SQL: Are dirty reads guaranteed to see very latest data? - sql

If I open a transaction in READ UNCOMMITTED Isolation level, am I guaranteed to see the latest data on every table/row? I.e. as soon as some other transaction updates a row, my tranaction will see that change? (this would be analogous to a write-through to main memory)
Could it even be that my SELECT will get a row containing part of an UPDATE, but not all of it? What would in this case be the smallest element that is atomically updated/read?
Are there differences in the various relational database systems?

No. "Dirty data" means that you are relying on the internals of the database, so there are no guarantees. Data could be written to the data page and then removed due to a transaction rollback. Data could be written to the data page -- and then a later step in the same transaction could overwrite it.
In addition, what you are asking for is not possible. Your query could be scanning an entire table. Your reads are occurring at the page level. Each page could be a different amalgamation of transactions, with no consistency.

Related

read-committed for rows whose keys are in a list (is the read atomic?)

I happen to be using innodb, read-committed.
My simple question is this relative to a transaction:
I have a table (TreeNodeId) which holds a set of 4 different nodekeys, that represent all extant nodes in my system that relate to available paths to webpages. Each key represents an item in the database, and each row in the table represents various combinations in which items are used.
At the beginning of a transaction, based on the items being changed, I make a single query for all rows in TreeNodeId that reflect some extant combination of my one or 2 items.
Will this single query be internally consistent, even if it fetches 10,000 rows? Is it possible for the db query set to get the first 100 rows, and then for some other simultaneous transaction to commit new or deleted rows that would cause the remaing results to be inconsistent?
Andy
If you isolation level is read 'committed' it will only return results that have been 'committed' by the transaction log. So if you start a query that is in isolation level 'committed' at that point in time the sql transaction log will only give you transactions that had posted to it's log as committed. If in the middle of the select someone posts records they will be seen as 'uncommitted' at that point in time till they end their operation and will be 'committed'. However even if you change the level to 'uncommitted' you should not get data as it is in mid stream, you should get what is available to the engine at the moment you began your operation according to the transaction logs.
Committed versus uncommitted will get records in the system at the moment of select that are there based on your select. So if I had say 3,000,000 records and 200,000 records inserting but they were committing one at a time and only 100,000 had committed and 100,000 were aware of operation in the logs but not committed yet.
Committed would give me 3,100,000 and Uncommitted would give 3,200,000. However there are schools of thought and I just got into a discussion yesterday with someone on this.... Uncommitted will give you the uncommitted results and are known as 'dirty reads' in that you are reading logs that are not set yet(you rebel). You are saying "Hey database I don't care what you got incoming that is finalized I WANT IT NOW." When you say committed you are saying: "Database I only want qualified data, if something is not finalized I don't want it."
Advantages with each:
Uncommitted you will not LOCK anything. You are basically saying to the system: "Don't lock anything out, just let me go through the system freely getting what is there and I don't care if you change something. I want it at moment of operation." If something is trying to insert or update when you perform this it WILL NOT LOCK IT.
Committed will not lock anything except that which is in process to commit till your operation has been completed. You are safe in knowing your data returned is finalized but your run the risk of BLOCKING transactions trying to insert or post. Your are essentially telling the database: "Wait for me to finish before continuing your commits on tables I am accessing. I need my data accurate so hands off till I am done". This will potentially lock data while it is performing the reads on a table you are gathering from. This is not that common as most selects are near instant but on huge systems that are transactional based on posting thousands of records a second it is a BIG CONCERN.
Honestly in my discussion I favored uncommitted and the other person favored committed. I argued it is far more acceptable to get dirty data than stop production inserts. They argued that phantom reads and other instances were worse. This is an opinion and SQL systems are designed around inserts and selects but seldom can you do both exceptionally fast without taking a little away from the other. My answer if you want accurate reporting is do nightly backups, SSIS packages, binary collections, or something similar in an isolation level such as snapshot or committed and put that data somewhere. Let that data have been set in a way that we know it is finalized and it is locked so it may not be changed later and report off of that. Don't report off of production data hot and make it a point to tell everyone to do that. That is bad practice in and of itself to tell people to report off of live data performing inserts and updates in real time.
Will it hurt if you are a small mom and pop store with only 5 or 10 people using the database, probably not. Will it hurt if you are little bigger and have 50 people accessing the same database but it is about 100 gigs and semi transactional in that you get trickle's of data during the day. Still probably not. Will it hurt if you have 200 people and multiple servers and databases and a main transactional database brain storing the composite of all the data. ABSOLUTELY, don't read from a main production database with intense operations if it's main purpose is to get data to store.
EDIT to further point from real world example:
That is why usually at the top of most operations where I am not using table variables (declare #Table table) I set this: "set transaction isolation level read uncommitted". Will I be using this intensely every time I query? LOL, I hope not. In fact Full disclosure it may NEVER EVER help me from this point on because I isolate my data a lot with temp tables for huge transaction reporting. But I will not be getting yelled at by others I have a long running transaction blocking their inserts. You will also see a lot of people do this: "select * from table (nolock)" I Generally give code like this to lesser query designers as it embeds the nolock hint with the query. If I tell everyone to do this they will make it policy.
You do not have to do this and in fact some people will maybe follow me and claim this is wrong and post their side. I do it MOSTLY FOR PRODUCTION PROTECTION and anyone that tells me that is wrong I would like to hear why they like to lock tables and report off of them in production versus getting their data in or updated in real time first. I would have a hard time going to a manager and saying: "You know that huge account you were waiting to post 2 million records on and know the instance it was done. Well John down the hall really wanted to run this query that takes an hour to run because it was sloppily designed. He chose to use committed and is hitting some of the tables doing inserts so we are getting occasional locks. Well I think it is more important he get his report than we get business." I wonder what the manager would tell me back?

standard protocol on inserting data and querying data at the same time

every day we have an SSIS package running to import data into a database.
sometimes people are querying the database at the same time.
the loading (data import) times out because there's a table lock on the specific table.
what is the standard protocol on inserting data and querying data at the same time?
First you need to figure out where those locks are coming from. Use the link to see if there are any locks.
How to: Determine Which Queries Are Holding Locks
If you have another process that holds a table lock then not much you can do.
Are you sure the error is "not able to OBTAIN a table lock". If so look at changing your SSIS package to not use table locks.
There are several strategies.
One approach is to design your ETL pipeline as to minimize lock time. All the data is prepared in staging tables and then, when complete, is switched in using fast partition switch operations, see Transferring Data Efficiently by Using Partition Switching. This way the ETL blocks reads onyl for a very short duration. It also has the advantage that the reads see all the ETL data at once, not intermediate stages. The drawback is difficult implementation.
Another approach is to enable snapshot isolation and/or read committed snapshot in the database, see Row Versioning-based Isolation Levels in the Database Engine. This way reads no longer block behind the locks held by the ETL. the drawback is resource consumption, the hardware must be able to drive the additional load of row versioning.
Yet another approach is to move the data querying to a read-only standby server, eg. using log shipping.

Locking the database

Hi I'm trying to see what's locking the database and found 2 types of locking. Optimistic and Pessimistic Locking. I found some articles on Wiki but I would like to know more ! Can someone explain me about those locking ? We should only use locking when we need exclusive access to something? Locking only happens when we use transaction?
Thanks in advance.
Kevin
Optimistic locking is no locking at all.
It works by noting the state the system was in before you started making your changes, and then going ahead and just making those changes, assuming (optimistically) that no one else will want to make conflicting updates. Just as you are about to atomically commit those changes, you would check if in the mean-time someone else has also updated the same data. In which case, your commit fails.
Subversion for example using optimistic locking. When you try to commit, you have to handle any conflicts, but before that, you can do on your working copy whatever you want.
Pessimistic locks work with real locks. Assuming that there will be contention, you lock everything you want to update before touching it. Everyone else will have to wait for you to commit or rollback.
When using a relational database with transaction support, the database usually takes care of locking internally (such as when you issue an UPDATE statement), so for normal online processing you do not need to handle this yourself. Only if you want to do maintenance work or large batches do you sometimes want to lock down tables.
We should only use locking when we need exclusive access to something?
You need it to prevent conflicting operations from other sessions. In general, this means updates. Reading data can normally go on concurrently.
Locking only happens when we use transaction?
Yes. You will accumulate locks while proceeding with your transaction, releasing all of them at the end of it. Note that a single SQL command in auto-commit mode is still a transaction by itself.
Transactions isolation levels also specify the locking behaviour. BOL refers:Transaction isolation levels control:
Whether locks are taken when data is read, and what type of locks are requested.
How long the read locks are held.
Whether a read operation referencing rows modified by another transaction:
Blocks until the exclusive lock on the row is freed.
Retrieves the committed version of the row that existed at the time the statement or transaction started.
Reads the uncommitted data modification.
The default levels are:
Read uncommitted (the lowest level where transactions are isolated only enough to ensure that physically corrupt data is not read)
Read committed (Database Engine default level)
Repeatable read
Serializable (the highest level, where transactions are completely isolated from one another)

Serializable isolation level atomicity

I have several threads executing some SQL select queries with serializable isolation level. I am not sure which implementation to choose. This:
_repository.Select(...)
or this
lock (_lockObject)
{
_repository.Select(...);
}
In other words, is it possible several transactions will start executing at the same time and partially block records inside Select operation range.
P. S. I am using MySQL but I guess it is a more general question.
Transactions performing SELECT queries place a shared lock on the rows, permitting other transactions to read those rows, but preventing them from making changes to the rows (including inserting new records into the gaps)
Locking in the application is doing something else, it will not allow other threads to enter the code block which fetches the data from the repository, This approach can lead to very bad performance for a few reasons:
If any of the rows are locked by another transaction (outside the application) via a exclusive lock, the lock in the application will not help.
Multiple transactions will not be able to perform reads even on rows that are not locked in exclusive mode (not being updated).
The lock will not be released until all the data is fetched and returned to the client. This includes the network latency and any other overhead that it takes converting the MySql result set to a code object.
Most importantly, Enforcing data integrity & atomicity is the databases job, it knows how to handle it very well, how to detect potential deadlocks. When to perform record locks, and when to add Index gap locks. It is what databases are for, and MySql is ACID complaint and is proven to handle these situations
I suggest you read through Section 13.2.8. The InnoDB Transaction Model and Locking of the MySql docs, it will give you a great insight how locking in InnoDB is performed.

SQL Server - Dirty Reads Pros & Cons

Why should I or shouldn't I use dirty reads:
set transaction isolation level read uncommitted
in SQL Server?
From MSDN:
When this option is set, it is possible to read uncommitted or dirty data; values in the data can be changed and rows can appear or disappear in the data set before the end of the transaction.
Simply put, when you are using this isolation level, and you are performing multiple queries on an active table as part of one transaction, there is no guarantee that the information returned to you within different parts of the transaction will remain the same. You could query the same data twice within one transaction and get different results (this might happen in the case where a different user was updating the same data in the midst of your transaction). This can obviously have severe ramifications for parts of your application that rely on data integrity.
Generally when you need to do a sizeable (or frequent) queries to busy tables, where read committed would possibly be blocked by locks from uncommited transactions, but ONLY when you can live with inaccurate data.
As an example, on a gaming web site I worked on recently there was a summary display of some stats about recent games, this was all based on dirty reads, it was more important for us to include then exclude the transactional data not yet committed (we knew anyway that few, if any, transactions would be backed out), we felt that on average the data would be more accurate that way.
use it if you want the data back right away and it is not that important if it is right
do not use if if the data is important to be correct or if you are doing updates with it
Also take a look at snapshot isolation which has been introduced in sql server 2005
The Thing is when you want to read the data before committing, we can do with the help of set transaction isolation level read uncommitted, the data may, or may not change.
We can read the data by using the query:
Select * from table_name with(nolock)
This is applicable to only read uncommitted isolation level.