If a schedule of transactions is not view-serialisable, can we conclude that the schedule is non-serialisable?
In other words, is it possible for a schedule to be serialisable and yet not view serialisable?
If possible, please give an example.
Related
I have two tables in DynamoDB. One has data about homes, one has data about businesses. The homes table has a list of the closest businesses to it, with walking times to each of them. That is, the homes table has a list of IDs which refer to items in the businesses table. Since businesses are constantly opening and closing, both these tables need to be updated frequently.
The problem I'm facing is that, when either one of the tables is updated, the other table will have incorrect data until it is updated itself. To make this clearer: let's say one business closes and another one opens. I could update the businesses table first to remove the old business and add the new one, but the homes table would then still refer to the now-removed business. Similarly, if I updated the homes table first to refer to the new business, the businesses table would not yet have this new business' data yet. Whichever table I update first, there will always be a period of time where the two tables are not in synch.
What's the best way to deal with this problem? One way I've considered is to do all the updates to a secondary database and then swap it with my primary database, but I'm wondering if there's a better way.
Thanks!
Dynamo only offers atomic operations on the item level, not transaction level, but you can have something similar to an atomic transaction by enforcing some rules in your application.
Let's say you need to run a transaction with two operations:
Delete Business(id=123) from the table.
Update Home(id=456) to remove association with Business(id=123) from the home.businesses array.
Here's what you can do to mimic a transaction:
Generate a timestamp for locking the items
Let's say our current timestamp is 1234567890. Using a timestamp will allow you to clean up failed transactions (I'll explain later).
Lock the two items
Update both Business-123 and Home-456 and set an attribute lock=1234567890.
Do not change any other attributes yet on this update operation!
Use a ConditionalExpression (check the Developer Guide and API) to verify that attribute_not_exists(lock) before updating. This way you're sure there's no other process using the same items.
Handle update lock responses
Check if both updates succeeded to Home and Business. If yes to both, it means you can proceed with the actual changes you need to make: delete the Business-123 and update the Home-456 removing the Business association.
For extra care, also use a ConditionExpression in both updates again, but now ensuring that lock == 1234567890. This way you're extra sure no other process overwrote your lock.
If both updates succeed again, you can consider the two items updated and consistent to be read by other processes. To do this, run a third update removing the lock attribute from both items.
When one of the operations fail, you may try again X times for example. If it fails all X times, make sure the process cleans up the other lock that succeeded previously.
Enforce the transaction lock throught your code
Always use a ConditionExpression in any part of your code that may update/delete Home and Business items. This is crucial for the solution to work.
When reading Home and Business items, you'll need to do this (this may not be necessary in all reads, you'll decide if you need to ensure consistency from start to finish while working with an item read from DB):
Retrieve the item you want to read
Generate a lock timestamp
Update the item with lock=timestamp using a ConditionExpression
If the update succeeds, continue using the item normally; if not, wait one or two seconds and try again;
When you're done, update the item removing the lock
Regularly clean up failed transactions
Every minute or so, run a background process to look for potentially failed transactions. If your processes take at max 60 seconds to finish and there's an item with lock value older than, say 5 minutes (remember lock value is the time the transaction started), it's safe to say that this transaction failed at some point and whatever process running it didn't properly clean up the locks.
This background job would ensure that no items keep locked for eternity.
Beware this implementation do not assure a real atomic and consistent transaction in the sense traditional ACID DBs do. If this is mission critical for you (e.g. you're dealing with financial transactions), do not attempt to implement this. Since you said you're ok if atomicity is broken on rare failure occasions, you may live with it happily. ;)
Hope this helps!
My program has users and groups.
Use-case: Users have credits they can give to the groups.
I want no credits to be lost.
The problem with RDBMS-like schema is the atomicity of Mongo is document-level. I reduce the credits of the user and then increase the credits of the group. If the application crashes between the two the credits, that are sent, become lost. (If I replace the two actions credits can appear without being withdrawn from the user.)
One solution could be using of a collection called transactions. Then the credits of the user can be calculated from the send credits of the user subtracted from the credits of the user. The credits of the group can be calculated as the sum of the sent credits. The problem is if the database grows the sum will take a while.
Can you give me any acceptable, scalable and robust solution for this with NoSQL? (I know it is really easy in RDBMS)
Two phase commits in MongoDB
You can perform multi-document updates or multi-document transactions using a two phase commit approach.
Using two-phase commit ensures that data is consistent and, in case of an error, the state that preceded the transaction is recoverable. During the procedure, however, documents can represent pending data and states.
For more details about Two phase commits you can refer to the docs here
NOTE
Because only single-document operations are atomic with MongoDB, two-phase commits can only offer transaction-like semantics. It is possible for applications to return intermediate data at intermediate points during the two-phase commit or rollback.
I basically understand what Serial and Seralizable Schedules are but the question I want to answer is
Briefly explain the terms, Serializable Schedule, Serial Schedule and
Equivalent Schedule
What is the difference between a Serealizable Schedule and an Equivalent Schedule?
Anything to do with the order of Transactions? or the values writing in to them?
Serial Schedule
One process at a time
Does not interleave
Equivalent Schedule
When the effect of executing different schedules are the same
Serializable Schedule
A schedule that is equivalent to some Serial Values
I saw this sentence not only in one place:
"A transaction should be kept as short as possible to avoid concurrency issues and to enable maximum number of positive commits."
What does this really mean?
It puzzles me now because I want to use transactions for my app which in normal use will deal with inserting of hundreds of rows from many clients, concurrently.
For example, I have a service which exposes a method: AddObjects(List<Objects>) and of course these object contain other nested different objects.
I was thinking to start a transaction for each call from the client performing the appropriate actions (bunch of insert/update/delete for each object with their nested objects). EDIT1: I meant a transaction for entire "AddObjects" call in order to prevent undefined states/behaviour.
Am I going in the wrong direction? If yes, how would you do that and what are your recommendations?
EDIT2: Also, I understood that transactions are fast for bulk oeprations, but it contradicts somehow with the quoted sentence. What is the conclusion?
Thanks in advance!
A transaction has to cover a business specific unit of work. It has nothing to do with generic 'objects', it must always be expressed in domain specific terms: 'debit of account X and credit of account Y must be in a transaction', 'subtract of inventory item and sale must be in a transaction' etc etc. Everything that must either succeed together or fail together must be in a transaction. If you are down an abstract path of 'adding objects to a list is a transaction' then yes, you are on a wrong path. The fact that all inserts/updates/deletes triggered by a an object save are in a transaction is not a purpose, but a side effect. The correct semantics should be 'update of object X and update of object Y must be in a transaction'. Even a degenerate case of a single 'object' being updated should still be regarded in terms of domain specific terms.
That recommendation is best understood as Do not allow user interaction in a transaction. If you need to ask the user during a transaction, roll back, ask and run again.
Other than that, do use transaction whenever you need to ensure atomicity.
It is not a transactions' problem that they may cause "concurrency issues", it is the fact that the database might need some more thought, a better set of indices or a more standardized data access order.
"A transaction should be kept as short as possible to avoid concurrency issues and to enable maximum number of positive commits."
The longer a transaction is kept open the more likely it will lock resources that are needed by other transactions. This blocking will cause other concurrent transactions to wait for the resources (or fail depending on the design).
Sql Server is usually setup in Auto Commit mode. This means that every sql statement is a distinct transaction. Many times you want to use a multi-statement transaction so you can commit or rollback multiple updates. The longer the updates take, the more likely other transactions will conflict.
What is the relationship between ACID and database transaction?
Does ACID give database transaction or is it the same thing?
Could someone enlighten this topic.
ACID is a set of properties that you would like to apply when modifying a database.
Atomicity
Consistency
Isolation
Durability
A transaction is a set of related changes which is used to achieve some of the ACID properties. Transactions are tools to achieve the ACID properties.
Atomicity means that you can guarantee that all of a transaction happens, or none of it does; you can do complex operations as one single unit, all or nothing, and a crash, power failure, error, or anything else won't allow you to be in a state in which only some of the related changes have happened.
Consistency means that you guarantee that your data will be consistent; none of the constraints you have on related data will ever be violated.
Isolation means that one transaction cannot read data from another transaction that is not yet completed. If two transactions are executing concurrently, each one will see the world as if they were executing sequentially, and if one needs to read data that is written by another, it will have to wait until the other is finished.
Durability means that once a transaction is complete, it is guaranteed that all of the changes have been recorded to a durable medium (such as a hard disk), and the fact that the transaction has been completed is likewise recorded.
So, transactions are a mechanism for guaranteeing these properties; they are a way of grouping related actions together such that as a whole, a group of operations can be atomic, produce consistent results, be isolated from other operations, and be durably recorded.
ACID are desirable properties of any transaction processing engine.
A DBMS is (if it is any good) a particular kind of transaction processing engine that exposes, usually to a very large extent but not quite entirely, those properties.
But other engines exist that can also expose those properties. The kind of software that used to be called "TP monitors" being a case in point (nowadays' equivalent mostly being web servers).
Such TP monitors can access resources other than a DBMS (e.g. a printer), and still guarantee ACID toward their users. As an example of what ACID might mean when a printer is involved in a transaction:
Atomicity: an entire document gets printed or nothing at all
Consistency: at end-of-transaction, the paper feed is positioned at top-of-page
Isolation: no two documents get mixed up while printing
Durability: the printer can guarantee that it was not "printing" with empty cartridges.
What is the relationship between ACID and database transaction?
In a relational database, every SQL statement must execute in the scope of a transaction.
Without defining the transaction boundaries explicitly, the database is going to use an implicit transaction which is wraps around every individual statement.
The implicit transaction begins before the statement is executed and end (commit or rollback) after the statement is executed.
The implicit transaction mode is commonly known as auto-commit.
A transaction is a collection of read/write operations succeeding only if all contained operations succeed.
Inherently a transaction is characterized by four properties (commonly referred as ACID):
Atomicity
Consistency
Isolation
Durability
Does ACID give database transaction or is it the same thing?
For a relational database system, this is true because the SQL Standard specifies that a transaction should provide the ACID guarantees:
Atomicity
Atomicity takes individual operations and turns them into an all-or-nothing unit of work, succeeding if and only if all contained operations succeed.
A transaction might encapsulate a state change (unless it is a read-only one). A transaction must always leave the system in a consistent state, no matter how many concurrent transactions are interleaved at any given time.
Consistency
Consistency means that constraints are enforced for every committed transaction. That implies that all Keys, Data types, Checks and Trigger are successful and no constraint violation is triggered.
Isolation
Transactions require concurrency control mechanisms, and they guarantee correctness even when being interleaved. Isolation brings us the benefit of hiding uncommitted state changes from the outside world, as failing transactions shouldn’t ever corrupt the state of the system. Isolation is achieved through concurrency control using pessimistic or optimistic locking mechanisms.
Durability
A successful transaction must permanently change the state of a system, and before ending it, the state changes are recorded in a persisted transaction log. If our system is suddenly affected by a system crash or a power outage, then all unfinished committed transactions may be replayed.
I slightly modified the printer example to make it more explainable
1 document which had 2 pages content was sent to printer
Transaction - document sent to printer
atomicity - printer prints 2 pages of a document or none
consistency - printer prints half page and the page gets stuck. The printer restarts itself and prints 2 pages with all content
isolation - while there were too many print outs in progress - printer prints the right content of the document
durability - while printing, there was a power
cut- printer again prints documents without any errors
Hope this helps someone to get the hang of the concept of ACID
ACID properties are very old and important concept of database theory. I know that you can find lots of posts on this topic, but still I would like to start share answer on this because this is very important topic of RDBMS.
Database System plays with lots of different types of transactions where all transaction has certain characteristic. This characteristic is known ACID Properties.
ACID Properties take grantee for all database transactions to accomplish all tasks.
Atomicity : Either commit all or nothing.
Consistency : Make consistent record in terms of validate all rule and constraint of transaction.
Isolation : Make sure that two transaction is unaware to each other.
Durability : committed data stored forever.
Reference taken from this article:
To quote Wikipedia:
ACID (atomicity, consistency, isolation, durability) is a set of properties that guarantee database transactions are processed reliably.
A DBMS that supports transactions will strive to support all of these properties - any commercial DBMS (as well as several open-source DBMSs) provide full ACID 'support' - although it's often possible (for example, with varying isolation levels in MSSQL) to lessen the ACIDness - thus losing the guarantee of fully transactional behaviour.
ACID Properties in Databases:
Atomicity : Transactions are all or nothing
Consistency: Only valid data is saved (database from one state that is consistent to another state that is also consistent.)
Isolation: Transaction do not effect each other (Multiple transactions can run at the same time in the system. Executing multiple transactions in parallel must have the same results as running them sequentially.)
Durability: Written data will not be lost (even if the database crashes immediately or in the event of a power loss.)
Credit
[Gray] introduced the ACD properties for a transaction in 1981. In 1983 [Haerder] added the Isolation property. In my opinion, the ACD properties would be have a more useful set of properties to discuss. One interpretation of Atomicity (that the transaction should be atomic as seen from any client any time) would actually imply the isolation property. The "isolation" property is useful when the transaction is not isolated; when the isolation property is relaxed. In ANSI SQL speak: if the isolation level is weaker then SERIALIZABLE. But when the isolation level is SERIALIZABLE, the isolation property is not really of interest.
I have written more about this in a blog post: "ACID Does Not Make Sense".
http://blog.franslundberg.com/2013/12/acid-does-not-make-sense.html
[Gray] The Transaction Concept, Jim Gray, 1981.
http://research.microsoft.com/en-us/um/people/gray/papers/theTransactionConcept.pdf
[Haerder] Principles of Transaction-Oriented Database Recovery, Haerder and Reuter, 1983.
http://www.stanford.edu/class/cs340v/papers/recovery.pdf
Transaction can be defined as a collection of task that are considered as minimum processing unit. Each minimum processing unit can not be divided further.
All transaction must contain four properties that commonly known as ACID properties. i.e ACID are the group of properties of any transaction.
Atomicity :
Consistency
Isolation
Durability