concurrent requests. While you can write logic that manages file locking (mutexes, volatile objects), implementing that is a pain and requires abstraction (an interface) if you plan to be able to refactor it in the future--which you will want to do, because eventually the demand on the filesystem resource will be heavier than what can be addressed in a multithreaded context.
Speaking of which, unless you implement paging, you will be reading and writing the entire file every time you access it. That's slow. Even paging is slow compared to an in-memory operation. Compare what you think you can get out of the disks you're using with the Redis benchmarks from New Relic. Feel free to perform your own calculation based on the estimated size of the file and the number of threads waiting to write to it. You will never match an in-memory cache.
Moreover, as previously mentioned, asynchronous filesystem operations have to be managed while waiting for synchronous I/O operations to complete. Meanwhile, you will not have data consistent with the operations the web application executes unless you make the application wait. The only way I know of to fix that problem is to write to and read from a managed system that's fast enough to keep up with the requests coming in, so that the state of your cache will almost always reflect the latest changes.
Finally, since you are talking about a text file, and not a database, you will either be determining your own object notation for key-value pairs, or using some prefabricated format such as JSON or XML. Either way, it only takes one failed operation or one improperly formatted addition to render the entire text file unreadable. Then you either have the option of restoring from backup (assuming you implement version control...) and losing a ton of data, or throwing away the data and starting over. If the data isn't important to you anyway, then there's no reason to use the disk. If the point of keeping things on disk is to keep them around for posterity, you should be using a database. If having a relational database is less important than speed, you can use a NoSQL context such as MongoDB.
In short, by using the filesystem and text, you have to reinvent the wheel more times than anyone who isn't a complete masochist would enjoy.
I would like to get your opinion regarding a design implementation for data sharing.
I am working on Linux embedded device (mips 200 Mhz) and I want to have some sort of data sharing between multiple processes which can either read or write multiple parameters at once.
This data holds ~200 string parameters which are updated every second.
Process may access to data around ~10 times in 1 second.
I would very much like to try and make the design efficient (CPU / Mem).
This data is not required to be persistent and will be recreated every reboot.
Currently, I am considering two options:
Using shard memory IPC (SHM) + semaphore (locking on all SHM).
To use SQLite memory based DB.
For either option, I will supply a C interface library which will perform all the logic of DB operation.
For SHM, this mean locking/unlocking the semaphore and access the parameters which can be referred as an indexed array.
For SQLite, my library will be a wrapper for the SQLite interface library, so the process will not have to know SQL syntax, (some parsing should be done for queries and reply).
I believe that shared memory is more efficient:
No need to use and parse SQL, and it is accessed as an array.
Saying that, there are some pros as well for using SQLite:
Already working and debugged (DB level).
Add flexibility.
Used widely in many embedded systems.
Getting to the point,
Performance wise, I have no experience with SQLite, I would appreciate if you can share your opinions and experience.
Thanks
SQLite's in-memory databases cannot be shared between processes, but you could put the DB file into tmpfs.
However, SQLite does not do any synchronization between processes. It does lock the DB file to prevent update conflicts, but if one process finds the file already locked, it just waits for a random amount of time.
For efficient communication between processes, you need to use a mechanism like SHM/semaphores or pipes.
When working with CRUD operation in flex, I want to know how to open only one time for all update and delete operations. How can I do this?
As Flextra's mentioned in his comment above, Flex doesn't access the database directly. You'll have to make a RemoteObject call to another layer that will perform the actual CRUD operations.
That being said, unless you want to perform all of your CRUD operations in one giant batch, I would not recommend keeping the database connection open just waiting for something to do. That's generally considered poor practice. I would recommend opening and closing the connection to your database as needed when performing each operation.
It depends on the server-side technology if you aren't talking about a local SQLite database.
PHP has the mysql_pconnect() for a persistent connection for example.
Background:
Enterprise application - very will written for its time in 2004.
Stack:
.NET, Heavy use of Remoting, ASMX style web services, SQL Server
Problem:
The application allows user to go through various wizards for lack of a better term, all of their actions are stored in what we call "wiz state", which is essentially XML that is persisted to a SQL server database very frequently because we allow users to pause/resume their application. Often in these wizards, the XML that comprises the wizard state grows very large, I'm talking 5-8 MB of data, and we noticed that when we had a sudden influx of simultaneous users, we started receiving occasional timeouts against the database, because a lot of what the wizard state is comprised of, is keeping track of collections of "things". Sometimes these custom collections grow very large.
Question:
We were in a meeting today and we're expecting a flurry of activity in October that will test the system like never before, and possibly result in huge wizard states that go back and forth from the web server to the database. The crux of the situation is that there is only one database and one web server.
For arguments sake, because of the complexity of the application, lets say adding any kind of clustering/mirroring to increase database throughput is out of the question. I spoke up in the meeting and said the quickest way to address this in the shortest time period would be to add more servers to the front end web application so the load could be distributed amongst web servers. The development lead said I was completely wrong and it would have no effect because we only have one database, so adding more web power would do nothing. He is having one of the other developers reduce the xml bloat that we persist frequently to the database. Probably in the long run, reducing the size of the xml that we pass back and forth is the right idea, but will adding additional web servers truly have no effect, I just think in terms of simultaneous users, it should help.
Any responses thoughts are appreciated, proof that more web servers would help would be pure win.
Thanks.
EDIT: We use binary serialization to store the XML in the database in an image field.
I haven't heard anything about locating the "bottlenecks". Isn't that the first thing to do? Here's the method I use.
Otherwise you're just investing in guesses. That won't work.
I've been in meetings like that, where everybody gets excited throwing ideas around, and "management" wants to make "decisions", but it's the blind leading the blind. Knuckle down and find out what's going on. You can't do that in meetings.
Some time ago I looked at a performance problem with some similarity to yours. The biggest "bottleneck" was in writing and parsing XML, with attendant memory allocation, setup, and destruction. Then there were others as well. You might find the same thing, or something different.
P.S. I keep quoting "bottleneck" because all the performance problems I've found have been nothing at all like the necks of bottles. Rather they are like way over-bushy call trees that need radical pruning, such as making and reading mountains of XML for no good reason.
If the rate at which the data is written by SQL is the bottleneck, feeding data to SQL more quickly should have no effect.
I am not sure exactly what the data structure is, but perhaps compressing the XML data on the web server(s) before writing may have a positive effect.
If the bottleneck is the database, then more web services will not help you a lot.
The problem may be that the problem is not only the size of the data, but the number of concurrent request to the same table. The number of writes will be the big problem. If your XML write is in a transaction with other queries you may try to break out the XML write from that transaction to reduce locking time of the XML table.
As stated by vdeych you may try compression to reduce the data size. (That would increase the load on the web servers.)
You may also try caching the data. Only read from the SQL server if the data is not already in the cache. Make sure you don't update the SQL server if your data has not changed.
No one seems to have suggest this, what about replacing your XML serialization of your wizard with JsonSerialization.
Not only should this give you a minor boost in performance in the serialization itself since both the DataContractSerializer (faster) and Newtonsoft Json.NET (fastest) out perform the XML serializers in .NET. This should easily reduce the size of your object graph by upwards of 50% or more (depending on number of properties vs large strings in the XML).
This should dramatically lower the IO that is inflicted upon Sql server. This should also limit the amount of scope required to alter your application significantly (assuming it's well designed and works through common calls for serialization/deserialization).
If you choose to go this route also invest time comparing BSON vs JSON as I think it would be likely that the binary encoded one will offer even more space savings (and further IO reduction) due to the size of your object graphs.
I'm not a .NET expert but maybe using a binary serialization would increase throughput. Making sure that the XML isn't stored as text (fairly obvious but thought I'd mention it). Also relational databases are best for storing relational data, so perhaps substituting an ORM layer in place of the serialization (sounds feasible) could speed things up.
Mike is spot on, without understanding the resource constaint leading to the performance issues, no amount of discussion will resolve the problem. I'll add that socket timeouts that affect running statements are a symptom, and are never imposed by SQL Server, they're an artifact of your driver configuration or a firewall or similar device between app and db imposing them (unless you're talking about timeouts for new connections, then you have a host in serious distress under load).
Given your symptom is database timeouts, you need to start there. If they're indicative of long running statements that result in a socket timeout, use SQL Server profiler to capture the workload while simultaneously monitoring system resources. Given it's a mature application and the type of workload you mention, it's unlikely to be statement tuning related, it probably boils down to resource limitations CPU, memory or disk IO capacity
This Technet guide is a very good place to start:
http://technet.microsoft.com/en-us/library/cc966540.aspx
If it's resource contention, then it's a simple discussion about how the resource contention can be tuned, configured for or addressed by adding more of whatever is needed.
Edit: I should add that given a database performance issue, more applications servers is likely to worsen the problem as you increase the amount of concurrency, that might otherwise be kept in check by connection pool, request processing or other limits.
I'm currently using the in-memory option for SQLite and while it works (a bit slow right now but I'm still exploring ways to optimize my usage of it like batching and such), I'm just curious whether there are other alternatives to SQLite that support in-memory DBs and are embedded solutions. I don't necessarily need a schema-based DB (NoSQL would be an interesting thing to try). I do writes more frequently than reads (this is part of a backend for a web application), so I need my updates to be fast enough to keep up with the incoming flow of data.
I believe SQLite is probably more than capable of handling the volume with some optimizations on the query-side, but I'm just wondering about the alternatives.
Have you tried Oracle's TimesTen database? (Wikipedia article available here)