I have some code that uses an Informix 11.5 database that I want to run some tests against.
If the tests fail they will often leave the database in an inconsistent state that needs to be manually resolved before the tests can be run again.
I would like to automate this so that the tests do not require manual intervention before running the tests again.
My current solution is to write some code that does the cleanup, but this means the code must be maintained whenever potential new inconsistent states can occur in new features.
The code runs a lot of stored procedures, which themselves often use transactions. As Informix does not support nested transactions I can't just wrap up all the work in one big transaction.
Is there another way to create a checkpoint which I can restore the database back to?
You could create a virtual machine with an undo disk and after you run the test you can close the virtual machine without saving the changes. It's equivalent to like you never ran the tests!
If this is a development only server, how about taking a Level 0 ontape system archive before the test? I think this can be done via the sysadmin functions too (not sure though), so it can be automated. After the tests you just restore the archive.
Changing database state - and resetting it back to a known state - is one of the reasons that the Unit Test community spends time and effort avoiding testing against databases. It is a tough problem.
Informix 11.50 does support savepoints; however, it does not support one BEGIN WORK after another without an intervening COMMIT or ROLLBACK.
To the extent possible, have the tests create and load a set of tables with the known data. One way of achieving that is to create a whole new database for the test. However, this is only borderline feasible if you need to test with high volumes of data.
I don't think this issue is in any way unique to Informix - it is a general problem with testing DBMS operations.
Related
we have several technologies accessing the same database. At the moment, Ruby/Rails is used to create migrations when making changes to the database. The question is a simple one:
Is it possible for our DBAs to make changes to the database (not using Ruby migrations) without stepping on the Ruby devs toes and breaking the Ruby web application?
If so, some generic details about how to get started or pointed in the right direction would be great! Thanks.
I can tell you from experience that this is not the best idea, one that you will eventually regret and later, inevitably, reverse. But I know that it does come up. I've had to do them (against my will or in case of extreme emergencies).
Given the option, I'd push back on it if you can in favor of any solution that bring the SQL closer to the repository and further away from a "quick fix" to the database directly. Why?
1) Your local/testing/staging/production databases will diverge, eventually rendering your code untestable in a reliable way
2) You won't be able to regenerate your database from "scratch" to match production
3) If the database is ever clobbered, you won't be able to re-create it in any sensible way.
DBA's generally don't care about these things until something in the code breaks, and they want you to figure it out. But, for obvious reasons, that now becomes quite difficult.
One approach I have taken that seems to make everyone happy is to do the following:
1) Commit to having ALL database changes, big or small, put into a repository with the code. This means that everything that has happened to the database is all together in one place.
2) Each change, or set of changes, should be a migration. A migration can be simply running an SQL file. But, it should be run from within a migration for all the testability benefits.
So, for example, let's say you have a folder structure like:
- database_updates
-- v1
--- change_1.sql
--- change_2.sql
-- v2
--- change_3.sql
--- change_2_fix.sql
Now, let say you want to make a change or set of change via SQL. First, create a new version folder, let's call it "v1". Next, put your SQL scripts in this folder. Finally, create a migration:
def change
# Read all files in v1 folder, and run the SQL
end
(I have code that does this, happy to share the gist if you find yourself using this approach)
Since each migration is transactional, any of the scripts that fail will cause all of them to fail.
Now, let's say you have the next set, v2. Same exact thing. And, we have a history of these "versioned" changes, so we can look at the migration history and see what's been run, etc.
As a power user note, this set up also allows for recourse if things fail; in these cases, we can opt to go back to v1:
def up
# run v2 scripts
end
def down
# run v1 scripts
end
For this to work, v1 and v2 would need to be autonomous -- that is, they can destroy and rebuild entities without any dependencies. If that's not what you want, just stick with the change method.
This would also allow you to test for breaking changes. Let's say it is reported that something doesn't work anymore with v6. You can rollback your database migrations to v5, v4, etc (because you are doing a migration per folder) and test to see when the test broke, and correct it with v7.
Anyway, the end game of it all is that you can safely check out this project from a repository, create your database, run rake db:migrate and know that your database structure resembles exactly what is deployed elsewhere. And, worst case, if your database gets clobbered, you can just run all your scripts from v1 - vN and end up with your database back again.
For DBA's everything remains SQL for them, they can just send you a file or set of files for you to run.
If you want to get fancy, you could even write a migration generator that knows how to handle a line like rails g migration UpdateDBVersion version:v7 to take care of the repetitive boilerplate.
As long as everyone relies on the same updated schema.rb or structure.sql, everyone will share the same database 'version'.
See this SO answer for more insight.
Changes to the database, tables, or indexes should be made using ActiveRecord migrations whenever possible. This specifically ensures that development and test environments remain logically in sync. Remember that developers must be capable of accurate development and testing against the same database structure as occurs in the production environment, and QA teams must be able to adequately test such changes.
However, some database features are not actually supported by ActiveRecord migrations, and may only be applied directly to the database. These features are often database-specific, such as any of the following:
Views
Triggers
Stored procedures
Indexes with function-based columns
Virtual columns
Essentially any database-specific features that don't have an ActiveRecord abstraction will be made directly to the database.
Sometimes, however, other applications require the addition of tables, columns, or indexes in order to operate properly or efficiently. These other applications may simply be used to view/report against the database, or they may be substantial business applications that have their own independent database requirements and separate development teams. Occasionally, a DBA may have to step in and create an index or provide some optimization needed to solve a real-world production performance issue.
There are simply far too many situations for shared database management to give a definitive answer. Depending on the size of the organization and the complexity of the needs for the shared management, there may be many ways to solve the problem of a shared database schema that are specific to the application or organization.
For instance, I have worked on applications that shared a database with as many as 10 other applications, each of which "owned" portions of the schema and shared other portions with the other teams, all mediated through the DBA group. In situations such as this, the organizational structure and change control process may be the only means of solving this problem.
Whichever the situation, some real-world suggestions may help avoid problems and mitigate maintenance woes:
Offer to translate SQL DDL commands into ActiveRecord migrations, where possible, so that DBAs can accomplish their needs, and the application team can still appropriately maintain the schema
Any changes made outside the ActiveRecord migration should be thoroughly tested for impact to the project in a non-production environment by the same QA resources that test the actual Rails application
Encapsulate any external changes in a .sql file and include the file as part of the project in version control
If the development team is using the same database product in development (some cannot, due to licensing or complexity), those changes should be applied to the developer database instances, as well
It's best if you can apply the changes during a migration, even just by calling the relevant CLI tools as a migration step - the exact mechanism will be database-dependent, as well
Try to avoid doing this more than is absolutely necessary, as this can significantly reduce the database independence of the application, even between versions of the same database product (limiting upgrade opportunities)
We're using Grails as our web framework and we have integration tests that we want to have isolated. One idea that was brought up is to drop the database after every test case. What are alternative and more applicable ways to achieve test isolation.
we were doing two things:
rollback transaction. this deals with most of the problems (DML) but not all (for example sequences). also sometimes you need to commit a few transactions to make a proper tests. that's why we:
reset the database. you can achieve it in many ways: use frameworks that cleans data (db-unit), do manual reverts of inserted data, drop db or, as we did, truncate all tables and run custom script (if you need to reset sequences or something else). it's much faster than dropping and recreating db. it worked really good
You probably don't need something that aggressive. Each integration test is run in a transaction that's rolled back at the end of the test, so you shouldn't see anything from previous tests. There are cases where you want to commit a transaction though, so you can disable the automatic transaction and rollback and manage things yourself. That will increase the likelihood of data pollution between tests but it's easy enough to fix.
Since the database is in-memory initially, it's relatively inexpensive to drop the whole database and re-create all of the tables and objects, but this will be significantly slower if you move to a "real" database, e.g. a local install of Postgres to ensure that tests are running as close to how the code will run in production as possible.
I have an MVC app that using EF6 Code First. I want to deploy this app to multiple datacenters. On deployments that have migrations, I can write a script to migrate them all as simultaneously as possible, but if one datacenter is slower, then the calls could all be rejected since the schema no longer matches. A script that tried to coordinate would also make rolling upgrades impossible.
Is there a way to make EF at least attempt to run the query even though the schemas don't match? Is there a different way I can/should approach this?
UPDATE:
Let's see if I can word this better. I want to have my MVC app in multiple datacenters. Let's assume that I deploy the app to each datacenter individually.
Option 1
Deploy to DC A
Code first migration runs on centralized DB
Requests made to DC A succeed, but requests to DC B fail
Option 2
Deploy to DC A
Do not automatically run migration
Requests made to DC A fail and requests to DC B continue to succeed
How do I develop a deployment strategy that will make it so that requests to either DC will work?
BTW: I am using Azure Web Sites, if a platform-specific solution is needed.
In your post, it seemed like you were concerned with how it would behave during the actual upgrade. Nothing about testing. But in comments you are asking about doing a partial deployment then doing testing. So on one hand you'd want to deploy as quickly as possible to minimize downtime. On the other hand, it sounds like you want to deploy to one site, test, and have the other sites continue to function while you are verifying the first deployment?
Verifying a deployment is reasonable, but fairly complex. I'm not sure you will find much in the way of automation for this. I think you should test prior to production deployment thoroughly, and then simply deploy as quickly as possible in production. If there were an issue you found only when deploying to production, you'd be in a bad situation, because now your site is down until you can fix it. Even if you could get the other instance to work with the new database, that is risky as it is going to be modifying things against a schema it doesn't completely understand. Additionally, if you do need to rollback the DDL then you will almost certainly lose any data that was modified since the deployment. So it is really best that all instances for the old schema fail until they are upgraded, to prevent them from modifying data that is at risk of being lost.
Usually you should have done a deployment to a staging environment that is as close to your production as possible to test the database migration process. This is called pre-production testing, and sometimes involves restoring the most recent backup from production into staging to ensure new constraints/structures are valid for existing data. By deploying to this staging environment, you should have a very high level of confidence that production deployment will go successfully.
You additionally safe guard yourself against production deployment issues by taking backups prior to deployment so that you can rollback as necesary(although this is worst case scenario as it might mean throwing out important data that came in between backup/deployment and realization that there is an issue). I imagine EF migrations uses a transaction to run the DDL scripts so they should rollback all-or-nothing if there is an issue.
I am building an app that is fast moving into production and I am concerned about the possibility that due to hacking, some silly personal error (like running rake db:schema:load or rake db:rollback) or other circumstance we may suffer data loss in one database table or even across the system.
While I don't find it likely that the above will happen, I would be remiss in not being prepared in case it ever does.
I am using Heroku's PG Backups (which is to be replaced with something else this month), and I also run automated daily backups to S3: http://trevorturk.com/2010/04/14/automated-heroku-backups/, successfully generating .dump files.
What is the correct way to deal with data loss on a production app?
How would I restore the .dump file in case I need to? Can I do a selective restore if a small part of the system is hit?
In case a selective restore is not possible: assume one table loses data 4 hours after the last backup. Result => would fixing the lost table require rolling back 4 hours of users' activity? Any good solution to this?
What is the best way to support users through the inconvenience if something like this happens?
A full DR (disaster recovery) solution requires the following:
Multisite. If a fire, flood, Osama Bin Laden or whathaveyou strikes the Amazon (or is it Salesforce?) data center that Heroku uses, you want to be sure that your data is safe elsewhere.
On-going replication of the data to a separate site (or sites). That means that every transaction that's written to your database on one site, is replicated within seconds to the mirror database on the other site. Most RDBMS's have mechanisms to let you do a master-slave replication like that.
The same goes for anything you put on a filesystem outside of the database, such as images, XML configuration files etc. S3 is a good solution here - they replicate everything to multiple data centers for you.
I won't hurt to create periodic (daily or so) dumps of the database and store them separately (e.g. on S3). This helps you recover from data corruption that propagates to the slave DBs.
Automate the process of data recovery. You want this to just work when you need it.
Test everything. Ideally, you want to automate the test process and run it periodically to ensure that your backups can restore. Netflix Chaos Monkey is an extreme example of this.
I'm not sure how you'd implement all this on Heroku. A complete solution is still priced out of reach for most companies - we're running this across our own data centers (one in the US, one in EU) and it costs many millions. Work according to the 80-20 rule - on-going backup to a separate site, plus a well tested recovery plan (continuously test your ability to recover from backups) covers 80% of what you need.
As for supporting users, the best solution is simply to communicate timely and truthfully when trouble happens and make sure you don't lose any data. If your users are paying for your service (i.e. you're not ad-supported), then you should probably have an SLA in place.
About backups, you cannot be sure at 100 percent every time that no data will be lost. The best is to test it on another server. You must have at leat two types of backup :
A database backup, like pg-dump. A dump is uniquely SQL commands so you can use it to recreate the whole database, just a table, or just a few rows. You loose the data added in the meantime.
A code backup, for example a git repository.
in addition to Hartator's answer:
use replication if your DB offers it, e.g. at least master/slave replication with one slave
do database backups on a slave DB server and store them externally (e.g. scp or rsync them out of your server)
use a good version control system for your source code, e.g. Git
use a solid deploy mechanism, such as Capistrano and write your custom tasks, so nobody needs to do DB migrations by hand
have somebody you trust check your firewall setup and the security of your system in general
The DB-Dumps contain SQL-commands to recreate all tables and all data... if you were to restore only one table, you could extract that portion from a copy of the dump file and (very carefully) edit it and then restore with the modified dump file (for one table).
Always restore first to an independent machine and check if the data looks right. e.g. you could use one Slave server, take if offline, then restore there locally and check the data. Good if you have two slaves in your system, then the remaining system has still one master and one slave while you restore to the second slave.
To simulate a fairly simple "total disaster recovery" on Heroku, create another Heroku project and replicate your production application completely (except use a different custom domain name).
You can add multiple remote git targets to a single git repository so you can use your current production code base. You can push your database backups to the replicated project, and then you should be good to go.
The only step missing from this exercise verses a real disaster recovery is assigning your production domain to the replicated Heroku project.
If you can afford to run two copies of your application in parallel, you could automate this exercise and have it replicate itself on a regular basis (e.g. hourly, daily) based on your data loss tolerance.
What data do you use with Selenium tests on Rails apps? Do you load from fixtures? Use an existing dev db? Use a separate (non-fixture) db?
I'm considering my options here. I have a Rails app with a large Selenium test suite that runs on a modified version of Selenium Grid. Part of the process, right now, is loading a large set of fixtures, once, before the test suite runs. It's a LOT of data. Most of it is reporting info exported from our production db. When I set it up originally, I exported the data to yaml from Oracle.
Now there's been a schema change in some of the reporting tables, so of course I have to regenerate the fixture data. There is so much of it that it's not worthwhile to edit the files by hand. But it seems inefficient to have to regenerate for every little schema change - not to mention that it's yet another step to remember to do. Is there a better way?
EDIT: I originally intended to load the fixtures before each test and unload them after each test, like regular Rails tests. But it takes about 15 minutes to load the fixtures due to this reporting data. There are 200+ tests, and the suite runs every 12 hours. I cannae bend spacetime captain!
EDIT 2: I also agree that having this big set of fixtures is a bad smell. I'm not sure how to pare it down, though, because the reports aggregate a lot of data and much of the value of the selenium tests is that they test the reports.
Even if it's a small set of data, though...it's still another set to keep co-ordinated with schema changes. (We have a separate, smaller set for unit, functional, and [Rails] integration tests.)
Which brings me back to my original question - are there other options besides doing it by hand, or remembering to regenerate them each time?
If you can, the best possible thing to do is have a system in which each Selenium test gets it's own data state (ie: DB tables dropped and recreated, bootstrap data re-inserted, and caches cleared). This is easier said than done and usually is only possible if the project planned for it from the start.
The next best thing is to have a consistent DB state for each test suite/run. This is not as nice since there is now a strong chance that some tests will depend on the success of previously run tests, making it more difficult identify true failures vs. false negatives.
The worst case, IMO, is to use a static DB in which each test run mutates the date. This almost always leads to problems and is usually a "project smell". The key to doing it the "right way" (again, IMO) is to be vigilant about any state/schema change and capture it as part of the automated test/build process.
Rails does a good job with this already with Migrations, so take advantage of them! Without knowing your situation, I'd generally question the need to run Selenium tests against a snap of the full DB. Most DBs can (or should) be distilled down to less than 1MB for automated testing, making automated schema migrations and data reset much more efficient.
The only time I've seen a "valid" reason for massive DBs for Selenium tests is when the DB itself contains large chunks of "logic data" in which the data affects the application flow (think: data-driven UI).
I think you're asking two questions here that are intertwined so if I'm to break it down:
You want to get test data into and out of your DB quickly and fixtures aren't doing it for you.
You've been burnt by a schema change and you want to make sure that whatever you do doesn't require eight iterations themed "fiddling with the test data...still" :)
You've got a couple of alternatives here which I've hashed out below. Because you've mentioned Oracle I'm using Oracle technologies here but the same thing is true for other DB platforms (e.g. Postgresql):
Rake tesks that call PL/SQL scripts to generate the data, nasty horrible evil idea, don't do it unless there's no other option. I did it on one project that needed to load in billions of rows for some infrastructure architecture tests. I still sulk about it.
Get your DB into a dump format. For speedy binary dumps check out the exp/imp and data pump utilities. This will allow you quick setup and teardown of your DB. Certainly on a rails project I worked on we used rake tasks to exp/imp a database which had around 300k records in under a minute. Also check SQLLoader which is the logical dump utility, as its logical its slower and requires you to have control scripts to help SQLLoader understand the dumps. However, the benefit of the logical dump is that you can run transformation scripts over them to massage the data into the latest format. Sadly though just like fixtures all these tools are pretty sensitive to change in the schema.
Use a plugin such as Machinist or Factory Girl to make the generation of the data nicer. You still incur the penalty of using ActiveRecord to setup the DB but these fake object generators will help you stay close to you migrations and are a lot less hassle to maintain than fixtures.
Combine approaches 2 and 3. What happens here is that you make some test data with say Machinst. You export that test data to a dump and then reload the dump during each test run. When the schema changes update the Machinist config and re-export.
Hope that helps.
I'm currently on a project with an enormous Selenium test suite--actually, the one Selenium Grid was written for--and our tests use a small amount of reference data (though we don't use Rails YAML fixtures) and object factories for one-off data needed for particular tests.
Alternatively, on many of the ThoughtWorks Rails projects I've been on we've written checkin scripts that incorporate a number of pre-commit hooks--for example, running the tests before allowing a commit. One thing you might consider trying is writing (or customizing) a similar checkin script that will check for schema changes and reload the reference data as needed.
See e.g. Paul Gross's rake commit tasks on Github.