I need to insert a field in the middle of current fields of a database table. I'm currently doing this in VB6 but may get the green light to do this in .net. Anyway I'm wondering since Access gives you the ability to "insert" fields in the table is there a way to do this in ADOX? If I had to I could step back and use DAO, but not sure how to do it there either.
If yor're wondering why I want to do this applications database has changed over time and I'm being asked to create Upgrade program for some of the installations with older versions.
Any help would be great.
This should not be necessary. Use the correct list of fields in your queries to retrieve them in the required order.
BUT, if you really need to do that, the only way i know is to create a new table with the fields in the required order, read the data from the old table into the new one, delete the old table and rename the new table as the old one.
I hear you: in Access the order of the fields is important.
If you need a comprehensive way to work with ADOX, your go to place is Allen Browne's website. I have used it to from my novice to pro in handling Access database changes. Here it is: www.AllenBrowne.com. Go to Access Tips then scroll down to ADOX Code.
That is also where I normally refer people with doubts about capabilities of Access as a database :)
In your case, you will juggle through creating a new table with the new field in the right position, copying data to the new table, applying properties to the fields, deleting original table, renaming the new table to the required (original) name.
That is the correct order. Do not apply field properties before copying the data. Some indexes and key properties may not be applied when the fields already have data.
Over time, I have automated this so I just run an application to do detect and implement the required changes for me. But that took A LOT of work-weeks.
Related
Ok, tricky question I am trying to figure out where a database schema is storing a particular pointer. I know the pointer value I just don't what table it is in or what column. I know the pointer is 123123123. How do I check all table columns to see if any of them have that value?
Thanks.
In h2 you can use fulltext search, but then you would need to add all tables in the search scope and indexing.
If you need to index only primary keys, then it might be better but you still need to come up with individual FT_CREATE_INDEX() calls for each table. You can automate this with several languages or with ETLs (like scriptella).
If you've enough disk space, you could dump a SQL from your db and use a viewer for big files like glogg.
The advantage of the first solution is no external tools but you need to work out a specific indexing script for SQL for any existing or new table. The 2nd solution is a 1 time fix.
I use SQL Search from RedGate. It's free and it helps you find any text anywhere in the database.
https://www.red-gate.com/products/?gclid=CjwKEAjwiYG9BRCkgK-G45S323oSJABnykKAE7IH_EMhnmq7OdLdXljfIkdGZrDD6OnOrT4VB0agahoCVn3w_wcB
I'm trying to make a database table for every single username. I see that for every username, I can add more columns in it's row, but I want to attribute a full table for each one. How can I do that?
Thanks,
Eli
First let me say, what you are trying to do sounds like really, really bad database design and you should rethink your idea of creating a table per user. To get help for this you should add way more detail about the reasoning to your question to get a good answer. As far as I know there is also a maximum number of classes you can create on Parse so sooner or later you will run into problems, either performance wise or due to technical limitations of the platform.
That being said, you can use the Schema API to programmatically create/delete/update tables of your Parse app. It always requires the master key, so doing this from the client side is not recommended for security reasons. You could put this into a Cloud Code function for example and call this one from your app/admin tool to create a new table for a user on the fly or delete a table of a user.
Again, better don't do it and think about a better way to design your database, it would be out of scope here to discuss it.
I am new to Cassandra. I am looking at many examples online. Here is one from JHipster Cassandra examples on GitHub:
https://gist.github.com/jdubois/c3d3bedb869466731316
The repository save(user) method does a read (to look for existence) then a delete and re-insert of the existing user across all the denormalized tables whenever the user data changed.
Is this best practice?
Is this only because of how the data model for this sample is designed?
Is this sample's design a result of twisting a POJO framework into a NoSQL database design?
When would I want to just do a update in Cassandra? It supports updates at the field-level, so it seems like that would be preferred.
First of all, the delete operations should be part of the batch for more robust error handling. But it looks like there are also some concurrency issues with the code. It will update the user based on the current user value read before. It's not save to assume this will still be the latest value while save() is actually executed. It will also just overwrite any keys in the lookup table that might be in use for a different user at that point. E.g. the login could already exist for another user while executing insertByLoginStmt.
It is not necessary to delete a row before inserting a new one.
But if you are replacing rows and new columns are different from existing columns then you need to delete all existing columns and insert new columns. Or insert new and delete old, does not matter if happens in batch.
We are developing an application based on DDD principles. We have encountered a couple of problems so far that we can't answer nor can we find the answers on the Internet.
Our application is intended to be a cloud application for multiple companies.
One of the demands is that there are no physical deletions from the database. We make only passive deletion by setting Active property of entities to false. That takes care of Select, Insert and Delete operations, but we don't know how to handle update operations.
Update means changing values of properties, but also means that past values are deleted and there are many reasons that we don't want that. One of the primary reason is for Accounting purposes.
If we make all update statements as "Archive old values" and then "Create new values" we would have a great number of duplicate values. For eg., Company has Branches, and Company is the Aggregate Root for Branches. If I change Companies phone number, that would mean I have to archive old company and all of its branches and create completely new company with branches just for one property. This may be a good idea at first, but over time there will be many values which can clog up the database. Phone is maybe an irrelevant property, but changing the Address (if street name has changed, but company is still in the same physical location) is a far more serious problem.
Currently we are using ASP.NET MVC with EF CF for repository, but one of the demands is that we are able to easily switch, or add, another technology like WPF or WCF. Currently we are using Automapper to map DTO's to Domain entities and vice versa and DTO's are primary source for views, ie. we have no view models. Application is layered according to DDD principle, and mapping occurs in Service Layer.
Another demand is that we musn't create a initial entity in database and then fill the values, but an entire aggregate should be stored as a whole.
Any comments or suggestions are appreciated.
We also welcome any changes in demands (as this is an internal project, and not for a customer) and architecture, but only if it's absolutely neccessary.
Thank you.
Have you ever come across event sourcing? Sounds like it could be of use if you're interested in tracking the complete history of aggregates.
To be honest I would create another table that would be a change log inserting the old record and deleted records etc etc into it before updating the live data. Yes you are creating a lot of records but you are abstracting this data from live records and keeping this data as lean as possible.
Also when it comes to clean up and backup you have your live date and your changed / delete data and you can routinely back up and trim your old changed / delete and reduced its size depending on how long you have agreed to keep changed / delete data live with the supplier or business you are working with.
I think this would be the best way to go as your core functionality will be working on a leaner dataset and I'm assuming your users wont be wanting to check revision and deletions of records all the time? So by separating the data you are accessing it when it is needed instead of all the time because everything is intermingled.
not sure if the subject entirely conveys what I'm trying to achieve, but let me explain:
We are building an application that uses Oracle as storage backend. Each year, last years dataset will be "Archived", and a new instance created and populated from scratch.
What are the options to do this within the same schema?
Keep version information on a record level (we presume this will be too slow for our use-case).
Keep version information on a table level, so for each new version, we will re-create all the tables but with a new version prefix. (We like this solution, since we can do it all in code).
?
Is there not something like partitions/personalities/namespaces available that will allow us to achieve this in Oracle?
My oracle experience is rather limited, any assistance will be greatly appreciated!
The RDBMS conceptual model is not very good at maintaining temporal versions of data. So it is not just Oracle which is lacking in this regard.
I am unclear why you think keeping version information at the record level will be too slow. Too slow in creating a new version? Or too slow where it comes to data retrieval during regular operations?
Here is how you could do it. Given a table CUSTOMERS with a business key of CUSTOMER_REF I might normally build it like this (I am using abbreviated syntax rather than best practice for reasons of space):
create table customers
( id number not null primary key
, customer_ref number not null unique key
, name varchar2(30) not null )
/
The versioned equivalent would look like this:
create table customers
( id number not null primary key
, customer_ref number not null
, version_number number
, name varchar2(30) not null
, constraint whatever unique (customer_ref, version_number) )
/
This works by keeping the current version of VERSION_NUMBER null, and only populating it at archival time. Any lookup is going to have to include and version_number is null. This will be a bit of a pain and you may need to include the column in any additional indexes you build.
Obviously maintaining all versions of the records in the same table will increase the size of your tables, which might have an effect on performance. Oracle's Partitioning option can definitely help here. It also would give you a neat way of creating next year's set of data. However, it is a chargeable extra on top of the Enterprise License, so it is an expensive option. Find out more..
The most time consuming aspect of this will be managing foreign key relationships in the new version of the table. Presuming you choose to use synthetic primary keys, the archival process will have to generate new IDs and then painstakingly cascade them to their dependent records in the new versions of referencing foreign keys.
Thinking about this makes discreet tables for each version seem very attractive. For ease of use I would keep the current version un-prefixed, so that archiving becomes a process simply of
create table customers_n as select * from customers;
You might want to avoid downtime while creating the versioned tables. In that case you could use materialized views to capture the tables' state during the run-up to the archival switchover. When the clock strikes twelve you can switch off the refresh. (caveat: this is thinking on the fly, I have never done anything like this so try before you buy.)
One pertinent advantage of multiple tables (and Partitioning) is that you can move the archived records to a READ ONLY tablespace. This not only preserves them from unwanted change, it also means you can exclude them from subsequent backups.
edit
I notice you have commented that the archived data can occasionbally be amended. In taht case moving it to READ ONLY tablespaces is not a go-er.
The only thing I wil add to what APC said is regarding your asking for "namespaces".
A namespace in Oracle is a schema, whereby you can have the same object name(s) in each schema.
Of course this all depends on how your app must access multiple versions, but I would lean towards a different schema for each year before I would use some sort of naming convention to maintain versions of tables in the same schema. The reason is, eventually you will have a nightmares. At least with different schemas, all DDL can be the same, all references to objects will be the same, and tools like ER modellers and query tools will work within the context of that schema. Data models change, so at some point you may need to run some compare tools, and if all your tables are named funky with some sort of version postfix, that won't work well.
Add a schema can be copied / moved with export or data pump quickly using the fromuser/touser or remap_schema options, so you won't need much code, except to do any cleanup of last years data out of the new version.
I find schemas are very useful as "containers" and most apps I host only have schema level privileges, so I'm guaranteed the app can be easily and quickly moved from instance to instance, or multiple copies of the app can be hosted side-by-side on the same instance.
Might the schema change between years. For example, in 2010 you have fifteen columns but in 2011 you add a sixteenth.
If so, will the same application work on both 2010 and 2011 data.
If the schema is static, I'd go for table with a 'YEAR' column and use VPD/RLS/FGAC to apply a YEAR = '2010' predicate.
I'd only worry about partitioning if performance was a problem.
1) Interval partition it by year and some date field in the row.
2) Add it at the end of each table and populate it with a sequence and trigger.
3) Then partition by interval year on this col.