This seems to be an overlooked area that could really use some insight. What are your best practices for:
making an upgrade procedure
backing out in case of errors
syncing code and database changes
testing prior to deployment
mechanics of modifying the table
etc...
Liquibase
liquibase.org:
it understands hibernate definitions.
it generates better schema update sql than hibernate
it logs which upgrades have been made to a database
it handles two-step changes (i.e. delete a column "foo" and then rename a different column to "foo")
it handles the concept of conditional upgrades
the developer actually listens to the community (with hibernate if you are not in the "in" crowd or a newbie -- you are basically ignored.)
http://www.liquibase.org
opinion
the application should never handle a schema update. This is a disaster waiting to happen. Data outlasts the applications and as soon as multiple applications try to work with the same data ( the production app + a reporting app for example) -- chances are they will both use the same underlying company libraries... and then both programs decide to do their own db upgrade ... have fun with that mess.
I am a big fan of Red Gate products that help creating SQL packages to update database schemas. The database scripts can be added to source control to help with versioning and rollback.
In general my rule is: "The application should manage it's own schema."
This means schema upgrade scripts are part of any upgrade package for the application and run automatically when the application starts. In case of errors the application fails to start and the upgrade script transaction is not committed. The downside to this is that the application has to have full modification access to the schema (this annoys DBAs).
I've had great success using Hibernates SchemaUpdate feature to manage the table structures. Leaving the upgrade scripts to only handle actual data initialization and occasional removing of columns (SchemaUpdate doesn't do that).
Regarding testing, since the upgrades are part of the application, testing them becomes part of the test cycle for the application.
Afterthought: Taking on board some of the criticism in other posts here, note the rule says "it's own". It only really applies where the application owns the schema as is generally the case with software sold as a product. If your software is sharing a database with other software, use other methods.
That's a great question. ( There is a high chance this is going to end up a normalised versus denormalised database debate..which I am not going to start... okay now for some input.)
some off the top of my head things I have done (will add more when I have some more time or need a break)
client design - this is where the VB method of inline sql (even with prepared statements) gets you into trouble. You can spend AGES just finding those statements. If you use something like Hibernate and put as much SQL into named queries you have a single place for most of the sql (nothing worse than trying to test sql that is inside of some IF statement and you just don't hit the "trigger" criteria in your testing for that IF statement). Prior to using hibernate (or other orms') when I would do SQL directly in JDBC or ODBC I would put all the sql statements as either public fields of an object (with a naming convention) or in a property file (also with a naming convention for the values say PREP_STMT_xxxx. And use either reflection or iterate over the values at startup in a) test cases b) startup of the application (some rdbms allow you to pre-compile with prepared statements before execution, so on startup post login I would pre-compile the prep-stmts at startup to make the application self testing. Even for 100's of statements on a good rdbms thats only a few seconds. and only once. And it has saved my butt a lot. On one project the DBA's wouldn't communicate (a different team, in a different country) and the schema seemed to change NIGHTLY, for no reason. And each morning we got a list of exactly where it broke the application, on startup.
If you need adhoc functionality , put it in a well named class (ie. again a naming convention helps with auto mated testing) that acts as some sort of factory for you query (ie. it builds the query). You are going to have to write the equivalent code anyway right, just put in a place you can test it. You can even write some basic test methods on the same object or in a separate class.
If you can , also try to use stored procedures. They are a bit harder to test as above. Some db's also don't pre-validate the sql in stored procs against the schema at compile time only at run time. It usually involves say taking a copy of the schema structure (no data) and then creating all stored procs against this copy (in case the db team making the changes DIDn't validate correctly). Thus the structure can be checked. but as a point of change management stored procs are great. On change all get it. Especially when the db changes are a result of business process changes. And all languages (java, vb, etc get the change )
I usually also setup a table I use called system_setting etc. In this table we keep a VERSION identifier. This is so that client libraries can connection and validate if they are valid for this version of the schema. Depending on the changes to your schema, you don't want to allow clients to connect if they can corrupt your schema (ie. you don't have a lot of referential rules in the db, but on the client). It depends if you are also going to have multiple client versions (which does happen in NON - web apps, ie. they are running the wrong binary). You could also have batch tools etc. Another approach which I have also done is define a set of schema to operation versions in some sort of property file or again in a system_info table. This table is loaded on login, and then used by each "manager" (I usually have some sort of client side api to do most db stuff) to validate for that operation if it is the right version. Thus most operations can succeed, but you can also fail (throw some exception) on out of date methods and tells you WHY.
managing the change to schema -> do you update the table or add 1-1 relationships to new tables ? I have seen a lot of shops which always access data via a view for this reason. This allows table names to change , columns etc. I have played with the idea of actually treating views like interfaces in COM. ie. you add a new VIEW for new functionality / versions. Often, what gets you here is that you can have a lot of reports (especially end user custom reports) that assume table formats. The views allow you to deploy a new table format but support existing client apps (remember all those pesky adhoc reports).
Also, need to write update and rollback scripts. and again TEST, TEST, TEST...
------------ OKAY - THIS IS A BIT RANDOM DISCUSSION TIME --------------
Actually had a large commercial project (ie. software shop) where we had the same problem. The architecture was a 2 tier and they were using a product a bit like PHP but pre-php. Same thing. different name. anyway i came in in version 2....
It was costing A LOT OF MONEY to do upgrades. A lot. ie. give away weeks of free consulting time on site.
And it was getting to the point of wanting to either add new features or optimize the code. Some of the existing code used stored procedures , so we had common points where we could manage code. but other areas were this embedded sql markup in html. Which was great for getting to market quickly but with each interaction of new features the cost at least doubled to test and maintain. So when we were looking at pulling out the php type code out, putting in data layers (this was 2001-2002, pre any ORM's etc) and adding a lot of new features (customer feedback) looked at this issue of how to engineer UPGRADES into the system. Which is a big deal, as upgrades cost a lot of money to do correctly. Now, most patterns and all the other stuff people discuss with a degree of energy deals with OO code that is running, but what about the fact that your data has to a) integrate to this logic, b) the meaning and also the structure of the data can change over time, and often due to the way data works you end up with a lot of sub process / applications in your clients organisation that needs that data -> ad hoc reporting or any complex custom reporting, as well as batch jobs that have been done for custom data feeds etc.
With this in mind i started playing with something a bit left of field. It also has a few assumptions. a) data is heavily read more than write. b) updates do happen, but not at bank levels ie. one or 2 a second say.
The idea was to apply a COM / Interface view to how data was accessed by clients over a set of CONCRETE tables (which varied with schema changes). You could create a seperate view for each type operation - update, delete, insert and read. This is important. The views would either map directly to a table , or allow you to trigger of a dummy table that does the real updates or inserts etc. What i actually wanted was some sort of trappable level indirection that could still be used by crystal reports etc. NOTE - For inserts , update and deletes you could also use stored procs. And you had a version for each version of the product. That way your version 1.0 had its version of the schema, and if the tables changed, you would still have the version 1.0 VIEWS but with NEW backend logic to map to the new tables as needed, but you also had version 2.0 views that would support new fields etc. This was really just to support ad hoc reporting, which if your a BUSINESS person and not a coder is probably the whole point of why you have the product. (your product can be crap but if you have the best reporting in the world you can still win, the reverse is true - your product can be the best feature wise, but if its the worse on reporting you can very easily loose).
okay, hope some of those ideas help.
These are all weighty topics, but here is my recommendation for updating.
You did not specify your platform, but for NANT build environments I use Tarantino. For every database update you are ready to commit, you make a change script (using RedGate or another tool). When you build to production, Tarantino checks if the script has been run on the database (it adds a table to your database to keep track). If not, the script is run. It takes all the manual work (read: human error) out of managing database versions.
I've heard good things about iBATIS 3 Schema Migrations System:
User Guide: http://svn.apache.org/repos/asf/ibatis/java/ibatis-3/trunk/doc/en/iBATIS-3-Migrations.pdf
As Pat said, use liquibase. Especially when you have several developers with their own dev databases
making changes that will become part of the production database.
If there's only one dev, as on one project I'm on now(ha), I just commit the schema changes as SQL text files into a CVS repo, which I check out in batches on the production server when the code changes go in.
But liquibase is better organized than that!
Related
I want to deploy hybris builds with zero down time. Our technical architecture consist of two frontend servers, two backend servers, two master/slave solr clusters, but a single DB server (MS SQL 2012). A new build may require patch execution which changes the DB schema.
Would it be possible to achieve this in a single DB landscape?
If two DB's are required (blue and green), then what is the best practice for DB replication in case of hybris?
Hybris does provide a rolling update feature (when you're running it in a cluster environment).
This is targeted to allow for zero downtime.
You can find more information on the hybris help pages, e.g.
https://help.hybris.com/6.5.0/hcd/8c455268866910149b25f7b53d1af3e1.html
Looking at the first picture there it seems to be pretty much fitting for the architecture you describe.
(But to be honest I have no experience with it, so I can't tell you whether or or how well it works :) )
If you have risky changes or end up needing to rollback your rolled out update you will have to do quite a bit of db cleanup etc.
From that perspective a blue/green setup might sound better although with db replication you would end up with the same problem (as your updated schema would be replicated as well I assume).
Hybris only adding new columns to db, never change their type or remove them. So single DB can be OK. I didn't test this using store front while updating system. I think it will be OK.
On the other hand you need development for empty/null check for new attributes in development.
In my system I have more than one project, each project connect with individual DB .When Insert transaction occur in any project then record insert on all of the db,but when update event occur in any project then respective update occur only it’s DB not impact rest of the project db.it’s my system process.After continue this process data become difference on each db.With out change this process what I do to overcome this data mismatch problem.
Suppose on system-1 transaction activity :
Transaction -->Update -->Modification occur only on system1 db not in system-2,sytem-3 db
Any type of suggestion will be acceptable,if have any query please ask,thanks in advanced.
I'm currently working in almost the same Project architecture. Our solution is to create Orchestration module that will manage Single_entry_point module. Last one is responsible to unify the information from the Upstream (cluster of different DataBases and Service systems) and after it to upload/distribute it to a Downstream (Single_Data_Warehouse). By doing so - you can guarantee that all your information is actual in every moment. The Orchestrator communicates with Service massages when dealing with all other modules.
This design is based on Pipes and Filters Pattern concept.
I think that in your case, you can only add logic for Update DB information and reuse all that you have at this point. If you spend some time on such Single_entry_point module, which to deal with not only Insert, but with Transaction Update too.
When it comes to Databases “eyeballing” validation (done by SQL scripting) you definatelly have to consider the use of Informatica. To be more specific - when data as it is being moved into production systems. The data in your production systems has to be right in order to support your business decision making. Informatica Data Validation Option provides the ETL testing automation and management capabilities to ensure that your production systems are not compromised by the data update process.
If you find that this options doesn't suits your needs, here are resources I found about this topic:
database-synchronization-an-overview-of-approaches
MSDN Synchronizing Databases
how-to-synchronize-databases-in-different-servers-in-sql-server-2008
sql-comparison-sdk-synchronizing-databases
We are designing our new product, which will include multi-tenancy. It will be written in ASP.NET and C#, and may be hosted on Windows Azure or some other Cloud hosting solution.
We’ve been looking at MVC and other technologies and, to be honest, we’re getting bogged down in various acronyms (MVC, EF, WCF etc. etc.).
A particular requirement of our application is causing a headache – the users will be able to add fields to the database, or even create a whole new module.
As a result, each tenant would have a database with a different structure to every other tenant using the system. We envisage that every tenant will have their own database, rather than sharing a database.
(Adding fields etc. to the system will be accomplished using a web interface).
All well and good, but the problem comes when creating a data model for MVC. Modifying a data model programmatically to add a field to a table seems to be impossible, according to this link:
Create EDM during runtime?
This is a major headache for us. Even if we don’t use MVC, I think we’d still want to create a data model (perhaps for used with LINQ to SQL).
We’re considering having a table with loads of fields in it, and instead of adding fields to the database we allocate an existing field in the table when the user wants to add a field to his form. Not sure I like that idea, though.
Of course, we don’t have to use MVC or Entity Framework, but it appears to me that these are the kind of technologies that Microsoft would steer us towards for future development.
Any thoughts? I’m assuming that we’re not the first people in the world to consider this idea of a user-customisable application.
I'd make sure that you have fully explored the option of creating 'Name-Value Pair' type tables as described here http://msdn.microsoft.com/en-us/library/aa479086.aspx#mlttntda_nvp
before you start looking at a customizable schema. Also don't forget that you are going to have to grant much higher permissions to your sql accounts in order for them to create tables on the fly.
A customizable schema means that your sql accounts will also need much higher permissions. It wouldnt be advisable to assign these higher permissions to a tenants account, but to a separate provisioning account which can perform these tasks.
Also before investing effort into EF - try googling 'EF Vote of No Confidence'. It was raised (i believe) mainly in reaction to earlier versions but its definately worth reading up on. nHibernate is an alternative worth investigating.
Just off the top of my head it sounds like a bad idea to allow users to change the database schema. I think you are missing a layer of abstraction. In my mind, it would be more correct to use the database to hold data that describes the format of a customer's data. The actual data would then be saved in a text column as xml, including version information.
This solution may not fit your needs, but I don't know the details of your project. So just consider it my 5 cents.
Most modern SQL databases today supports the 'jsonb' type for key/value storage as a field. Other types (hstor for postgres) exists too. Forget about XML, that's yesterday and no application with respect for itself implements XML unless it is for importing/converting old data.
Recently I had a project in which I had to get some data from particular software system to a portlet. The software used a database, and I spent a fair bit of time modeling the data I wanted and then creating a web service so that my portlet could grab the information.
Then it suddenly struck me that I was wasting my time. I grabbed BIRT, tossed it into a portlet, and then just wrote some reports that directly grabbed the necessary data from the database. I was done in an afternoon.
I understand that reporting is a one way street, but this got me thinking. Reporting tools can be very effective for creating reports (duh) from your actual data, but when you're doing this you're bypassing your model which except in simple cases is not a direct representation of your data as it exists in your database.
If you're writing a data-intensive application and require the ability to perform non-trivial reporting, do you bypass your application and use something like BIRT or Crystal Reports? How do you manage these tools as part of your overall process? Do you consider the reports you write as being part of your application and treat them as such? A report is a view and a model and a controller (if you will) all in one big mess, how do you deal with and interpret and plan for that?
Revised question: it's possible and even common that a report will perform some business calculations that in a perfect world you would like to have contained in your application. This can lead to a mismatch of information given back to the user. On the other hand, reporting tools make it so easy to gather and display information that it's hard to take a purist's approach and do everything from within the application. Are there any good techniques for ensuring that the data in your reports matches the data that you might be showing in the regular GUI?
I see reporting as simply another view on the data, not a view/model/controller in one (well, maybe a view and controller in one).
We have our reports (built in sql 2008 reporting services) consume a service in our application layer to get data (keeping with our standard, that data access is in a repository). These functions could do a simple query or handle very complex processing that would be a nightmare in your reporting evironment or a stored procedure. In practice, we find this takes no longer than coding up some one-off stored procedure that will, as your system grows and grows, become a nightmare to maintain.
Treating reporting as simply a one-off or not integrating into your application design is a huge mistake.
Reporting is crucial. Reporting is mostly crucial to share values collected in one system to external users, e.g. users not directly using the system (eg management for sales figures). So reporting is a lot more than just displaying facts and figures and is something central to almost every system that drives a commercial.
At least the more advanced systems allow you to enhance them: with your own reusable "controls". Even a way back can be implemented - if you just use the correct plugins. Once I wrote a system to send emails out of a report, because the system did not allow for change. It worked - though it was not meant to be used that way ;)
Reports make a good part of the application, and you gain a lot freedom if you make reports changeable for your customers. Sometimes you come up with more possibilities than you thought of when you built the system in the first place.
So yes, for me reporting is part of the system.
Reports are part of your app but because they are generally something a user will have strong ideas about than, say, your data capture UI, I'd sacrifice purity for convenience/speed of delivery and get back to "real" coding... :-)
As soon as you've done a report, users want another one or change the colour or optional grouping or more filtering or... something that takes you away from whizzier stuff... so I don't bust a gut maintaining purity.
This is a fine line indeed. You don't want to spend too much time building reports (that users want you to change all the time anyway) but you don't want to duplicate logic by putting business logic into your reports! With our reporting products at Data Dynamimcs I think we have reached a happy medium between these two tradeoffs.
By using the ObjectDataProvider (see links below for more info) you can bind the report directly to business objects (plain old objects) so you don't have to bypass your business layer for getting data. At the same time we provide a way to reference and use functions from other libraries in your report. This way if you have some code configured already to do some business logic calculations you can reuse those functions directly within your report. You can see an example of this in the links below too.
Binding to Objects for your Data (see "Object Provider" section): http://www.datadynamics.com/Help/ddReports/ddrconDataSetAndObjectDataSource.html
Adding Custom Code to your reports Walkthrough: http://www.datadynamics.com/Help/ddReports/ddrwlkCustomCode.html
Using Custom Assemblies (referencing shared libraries/dlls from your report): http://www.datadynamics.com/Help/ddReports/ddrconCustomCode.html, and http://www.datadynamics.com/Help/ddReports/ddrtskCreatingAnInstanceMethod.html
Scott Willeke
Data Dynamics / GrapeCity
The way I've always worked with reports is to consider part reports as part of the code-base, and stored in the source along with the application. In some contexts, reports are more important than the application, in that management makes business decisions off of report data, having the wrong information can cause them to cancel a product line, cancel a campaign, or fire a sales person. Obviously, this depends highly on your management and your application.
Regarding keeping your model consistent, this is a bit trickier question. One way to ensure consistent model between reports and your application is to use stored procedures (or views) to retrieve data, depending on your application's architecture.
I have an ASP .NET application that connects to an Oracle or a SQL Server database. An installer has been developed to install a fresh database to an existing SQL Server using sql commands such as "restore database..." which simply restores a ".bak" file which we keep under source control.
I'm very new to Oracle and our application has only recently been ported to be compatible with 10g.
We are currently using the "exp.exe" tool to generate a ".dmp" file and then using the "imp.exe" to import it into a developers box.
How would you go about creating an "Oracle Database Installer"?
Would you create the database using script files and then populate the database with required default data?
Would you run the "imp.exe" tool behind the scenes?
Do we need to provide a clean interface for system administrators so that they can just select the destination server and have done, or should we just provide them with the ".dmp" file? What are the best practices?
Thanks.
The question is -- what do your customers know about Oracle?
Nothing? You should probably rethink this position. Oracle is very large and complex. If you assume your customers know nothing, you'll then start providing tutorials and help that's inappropriate.
Minimally Competent? If they're competent, they know enough to run imp by themselves. Also, they know enough to run a script that executes SQL.
Actual DBA's? Most organizations that can afford Oracle can afford real DBA's. Real DBA's can cope with a lot of things -- they do not need much hand-holding. Some of them like to assign storage parameters according to their shop standards.
You should provide a script with reasonable defaults. You should define your script in a way that someone can easily find all of your storage parameters and tweak them if necessary.
Your initial data can be via export/import or via a script. I prefer a script.
I have done this repeatedly from both sides (consumer and provider) as a DBA, developer, and architect.
As a provider, one of my grand accomplishments (in 1996) was the creation of an installation CD for a commercial insurance claims management software product targeted to the largest insurance carriers (a multi-million dollar item). That installation CD installed the Oracle 7.2 RDBMS engine, the FileNet optical storage system (scans paper documents and creates cataloged binary versions), and our custom claim-processing application (built in VB 4.0), all integrated and ready to run. As part of the installation process, the user could skip the Oracle software installation or customize it, and the user could customize/override the database configuration in all of its major details (database, schemas, tablespaces, sizes, disks, etc.).
I also provided the field service for this product, which included traveling to the client site as necessary. I tested the installation CD literally hundreds of times under every imaginable scenario that I could replicate, and we NEVER had a field failure that required even a phone call, let alone a trip (I did travel on four occasions, but for pre-sales stuff instead).
More recently (2007), I scripted the creation of an Oracle 10g database for an internal system at a megacorp. In production, the database was sized at 8 TB, mostly for a single transaction table with high data volume. In test, the database was sized around 1 TB for a modest server. In development, the database was sized around 100 MB to run on my laptop. The EXACT SAME SCRIPTS created all three environments, and I could extend them to handle a new environment/machine in about five minutes. This database involved extreme performance tuning, so customization of all pertinent characteristics was absolutely crucial.
Back to the insurance claims processing product--let me please add that I was originally hired to lead its conversion from a SQL Server database to an Oracle database. That conversion was identified as a business necessity because most potential clients did not view a SQL-Server-based product as a professional, serious solution. That is not quite as common today, but it still applies in general: a software product has a better chance of market penetration if it can accommodate multiple database options as preferred by the target customers (especially enterprise-class customers).
Likewise, the installation CD was also viewed as an essential element. However, that situation and many more have revealed to me that most "real" DBAs will not accept an import-based database installation. As a DBA and architect, I know that I definitely will not for the same reasons.
Simply put, an import-based database installation gives the customer almost no control over the resulting database. It is opaque to the customer, leaving them questioning what it did. It forces the customer to expend massive efforts to attempt to exercise what little control they can. It is notoriously fragile and error-prone (Oracle imports are well known for ownership and permission problems, constraint problems, etc.). Weighing all those impacts, an import-based database installation is unprofessional--it does not put the customers' needs first.
Scripting the database installation provides the right kind of transparency, configurability, selective repeatability, and overall customer control that professionalism demands. It also encourages you to properly understand the impacts of your database design decisions in a way that an import does not.
Best wishes.
Personally I favour SQL scripts to database creation and data loads where possible. I tend to use PL/SQL Developer. It has some good options to generate scripts from an existing database. Once you have these you can run the scripts using sqlplus or any application code that can execute arbitrary SQL (eg JDBC with Java). Toad is the more common (and more expensive) tool for Oracle development.
The only limitation of a SQL export is it can't export CLOB/BLOB fields. If you have those, you either need to do them separately (as a PL/SQL export) or do the whole thing as a PL/SQL export. Theres no dramas with this except the file is effectively a binary export (extension .pde) and is more limited in how you can execute it.
The other big advantage of SQL source files is they can be version controlled easily. It's really handy to be able to create a database environment by running one or two scripts.
The import and export tools for Oracle I think are more applicable for backup and restore operations.
Now, as for delivering that to a customer, from your comments it seems that you'll be giving this to DBAs. Pretty much any Oracle installation will have DBAs involved. They will be fine with SQL scripts to create the schema and do the data load. They will be doing a lot of site-specific configuration (eg tuning the SGA, temp tablespaces, # of concurrent connections, etc based on expected load).
You, as the vendor, can give guidance on any relevant configuration and you may get involved in support and possibly installation but ultimately it's up to them to figure out what works for them. Oracle runs on a large number of operating systems and hardware variants with infinite variations in network topology and firewall configuraiton. You can't factor in all of these to an installer or even a set of instructions (other than the guidelines mentioned previously).
The last time I was involved in the creation of a (oracle) db (for a reasonably large company with in-house DBAs) the DBAs wanted to know things like:
what we wanted to call the db,
what tablespaces we would need, and an estimate of how much data would be in each one
how many users would be connecting.
(From memory) they set up the db and tablespaces, then we provided a combination of simple scripts that they could run (or clear instructions if a task wasn't easy to automate)
As I say this was for an in-house app, so your mileage may vary, but in my case they wanted all instructions clearly spelt out so that (a) there was no possibily of a misunderstanding leading to the wrong thing being done, and (b) no culpability on their part if something didn't work ("we were just following the instructions")