Hi I have this silly question, but I want to be sure. I have created a database based on sqlite3. I trigger the commit() after 1000k operations so I will not have too much disk I/O. When I seek data on the database, will the select query search only in the database file or will it check the uncommited data too ?
Thanks.
Transactions allow isolation and atomicty regarding other users of the database.
Any changes you make are visible in your own connection immediately.
If you are using the same SQLite connection for reading as you are for writing the database, then the effects of the writing will be visible to the reader, as expected.
If you are using different connections -- even within a single thread -- for reading and writing, the reader will not see uncommitted writes to the database unless you go to rather significant lengths to allow it to do so.
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I am using hibernate-PostgreSQL in my application and I am using application-managed entity manager to perform database operations.
I have a very basic question regarding whether it is required/recommended to start a transaction for reading records from database?
If yes, won’t it make extra work to manage the transaction? We need to make sure rollback is done after reading, if not it will cause connection leak. Make sure transaction is not kept open for long as it can cause unnecessary resource usage and so on.
Hibernate document says "Always use clear transaction boundaries, even for read-only operations.". What would be the advantage of starting transaction if I just want to read some records from database?
Is it only for batching multiple read operations using single transaction?
I am designing a solution for a SQL Server 2012 database for the following scenario
The database contains about 1M records with some simple parent child relationships between 4 or 5 tables
There is a 24x7 high load of reads on the database
Once a day we receive a batch with about 1000 inserts, updates and deletes that should be merged into the database, occasionally this number could be higher.
Apart from the daily batch there are no other writers to the database
There are a few 'special' requirements
Readers should not experience any significant latency due to these updates
The entire batch should be processed atomically from the readers perspective. The reader should not see a partially processed batch
If the update fails halfway we need to rollback all changes of the batch
Processing of the batch itself is not time-critical, with a simple implementation it now takes up to a few minutes which is just fine.
The options I am thinking of are
Wrap a single database transaction around the entire update batch (this could be a large transaction), and using snapshot isolation to allow readers to read the original data while the update is running.
Use partition switching, It seems like this feature was designed with this kind of usecase in mind. The downside seems to be that before we can start processing the batch we need to create a copy of all the original data.
Switch the entire database. We could create a copy of the entire database, process the batch in this copy and then redirect all clients to this database(e.g. by changing their connection string). This should even allow us to make the database read only and possibly even create multiple copies of the database for scalability.
Which of these options, or another, would best fit this scenario and why?
the transaction strat will block and cause latency.
partition switching is not really going to solve your solution as you should consider that the same as doing it against the database as you have it today... (so the rollback/insert) would still be blocking however it could be isolated to just part of your data not all...
Your best bet is to use 2 databases and switch connection strings...
OR use 1 database and have 2 sets of tables and use views or sprocs that are swapped to look at the "active" tables. You still could have disk contention issues but from a locking perspective you would be fine.
I am taking an operating systems class where we just learned about the 'readers and writers' problem: how do you deal with multiple processes that want to read and write from the same memory (at the same time)? I'm also dealing with a version of this problem at work: I am writing an application that requires multiple users to read and write to a shared SQL server database. Because the 'readers and writers' problem seems so well understood and discussed, I'm assuming that Microsoft has solved it for me. Meaning, that I don't need to worry about setting permissions or configuring SQL server to ensure that people are not reading and writing to a database at the same time. Specifically, can I assume that, with SQL server 2005, by default:
No process reads while another process is writing
No two processes write at the same time
A writer will take an exclusive X lock on at least the row(s) they are modifying and will hold this until their transaction commits. X locks are incompatible with other X locks so two writers can not concurrently modify the same row.
A reader will (at default read committed isolation level) take a shared lock and release this as soon as the data is read. This is incompatible with an X lock so readers must wait for writing transactions to finish before reading modified data. SQL Server also has snapshot isolation in which readers are not blocked by writers but instead read an earlier version of the row.
Classic SQL Servers like MS-SQL use a pessimistic approach and lock rows, tables or pages until a writing operation is done. You really don't have to cope with that, because -- as you said -- the creator already solved that problem. Have a look at this article for some first information, any database book will cover the problem in depth. If you are interested in this topic, I would suggest reading "Database Systems" by Connolly and Begg, for example.
I have studied a lot how durability is achieved in databases and if I understand well it works like this (simplified):
Clent's point of view:
start transaction.
insert into table values...
commit transaction
DB engine point of view:
write transaction start indicator to log file
write changes done by client to log file
write transaction commit indicator to log file
flush log file to HDD (this ensures durability of data)
return 'OK' to client
What I observed:
Client application is single thread application (one db connection). I'm able to perform 400 transactions/sec, while simple tests that writes something to file and then fsync this file to HDD performs only 150 syncs/sec. If client were multithread/multi connection I would imagine that DB engine groups transactions and does one fsync per few transactions, but this is not the case.
My question is if, for example MsSQL, really synchronizes log file (fsync, FlushFileBuffers, etc...) on every transaction commit, or is it some other kind of magic behind?
The short answer is that, for a transaction to be durable, the log file has to be written to stable storage before changes to the database are written to disk.
Stable storage is more complicated than you might think. Disks, for example, are not usually considered to be stable storage. (Not by people who write code for transactional database engines, anyway.)
It see how a particular open source dbms writes to stable storage, you'll need to read the source code. PostgreSQL source code is online. (File is xlog.c) Don't know about MySQL source.
Has open source ever created a single file database that has better performance when handling large sets of sql queries that aren't delivered in formal SQL transaction sets? I work with a .NET server that does some heavy replication of thousands of rows of data from another server and it does so it a 1-by-1 fashion without formal SQL transactions. So, therefore I cannot use SQLite or FirebirdDB or JavaDB because they all don't automatically batch the transactions and therefore the performance is dismal. Each insert waits for the success of the previous one, etc. So, I am forced to use a heavier database like SQLServer, MySQL, Postgres, or Oracle.
Does anyone know of a flat file database (that has a JDBC connect driver) that would support auto batching transactions and solve my problem?
The main think I dont like about the heavier databases is the lack of the ability to see inside the database with a one-mouse-click operation, like you can with SQLLite.
I tried creating a SQLite database and
then set PRAGMA read_uncommitted=TRUE;
and it didn't result in any
performance improvement.
I think that Firebird can work for this.
Firebird have good dotnet provider and many solution for replication
May be you can read this article for Firebird transaction
Try hypersonic DB - http://hsqldb.org/doc/guide/ch02.html#N104FC
If you want your transactions to be durable (i.e. survive a power failure) then the database will HAVE to write to the disc after each transaction (this is usually a log of some sort).
If your transactions are very small this will result in a huge number of writes, and very poor performance even on your battery backed raid controller or SSD, but worse performance on consumer-grade hardware.
The only way of avoiding this is to somehow disable the flush at txn commit (which of course breaks durability). I have no idea which ones support this, but it should be easy to find out.