There are some similar questions on the topic, but they are not really helping me.
I want to implement a soft delete feature like on StackOverflow, where items are not really deleted, but just hidden. I am using a SQL database. Here are 3 options:
Add a is_deleted boolean field.
Advantages: Simple.
Disadvantages: No date record. Forces me to add a is_deleted = 0 in every query.
Add a deleted_date date field. This is set to NULL if it's not deleted.
Advantages: Has date.
Disadvantages: Still cluttering my queries.
For both of the above
It will also impact performance because there are all these useless rows. They still have to be maintained in indexes. Also an index on the deleted column won't help when fetching non-deleted (the majority) of the rows. Full table scan is needed.
Another option is to create a separate table to hold deleted items:
Advantages: Improved performance when querying non-deleted rows. No need to add conditions to my queries on non-deleted rows. Easier on index maintenance.
Disadvantages: Complexity: Requires data migration for both deletion and undeletion. Need for new tables. Referential integrity is harder to handle.
Is there a better option?
I personally would base my answer off of how often you anticipate your users wanting to access that deleted data or "restore" that deleted data.
If it's often, then I would go with a "Date_Deleted" field and put a calculated "IsDeleted" in my poco in the code.
If it's never (or almost never) then a history table or deleted table is good for the benefits you explained.
I personally almost never use deleted tables (and opt for isDeleted or date_deleted) because of the potential risk to referencial integrity. You have A -> B and you remove the record from B database... You now have to manage referencial integrity because of your design choice.
If the key is numeric, I handle a "soft-delete" by negating the key. (Of course, won't work for identity keys). You don't need to change your code at all, and can easily restore the record by multiplying by -1.
Just another approach to give some thought to... If the key is alphanumeric, you can do something similar by prepending a unique "marker" characters. Since deleted records will all begin with this marker, then will end up off by themselves in the index.
In my opinion, the best way forward, when thinking about scaling and eventual table/database sizes is your third option - a separate table for deleted items. Such a table can eventually be moved to a different database to support scaling.
I believe you have listed the three most common options. As you have seen, each has advantages and disadvantages. Personally, I like taking the longer view on things.
I think your analysis of the options is good but you missed a few relevant points which I list below. Almost all implementations that I have seen use some sort of deleted or versioning field on the row as you suggest in your first two options.
Using one table with deleted flag:
If your indexes all contain the deleted flag field first and your query's mostly contain a where isdeleted=false type structure then it DOES solve you performance problems and the indexes very efficiently exclude the deleted rows. Similar logic could be used for the deleted date option.
Using two Tables
In general you need to make massive changes to reports because some reports may refer to deleted data (like old sales figures might refer to a deleted sales category). One can overcome this by creating a view which is a union of the two tables to read from and only write to the active records table.
Let's suppose we create a field called dead to mark deleted rows. We can create a index where field dead is false.
In this way, we only search non-deleted rows using the hint use index.
Related
Scenario:
Entity 1 can have 0 or more Entity 2.
What trying to do:
When a field in Entity 1 is updated, a field in Entity 2 is consecutively updated.
What I'm doing:
Update field in Entity 1 by update sql, then querying related Entity 2 records (using SELECT ATTR FROM ENTITY2 WHERE ENTITY1.ID = ENTITY2.ENT1_ID) just to get the old value of ENTITY2 attr before doing an update on that records. Type of update (e.g. Subtract or add) on ENTITY2 record is based on the update value on ENTITY1.
Alternative :
Using triggers to consecutively update these related records.
(I still plan to study to implement triggers but I am not sure if it is worth it.
Any help from this also please? Or links?)
Is it better to use triggers? Or just stick to my current solution (which I think is quite slow due to the number of sql executions but easier to track down).
There are people, such as Tom Kyte who believe triggers should be used as little as possible, if at all.
There are others, such as Toon Koppelaars who believe they should be used, if their use is considered carefully.
I am of the second camp and believe triggers may be used. However, this use should not be to 'automagically' cause cascade actions such as you are suggesting. Instead these triggers may be used to enforce integrity constraints that cannot be declared using the standard mechanism of a table constraint clause i.e. the triggers themselves do no DML other than SELECT from tables.
(note: there are other mechanisms by which these constraints may be enforced, including materialized views or the introduction of additional columns and the use of specific indexing strategies) Therefore, I would suggest another alternative. Create triggers - or use these alternative mechanisms - to ensure no data that breaks your integrity constraints can be committed. Then create APIs, using PL/SQL, that encapsulate the multi-table data amendments that are required to ensure the integrity constraints are not broken and use these as your update path.
In this way you can be assured that no invalid data exists in the database, but also that the actual DML required to achieve this is not hidden across the database in multiple program units and triggers but is stated explicitly in one place.
Tom Kyte is brilliant. But he is, at heart, still just a DBA. Always keep that in mind when considering his advice on table design.
Can triggers be overused? Of course. But here's the rub: anything can be overused. I lean toward triggers because there is just no way to guarantee that all data manipulation will go through your app or any single channel. Or, if possible, define a foreign key relationship and let "cascade update" take care of everything. Tricky, I admit, and could be problematic, but don't reject any solution out of hand.
Having said that, I don't know if a trigger for this purpose is called for. I don't know why you are duplicating the data to a field in a different table. Without knowing your overall design and what you are trying to accomplish, there is no way to judge. But consider keeping data in one field in one table then use a view to expose that field as part of a second "table." Change the data where it resides, viola, it is now changed wherever it appears.
Performance hit? Yes. But keeping duplicate data in different places and keeping them synchronized is a data integrity hit. Only you know (or are in a position to find out) which way this balance tilts.
Oh, can views be overused? Of course. But there's always that rub I mentioned; and besides, views are so chronically underused in most databases that overuse would be a long way away.
Due to client requirements I need to implement following scenario:
Whenever user want to delete a record representing a document, that particular record needs to be marked as deleted using simple BOOLEAN is_deleted condition.
Document is a general name for one of the tables that store invoices, orders or offers.
Everything is pretty dead simple, but I wonder if there is a way to index records to perform quick searching and somehow skip/omit deleted items (or there is no need to worry about performance at all and use simple where clause is_deleted=False).
Other solutions/advices would be appreciated as well.
PostgreSQL supports partial indexes. You can do something like:
create index document_id_is_deleted_idx ON document(id) where is_deleted;
You can even create unique indexes if you need unique subsets over portions of your data.
Of course getting the right columns in your index is an exercise, but it is quite manageable.
Another option you might like to explore is to move those records to another table, or to use partitioning to separate the deleted and undeleted rows (which would amount to broadly the same thing).
That would let you keep all the records of interest in a smaller table that can be indexed differently from that of the deleted records.
If you went down the partitioning route you'd have a DOCUMENTS master table with DOCUMENTS_DELETED and DOCUMENTS_LIVE tables inheriting from it.
I wanted to know, what should i consider while deciding if i should create a new table or modify an existing table for a sql db. i use both mysql and sqlite.
-Edit- I always thought if i can put a column into a table where it makes sense and can be used by every row then i would always modify it. However at work if its a different 'release' we put it in a different table.
You can modify existing tables, as long as
you are keeping the database Normalized
you are not breaking code that uses the table
You can create new tables even if 1. and 2. are true for the following reasons:
Performance reasons
Clarity in your schema logic.
Not sure if I'm understanding your question correctly, but one thing I always try to consider is the impact on existing data.
Taking the case of an application which relies on a database...
When you update the application (including database schema updates), it is important to ensure that any existing, in-use databases will be either backwards compatible with the application, or there is way to migrate and update the existing database.
Generally if the data is in a one-to-one relationship with the existing data in the table and if the table row size is not too large already and if there aren't too many records in the table, then I usually alter the table to accept the new column.
However, suppose I want to add a column with a default value to a table where it doesn't exist. Adding it to the table with 50 million records might not be so speedy a process and it might lock up the table on production when we move the change up. In this case, putting it into a separate table and adding the records to it may work out better. In general, I wouldn't do this unless my testing has shown that adding and populating the column will take an unacceptably long time. I would prefer to keep the record together where possible.
Same thing with the overall record size. SQL server has a byte limit to the number of bytes that can be in a record, it will allow you to create a structure that is potentially larger than that, but it will not alow you to put more than the byte limit into a specific record. Further, less wide tables tend to be faster to access due to how they are stored. Frequently, people will create a table that has a one-to-one relationship (we call them extended tables in our structure) for additional columns that are not as frequnetly used. If the fields from both tables will be frequently used, often they still create two tables but have a view that will pickout all the columns needed.
And of course if the data is in a one to many relationship, you need a related table not just a new column.
Incidentally, you should always do an alter table through a script and the SSMS GUI as it is more efficient and easier to move to prod.
OK, so practically every database based application has to deal with "non-active" records. Either, soft-deletions or marking something as "to be ignored". I'm curious as to whether there are any radical alternatives thoughts on an `active' column (or a status column).
For example, if I had a list of people
CREATE TABLE people (
id INTEGER PRIMARY KEY,
name VARCHAR(100),
active BOOLEAN,
...
);
That means to get a list of active people, you need to use
SELECT * FROM people WHERE active=True;
Does anyone suggest that non active records would be moved off to a separate table and where appropiate a UNION is done to join the two?
Curiosity striking...
EDIT: I should make clear, I'm coming at this from a purist perspective. I can see how data archiving might be necessary for large amounts of data, but that is not where I'm coming from. If you do a SELECT * FROM people it would make sense to me that those entries are in a sense "active"
Thanks
You partition the table on the active flag, so that active records are in one partition, and inactive records are in the other partition. Then you create an active view for each table which automatically has the active filter on it. The database query engine automatically restricts the query to the partition that has the active records in it, which is much faster than even using an index on that flag.
Here is an example of how to create a partitioned table in Oracle. Oracle doesn't have boolean column types, so I've modified your table structure for Oracle purposes.
CREATE TABLE people
(
id NUMBER(10),
name VARCHAR2(100),
active NUMBER(1)
)
PARTITION BY LIST(active)
(
PARTITION active_records VALUES (0)
PARTITION inactive_records VALUES (1)
);
If you wanted to you could put each partition in different tablespaces. You can also partition your indexes as well.
Incidentally, this seems a repeat of this question, as a newbie I need to ask, what's the procedure on dealing with unintended duplicates?
Edit: As requested in comments, provided an example for creating a partitioned table in Oracle
Well, to ensure that you only draw active records in most situations, you could create views that only contain the active records. That way it's much easier to not leave out the active part.
We use an enum('ACTIVE','INACTIVE','DELETED') in most tables so we actually have a 3-way flag. I find it works well for us in different situations. Your mileage may vary.
Moving inactive stuff is usually a stupid idea. It's a lot of overhead with lots of potential for bugs, everything becomes more complicated, like unarchiving the stuff etc. What do you do with related data? If you move all that, too, you have to modify every single query. If you don't move it, what advantage were you hoping to get?
That leads to the next point: WHY would you move it? A properly indexed table requires one additional lookup when the size doubles. Any performance improvement is bound to be negligible. And why would you even think about it until the distant future time when you actually have performance problems?
I think looking at it strictly as a piece of data then the way that is shown in the original post is proper. The active flag piece of data is directly dependent upon the primary key and should be in the table.
That table holds data on people, irrespective of the current status of their data.
The active flag is sort of ugly, but it is simple and works well.
You could move them to another table as you suggested. I'd suggest looking at the percentage of active / inactive records. If you have over 20 or 30 % inactive records, then you might consider moving them elsewhere. Otherwise, it's not a big deal.
Yes, we would. We currently have the "active='T/F'" column in many of our tables, mainly to show the 'latest' row. When a new row is inserted, the previous T row is marked F to keep it for audit purposes.
Now, we're moving to a 2-table approach, when a new row is inserted, the previous row is moved to an history table. This give us better performance for the majority of cases - looking at the current data.
The cost is slightly more than the old method, previously you had to update and insert, now you have to insert and update (ie instead of inserting a new T row, you modify the existing row with all the new data), so the cost is just that of passing in a whole row of data instead of passing in just the changes. That's hardly going to make any effect.
The performance benefit is that your main table's index is significantly smaller, and you can optimise your tablespaces better (they won't grow quite so much!)
Binary flags like this in your schema are a BAD idea. Consider the query
SELECT count(*) FROM users WHERE active=1
Looks simple enough. But what happens when you have a large number of users, so many that adding an index to this table would be required. Again, it looks straight forward
ALTER TABLE users ADD INDEX index_users_on_active (active)
EXCEPT!! This index is useless because the cardinality on this column is exactly two! Any database query optimiser will ignore this index because of it's low cardinality and do a table scan.
Before filling up your schema with helpful flags consider how you are going to access that data.
https://stackoverflow.com/questions/108503/mysql-advisable-number-of-rows
We use active flags quite often. If your database is going to be very large, I could see the value in migrating inactive values to a separate table, though.
You would then only require a union of the tables when someone wants to see all records, active or inactive.
In most cases a binary field indicating deletion is sufficient. Often there is a clean up mechanism that will remove those deleted records after a certain amount of time, so you may wish to start the schema with a deleted timestamp.
Moving off to a separate table and bringing them back up takes time. Depending on how many records go offline and how often you need to bring them back, it might or might not be a good idea.
If the mostly dont come back once they are buried, and are only used for summaries/reports/whatever, then it will make your main table smaller, queries simpler and probably faster.
We use both methods for dealing with inactive records. The method we use is dependent upon the situation. For records that are essentially lookup values, we use the Active bit field. This allows us to deactivate entries so they wont be used, but also allows us to maintain data integrity with relations.
We use the "move to separation table" method where the data is no longer needed and the data is not part of a relation.
The situation really dictates the solution, methinks:
If the table contains users, then several "flag" fields could be used. One for Deleted, Disabled etc. Or if space is an issue, then a flag for disabled would suffice, and then actually deleting the row if they have been deleted.
It also depends on policies for storing data. If there are policies for keeping data archived, then a separate table would most likely be necessary after any great length of time.
No - this is a pretty common thing - couple of variations depending on specific requirements (but you already covered them):
1) If you expect to have a whole BUNCH of data - like multiple terabytes or more - not a bad idea to archive deleted records immediately - though you might use a combination approach of marking as deleted then copying to archive tables.
2) Of course the option to hard delete a record still exists - though us developers tend to be data pack-rats - I suggest that you should look at the business process and decide if there is now any need to even keep the data - if there is - do so... if there isn't - you should probably feel free just to throw the stuff away.....again, according to the specific business scenario.
From a 'purist perspective' the realtional model doesn't differentiate between a view and a table - both are relations. So that use of a view that uses the discriminator is perfectly meaningful and valid provided the entities are correctly named e.g. Person/ActivePerson.
Also, from a 'purist perspective' the table should be named person, not people as the name of the relation reflects a tuple, not the entire set.
Regarding indexing the boolean, why not:
ALTER TABLE users ADD INDEX index_users_on_active (id, active) ;
Would that not improve the search?
However I don't know how much of that answer depends on the platform.
This is an old question but for those search for low cardinality/selectivity indexes, I'd like to propose the following approach that avoids partitioning, secondary tables, etc.:
The trick is to use "dateInactivated" column that stores the timestamp of when the record is inactivated/deleted. As the name implies, the value is NULL while the record is active, but once inactivated, write in the system datetime. Thus, an index on that column ends up having high selectivity as the number of "deleted" records grows since each record will have a unique (not strictly speaking) value.
Then your query becomes:
SELECT * FROM people WHERE dateInactivated is NULL;
The index will pull in just the right set of rows that you care about.
Filtering data on a bit flag for big tables is not really good in terms of performance. In case when 'active' determinate virtual deletion you can create 'TableName_delted' table with the same structure and move deleted data there using delete trigger.
That solution will help with performance and simplifies data queries.
Working on a project at the moment and we have to implement soft deletion for the majority of users (user roles). We decided to add an is_deleted='0' field on each table in the database and set it to '1' if particular user roles hit a delete button on a specific record.
For future maintenance now, each SELECT query will need to ensure they do not include records where is_deleted='1'.
Is there a better solution for implementing soft deletion?
Update: I should also note that we have an Audit database that tracks changes (field, old value, new value, time, user, ip) to all tables/fields within the Application database.
I would lean towards a deleted_at column that contains the datetime of when the deletion took place. Then you get a little bit of free metadata about the deletion. For your SELECT just get rows WHERE deleted_at IS NULL
You could perform all of your queries against a view that contains the WHERE IS_DELETED='0' clause.
Having is_deleted column is a reasonably good approach.
If it is in Oracle, to further increase performance I'd recommend partitioning the table by creating a list partition on is_deleted column.
Then deleted and non-deleted rows will physically be in different partitions, though for you it'll be transparent.
As a result, if you type a query like
SELECT * FROM table_name WHERE is_deleted = 1
then Oracle will perform the 'partition pruning' and only look into the appropriate partition. Internally a partition is a different table, but it is transparent for you as a user: you'll be able to select across the entire table no matter if it is partitioned or not. But Oracle will be able to query ONLY the partition it needs. For example, let's assume you have 1000 rows with is_deleted = 0 and 100000 rows with is_deleted = 1, and you partition the table on is_deleted. Now if you include condition
WHERE ... AND IS_DELETED=0
then Oracle will ONLY scan the partition with 1000 rows. If the table weren't partitioned, it would have to scan 101000 rows (both partitions).
The best response, sadly, depends on what you're trying to accomplish with your soft deletions and the database you are implementing this within.
In SQL Server, the best solution would be to use a deleted_on/deleted_at column with a type of SMALLDATETIME or DATETIME (depending on the necessary granularity) and to make that column nullable. In SQL Server, the row header data contains a NULL bitmask for each of the columns in the table so it's marginally faster to perform an IS NULL or IS NOT NULL than it is to check the value stored in a column.
If you have a large volume of data, you will want to look into partitioning your data, either through the database itself or through two separate tables (e.g. Products and ProductHistory) or through an indexed view.
I typically avoid flag fields like is_deleted, is_archive, etc because they only carry one piece of meaning. A nullable deleted_at, archived_at field provides an additional level of meaning to yourself and to whoever inherits your application. And I avoid bitmask fields like the plague since they require an understanding of how the bitmask was built in order to grasp any meaning.
if the table is large and performance is an issue, you can always move 'deleted' records to another table, which has additional info like time of deletion, who deleted the record, etc
that way you don't have to add another column to your primary table
That depends on what information you need and what workflows you want to support.
Do you want to be able to:
know what information was there (before it was deleted)?
know when it was deleted?
know who deleted it?
know in what capacity they were acting when they deleted it?
be able to un-delete the record?
be able to tell when it was un-deleted?
etc.
If the record was deleted and un-deleted four times, is it sufficient for you to know that it is currently in an un-deleted state, or do you want to be able to tell what happened in the interim (including any edits between successive deletions!)?
Careful of soft-deleted records causing uniqueness constraint violations.
If your DB has columns with unique constraints then be careful that the prior soft-deleted records don’t prevent you from recreating the record.
Think of the cycle:
create user (login=JOE)
soft-delete (set deleted column to non-null.)
(re) create user (login=JOE). ERROR. LOGIN=JOE is already taken
Second create results in a constraint violation because login=JOE is already in the soft-deleted row.
Some techniques:
1. Move the deleted record to a new table.
2. Make your uniqueness constraint across the login and deleted_at timestamp column
My own opinion is +1 for moving to new table. Its take lots of
discipline to maintain the *AND delete_at = NULL* across all your
queries (for all of your developers)
You will definitely have better performance if you move your deleted data to another table like Jim said, as well as having record of when it was deleted, why, and by whom.
Adding where deleted=0 to all your queries will slow them down significantly, and hinder the usage of any of indexes you may have on the table. Avoid having "flags" in your tables whenever possible.
you don't mention what product, but SQL Server 2008 and postgresql (and others i'm sure) allow you to create filtered indexes, so you could create a covering index where is_deleted=0, mitigating some of the negatives of this particular approach.
Something that I use on projects is a statusInd tinyint not null default 0 column
using statusInd as a bitmask allows me to perform data management (delete, archive, replicate, restore, etc.). Using this in views I can then do the data distribution, publishing, etc for the consuming applications. If performance is a concern regarding views, use small fact tables to support this information, dropping the fact, drops the relation and allows for scalled deletes.
Scales well and is data centric keeping the data footprint pretty small - key for 350gb+ dbs with realtime concerns. Using alternatives, tables, triggers has some overhead that depending on the need may or may not work for you.
SOX related Audits may require more than a field to help in your case, but this may help.
Enjoy
Use a view, function, or procedure that checks is_deleted = 0; i.e. don't select directly on the table in case the table needs to change later for other reasons.
And index the is_deleted column for larger tables.
Since you already have an audit trail, tracking the deletion date is redundant.
I prefer to keep a status column, so I can use it for several different configs, i.e. published, private, deleted, needsAproval...
Create an other schema and grant it all on your data schema.
Implment VPD on your new schema so that each and every query will have the predicate allowing selection of the non-deleted row only appended to it.
http://download.oracle.com/docs/cd/E11882_01/server.112/e16508/cmntopc.htm#CNCPT62345
#AdditionalCriteria("this.status <> 'deleted'")
put this on top of your #entity
http://wiki.eclipse.org/EclipseLink/Examples/JPA/SoftDelete