MySQL database sync for workstation developement/testing - mysql

I need a local copy of our production database, and I need to refresh it every few days so testing and development is not working with terribly stale data. A few days old is just fine. Here is the pseudo plan:
Write a script on the Production server that mysqldump's + gzip the database.
Add a cron process to run the script every other day during non-peak hours.
Write a script on the workstation that rsync's that gzipped dump and loads it up.
Is there any better, cleaner, or safer way of doing this?
EDIT: Just to add clarity. We still have in place Test Data that is known, along with our test library (test driven development). Once THOSE tests pass, its on to the (more) real stuff.

You may wish to consider MySQL replication. It isn't a thing to be trifled with but may be what you are looking for. More information here... http://dev.mysql.com/doc/refman/5.0/en/replication-features.html (I don't personally know anything about it other than that it can be done).

Testing should be working with "known" data; not production data. You should have scripts to load "Test" data into the system to achieve this. Test/Dev shouldn't have to deal with a moving target of data. Besides, if you have any sensitive data in production (doesn't everyone"); your dev/test teams shouldn't have access to it.
Some suggestions for creating test data:
1) Excel spreadsheets with VBA behind them to create sql to run against the DB
2) Raw sql scripts
3) Data creation programs that generate data in a known pattern.

Related

How to reconcile WordPress data between staging and production [duplicate]

I've had a hard time trying to find good examples of how to manage database schemas and data between development, test, and production servers.
Here's our setup. Each developer has a virtual machine running our app and the MySQL database. It is their personal sandbox to do whatever they want. Currently, developers will make a change to the SQL schema and do a dump of the database to a text file that they commit into SVN.
We're wanting to deploy a continuous integration development server that will always be running the latest committed code. If we do that now, it will reload the database from SVN for each build.
We have a test (virtual) server that runs "release candidates." Deploying to the test server is currently a very manual process, and usually involves me loading the latest SQL from SVN and tweaking it. Also, the data on the test server is inconsistent. You end up with whatever test data the last developer to commit had on his sandbox server.
Where everything breaks down is the deployment to production. Since we can't overwrite the live data with test data, this involves manually re-creating all the schema changes. If there were a large number of schema changes or conversion scripts to manipulate the data, this can get really hairy.
If the problem was just the schema, It'd be an easier problem, but there is "base" data in the database that is updated during development as well, such as meta-data in security and permissions tables.
This is the biggest barrier I see in moving toward continuous integration and one-step-builds. How do you solve it?
A follow-up question: how do you track database versions so you know which scripts to run to upgrade a given database instance? Is a version table like Lance mentions below the standard procedure?
Thanks for the reference to Tarantino. I'm not in a .NET environment, but I found their DataBaseChangeMangement wiki page to be very helpful. Especially this Powerpoint Presentation (.ppt)
I'm going to write a Python script that checks the names of *.sql scripts in a given directory against a table in the database and runs the ones that aren't there in order based on a integer that forms the first part of the filename. If it is a pretty simple solution, as I suspect it will be, then I'll post it here.
I've got a working script for this. It handles initializing the DB if it doesn't exist and running upgrade scripts as necessary. There are also switches for wiping an existing database and importing test data from a file. It's about 200 lines, so I won't post it (though I might put it on pastebin if there's interest).
There are a couple of good options. I wouldn't use the "restore a backup" strategy.
Script all your schema changes, and have your CI server run those scripts on the database. Have a version table to keep track of the current database version, and only execute the scripts if they are for a newer version.
Use a migration solution. These solutions vary by language, but for .NET I use Migrator.NET. This allows you to version your database and move up and down between versions. Your schema is specified in C# code.
Your developers need to write change scripts (schema and data change) for each bug/feature they work on, not just simply dump the entire database into source control. These scripts will upgrade the current production database to the new version in development.
Your build process can restore a copy of the production database into an appropriate environment and run all the scripts from source control on it, which will update the database to the current version. We do this on a daily basis to make sure all the scripts run correctly.
Have a look at how Ruby on Rails does this.
First there are so called migration files, that basically transform database schema and data from version N to version N+1 (or in case of downgrading from version N+1 to N). Database has table which tells current version.
Test databases are always wiped clean before unit-tests and populated with fixed data from files.
The book Refactoring Databases: Evolutionary Database Design might give you some ideas on how to manage the database. A short version is readable also at http://martinfowler.com/articles/evodb.html
In one PHP+MySQL project I've had the database revision number stored in the database, and when the program connects to the database, it will first check the revision. If the program requires a different revision, it will open a page for upgrading the database. Each upgrade is specified in PHP code, which will change the database schema and migrate all existing data.
You could also look at using a tool like SQL Compare to script the difference between various versions of a database, allowing you to quickly migrate between versions
Name your databases as follows - dev_<<db>> , tst_<<db>> , stg_<<db>> , prd_<<db>> (Obviously you never should hardcode db names
Thus you would be able to deploy even the different type of db's on same physical server ( I do not recommend that , but you may have to ... if resources are tight )
Ensure you would be able to move data between those automatically
Separate the db creation scripts from the population = It should be always possible to recreate the db from scratch and populate it ( from the old db version or external data source
do not use hardcode connection strings in the code ( even not in the config files ) - use in the config files connection string templates , which you do populate dynamically , each reconfiguration of the application_layer which does need recompile is BAD
do use database versioning and db objects versioning - if you can afford it use ready products , if not develop something on your own
track each DDL change and save it into some history table ( example here )
DAILY backups ! Test how fast you would be able to restore something lost from a backup (use automathic restore scripts
even your DEV database and the PROD have exactly the same creation script you will have problems with the data, so allow developers to create the exact copy of prod and play with it ( I know I will receive minuses for this one , but change in the mindset and the business process will cost you much less when shit hits the fan - so force the coders to subscript legally whatever it makes , but ensure this one
This is something that I'm constantly unsatisfied with - our solution to this problem that is. For several years we maintained a separate change script for each release. This script would contain the deltas from the last production release. With each release of the application, the version number would increment, giving something like the following:
dbChanges_1.sql
dbChanges_2.sql
...
dbChanges_n.sql
This worked well enough until we started maintaining two lines of development: Trunk/Mainline for new development, and a maintenance branch for bug fixes, short term enhancements, etc. Inevitably, the need arose to make changes to the schema in the branch. At this point, we already had dbChanges_n+1.sql in the Trunk, so we ended up going with a scheme like the following:
dbChanges_n.1.sql
dbChanges_n.2.sql
...
dbChanges_n.3.sql
Again, this worked well enough, until we one day we looked up and saw 42 delta scripts in the mainline and 10 in the branch. ARGH!
These days we simply maintain one delta script and let SVN version it - i.e. we overwrite the script with each release. And we shy away from making schema changes in branches.
So, I'm not satisfied with this either. I really like the concept of migrations from Rails. I've become quite fascinated with LiquiBase. It supports the concept of incremental database refactorings. It's worth a look and I'll be looking at it in detail soon. Anybody have experience with it? I'd be very curious to hear about your results.
We have a very similar setup to the OP.
Developers develop in VM's with private DB's.
[Developers will soon be committing into private branches]
Testing is run on different machines ( actually in in VM's hosted on a server)
[Will soon be run by Hudson CI server]
Test by loading the reference dump into the db.
Apply the developers schema patches
then apply the developers data patches
Then run unit and system tests.
Production is deployed to customers as installers.
What we do:
We take a schema dump of our sandbox DB.
Then a sql data dump.
We diff that to the previous baseline.
that pair of deltas is to upgrade n-1 to n.
we configure the dumps and deltas.
So to install version N CLEAN we run the dump into an empty db.
To patch, apply the intervening patches.
( Juha mentioned Rail's idea of having a table recording the current DB version is a good one and should make installing updates less fraught. )
Deltas and dumps have to be reviewed before beta test.
I can't see any way around this as I've seen developers insert test accounts into the DB for themselves.
I'm afraid I'm in agreement with other posters. Developers need to script their changes.
In many cases a simple ALTER TABLE won't work, you need to modify existing data too - developers need to thing about what migrations are required and make sure they're scripted correctly (of course you need to test this carefully at some point in the release cycle).
Moreover, if you have any sense, you'll get your developers to script rollbacks for their changes as well so they can be reverted if need be. This should be tested as well, to ensure that their rollback not only executes without error, but leaves the DB in the same state as it was in previously (this is not always possible or desirable, but is a good rule most of the time).
How you hook that into a CI server, I don't know. Perhaps your CI server needs to have a known build snapshot on, which it reverts to each night and then applies all the changes since then. That's probably best, otherwise a broken migration script will break not just that night's build, but all subsequent ones.
Check out the dbdeploy, there are Java and .net tools already available, you could follow their standards for the SQL file layouts and schema version table and write your python version.
We are using command-line mysql-diff: it outputs a difference between two database schemas (from live DB or script) as ALTER script. mysql-diff is executed at application start, and if schema changed, it reports to developer. So developers do not need to write ALTERs manually, schema updates happen semi-automatically.
If you are in the .NET environment then the solution is Tarantino (archived). It handles all of this (including which sql scripts to install) in a NANT build.
I've written a tool which (by hooking into Open DBDiff) compares database schemas, and will suggest migration scripts to you. If you make a change that deletes or modifies data, it will throw an error, but provide a suggestion for the script (e.g. when a column in missing in the new schema, it will check if the column has been renamed and create xx - generated script.sql.suggestion containing a rename statement).
http://code.google.com/p/migrationscriptgenerator/ SQL Server only I'm afraid :( It's also pretty alpha, but it is VERY low friction (particularly if you combine it with Tarantino or http://code.google.com/p/simplescriptrunner/)
The way I use it is to have a SQL scripts project in your .sln. You also have a db_next database locally which you make your changes to (using Management Studio or NHibernate Schema Export or LinqToSql CreateDatabase or something). Then you execute migrationscriptgenerator with the _dev and _next DBs, which creates. the SQL update scripts for migrating across.
For oracle database we use oracle-ddl2svn tools.
This tool automated next process
for every db scheme get scheme ddls
put it under version contol
changes between instances resolved manually

test and production server deployment with yii framework - syncing DB changes

I am working on a Yii framework based app where I have to test the app on my local machine and then when ready move the changes to the production server.
the app will be developed as people are using it and ask for new features. So when I make changes to my DB schema on the test machine I have to apply these to the schema of the production DB without destroying data there.
is there a recommended and convenient way to deal with this? syncing source code is less of an issue, i am using svn and can do svn export ; rsync ...
MySQLWorkbench can be helpful for syncing db schema as well as other database design tasks.
Yii does support Migrations (since v1.1.6), although it can be more trouble than it's worth depending on how often you make changes and how collaborative your project is.
Another approach I've used is to keep a log of update statements in svn and basically handled the migrations manually.
The best approach is going to depend on the cost/benefits to your particular project/workflow.
You can try SQLyog's Schema Synchronization Tool, which is a visual comparison/synchronization tool designed for developers who work between different MySQL servers or need to keep databases between two MySQL servers in sync. This means reporting the differences between tables, indexes, columns and routines of two databases, and generating scripts to bring them in Sync. Only the Schema will be synced in the target.
For a similar project we
use MySQLWorkbench (MWB) to design and edit the schema
share the .mwb file through a VCS.
When one of us is comfortable with a change he uses mysqldump --complete-insert... on the production and test schemas to generate a copy of the existing test and production data with field names
pull out all the production server insert statements in (3) and put them in protected/data/insert.sql
use the "forward engineer" menu item in MWB on the modified model to generate sql to save to a file called protected/data/create.sql, hand-editing as appropriate (be sure to use the if exists clause to reduce errors)
write a drop.sql file based on drop statements in (3)
use MWB, run the sql (drop.sql, create.sql, insert.sql) after issuing the appropriate "use database" command that identifies the production database
deal with all the errors in (7) by getting rid of any invalid inserts due to columns/fields that are not needed in the new models/schema. Rerun (7)
deal with new fields in (7) that need data other than Null. Rerun (7)
Now you have a snapshot of your schema (drop.sql create.sql) and your data that should revive either your test or production server if you ever have a problem. And you have a "fixture" of the data that was in your production server (insert.sql) that can be used to bring your test server up to speed, or as a backup of the production server data (that will quickly be outdated). Obviously all the foreign key relationships are what are really painful, so it's rare that the insert.sql is useful for anything except upgrading the schema and restoring the production data after this change. Clearly it takes some time to work out the kinks in the process so that the delay between (3) and (9) is small enough that the production server users don't notice the downtime.
Clearly "Rerun (7)" gets repetitive and quickly turns into a shell script that calls mysql directly. Also other steps in the sql editing process become sed scripts.
Have a look at schema comparison tool in dbForge Studio for MySQL.
This tool will help you to compare and synchronize two databases or a database project with specified database.
Also there is separate tool - dbForge Schema Compare for MySQL.

Access: How to get most recent datetime of table data changes

I have inherited a legacy Access app that has a TON of code running before the main form comes up. This code imports data, deletes data, and changes data a million ways.
Is there a way where (after the startup stuff is finished) I can list the tables and when each of them had data affected most recently?
Thanks!
Sorry, but I'm afraid the answer to your question is simply: No.
Here's an idea though:
Make a backup of the database file.
Open the app so it runs the code you are concerned about.
Compare the DB to the backup using a tool like Red Gate SQL Data compare.
BTW: I'm not sure if the RedGate tool works against access databases, but FMSInc. has one that claims to.

Migration strategies for SQL 2000 to SQL 2008

I've perused the threads here on migration from SQL 2000 to SQL 2008 but haven't really run into my question, so here we go with another one.
I'm building a strategy to move specific SQL 2000 databases to a new SQL 2008 R2 instance. My question comes with regards to the best method for transferring the schema and data. One way I know of is to do the quick 'n' dirty detach - copy - attach method, which should work so long as I've done my homework wrt compatibility and code and such.
What if, though, I wrote the schema and logins via script and then copied the data via SSIS? I'm thinking of trying that so I can more easily integrate some of my test cases into the package (error handling and whatnot). What would I be setting myself up for if I did this?
Since you are moving the data between servers or instances, I would recommend moving the data via data flows. If you don't expect to run the code more than once, then you can let the wizard generate your code for this move. However, when I did this once 2+ years ago, the wizard code generated combined execute sql tasks that combined many "create table" commands into one task and created a few data flow tasks that had multiple source and destinations in them to insert data in the destination. This was good to get up and running, but it was inadequate when I wanted to refresh the tables one more time after I modified the schema of the new target tables. If you expect to run the refresh more than once, then you may want to take the time to create the target schema first and then manually create the data flows.
Once you have moved the data, then you can enable full-text search on the new server. I don't believe you will need to have this enabled on your first load.
One reason I recommend against the detach-attach method for migration is that you bring all the dirty laundry from the 2000 database to the 2008 R2 database. If you had too lax security on the 2000 server or many ancient users that shouldn't exist, it could be easier to clean this up by starting from scratch. If you use the detach-attach method, then you have to worry about users.

How do you manage databases in development, test, and production?

I've had a hard time trying to find good examples of how to manage database schemas and data between development, test, and production servers.
Here's our setup. Each developer has a virtual machine running our app and the MySQL database. It is their personal sandbox to do whatever they want. Currently, developers will make a change to the SQL schema and do a dump of the database to a text file that they commit into SVN.
We're wanting to deploy a continuous integration development server that will always be running the latest committed code. If we do that now, it will reload the database from SVN for each build.
We have a test (virtual) server that runs "release candidates." Deploying to the test server is currently a very manual process, and usually involves me loading the latest SQL from SVN and tweaking it. Also, the data on the test server is inconsistent. You end up with whatever test data the last developer to commit had on his sandbox server.
Where everything breaks down is the deployment to production. Since we can't overwrite the live data with test data, this involves manually re-creating all the schema changes. If there were a large number of schema changes or conversion scripts to manipulate the data, this can get really hairy.
If the problem was just the schema, It'd be an easier problem, but there is "base" data in the database that is updated during development as well, such as meta-data in security and permissions tables.
This is the biggest barrier I see in moving toward continuous integration and one-step-builds. How do you solve it?
A follow-up question: how do you track database versions so you know which scripts to run to upgrade a given database instance? Is a version table like Lance mentions below the standard procedure?
Thanks for the reference to Tarantino. I'm not in a .NET environment, but I found their DataBaseChangeMangement wiki page to be very helpful. Especially this Powerpoint Presentation (.ppt)
I'm going to write a Python script that checks the names of *.sql scripts in a given directory against a table in the database and runs the ones that aren't there in order based on a integer that forms the first part of the filename. If it is a pretty simple solution, as I suspect it will be, then I'll post it here.
I've got a working script for this. It handles initializing the DB if it doesn't exist and running upgrade scripts as necessary. There are also switches for wiping an existing database and importing test data from a file. It's about 200 lines, so I won't post it (though I might put it on pastebin if there's interest).
There are a couple of good options. I wouldn't use the "restore a backup" strategy.
Script all your schema changes, and have your CI server run those scripts on the database. Have a version table to keep track of the current database version, and only execute the scripts if they are for a newer version.
Use a migration solution. These solutions vary by language, but for .NET I use Migrator.NET. This allows you to version your database and move up and down between versions. Your schema is specified in C# code.
Your developers need to write change scripts (schema and data change) for each bug/feature they work on, not just simply dump the entire database into source control. These scripts will upgrade the current production database to the new version in development.
Your build process can restore a copy of the production database into an appropriate environment and run all the scripts from source control on it, which will update the database to the current version. We do this on a daily basis to make sure all the scripts run correctly.
Have a look at how Ruby on Rails does this.
First there are so called migration files, that basically transform database schema and data from version N to version N+1 (or in case of downgrading from version N+1 to N). Database has table which tells current version.
Test databases are always wiped clean before unit-tests and populated with fixed data from files.
The book Refactoring Databases: Evolutionary Database Design might give you some ideas on how to manage the database. A short version is readable also at http://martinfowler.com/articles/evodb.html
In one PHP+MySQL project I've had the database revision number stored in the database, and when the program connects to the database, it will first check the revision. If the program requires a different revision, it will open a page for upgrading the database. Each upgrade is specified in PHP code, which will change the database schema and migrate all existing data.
You could also look at using a tool like SQL Compare to script the difference between various versions of a database, allowing you to quickly migrate between versions
Name your databases as follows - dev_<<db>> , tst_<<db>> , stg_<<db>> , prd_<<db>> (Obviously you never should hardcode db names
Thus you would be able to deploy even the different type of db's on same physical server ( I do not recommend that , but you may have to ... if resources are tight )
Ensure you would be able to move data between those automatically
Separate the db creation scripts from the population = It should be always possible to recreate the db from scratch and populate it ( from the old db version or external data source
do not use hardcode connection strings in the code ( even not in the config files ) - use in the config files connection string templates , which you do populate dynamically , each reconfiguration of the application_layer which does need recompile is BAD
do use database versioning and db objects versioning - if you can afford it use ready products , if not develop something on your own
track each DDL change and save it into some history table ( example here )
DAILY backups ! Test how fast you would be able to restore something lost from a backup (use automathic restore scripts
even your DEV database and the PROD have exactly the same creation script you will have problems with the data, so allow developers to create the exact copy of prod and play with it ( I know I will receive minuses for this one , but change in the mindset and the business process will cost you much less when shit hits the fan - so force the coders to subscript legally whatever it makes , but ensure this one
This is something that I'm constantly unsatisfied with - our solution to this problem that is. For several years we maintained a separate change script for each release. This script would contain the deltas from the last production release. With each release of the application, the version number would increment, giving something like the following:
dbChanges_1.sql
dbChanges_2.sql
...
dbChanges_n.sql
This worked well enough until we started maintaining two lines of development: Trunk/Mainline for new development, and a maintenance branch for bug fixes, short term enhancements, etc. Inevitably, the need arose to make changes to the schema in the branch. At this point, we already had dbChanges_n+1.sql in the Trunk, so we ended up going with a scheme like the following:
dbChanges_n.1.sql
dbChanges_n.2.sql
...
dbChanges_n.3.sql
Again, this worked well enough, until we one day we looked up and saw 42 delta scripts in the mainline and 10 in the branch. ARGH!
These days we simply maintain one delta script and let SVN version it - i.e. we overwrite the script with each release. And we shy away from making schema changes in branches.
So, I'm not satisfied with this either. I really like the concept of migrations from Rails. I've become quite fascinated with LiquiBase. It supports the concept of incremental database refactorings. It's worth a look and I'll be looking at it in detail soon. Anybody have experience with it? I'd be very curious to hear about your results.
We have a very similar setup to the OP.
Developers develop in VM's with private DB's.
[Developers will soon be committing into private branches]
Testing is run on different machines ( actually in in VM's hosted on a server)
[Will soon be run by Hudson CI server]
Test by loading the reference dump into the db.
Apply the developers schema patches
then apply the developers data patches
Then run unit and system tests.
Production is deployed to customers as installers.
What we do:
We take a schema dump of our sandbox DB.
Then a sql data dump.
We diff that to the previous baseline.
that pair of deltas is to upgrade n-1 to n.
we configure the dumps and deltas.
So to install version N CLEAN we run the dump into an empty db.
To patch, apply the intervening patches.
( Juha mentioned Rail's idea of having a table recording the current DB version is a good one and should make installing updates less fraught. )
Deltas and dumps have to be reviewed before beta test.
I can't see any way around this as I've seen developers insert test accounts into the DB for themselves.
I'm afraid I'm in agreement with other posters. Developers need to script their changes.
In many cases a simple ALTER TABLE won't work, you need to modify existing data too - developers need to thing about what migrations are required and make sure they're scripted correctly (of course you need to test this carefully at some point in the release cycle).
Moreover, if you have any sense, you'll get your developers to script rollbacks for their changes as well so they can be reverted if need be. This should be tested as well, to ensure that their rollback not only executes without error, but leaves the DB in the same state as it was in previously (this is not always possible or desirable, but is a good rule most of the time).
How you hook that into a CI server, I don't know. Perhaps your CI server needs to have a known build snapshot on, which it reverts to each night and then applies all the changes since then. That's probably best, otherwise a broken migration script will break not just that night's build, but all subsequent ones.
Check out the dbdeploy, there are Java and .net tools already available, you could follow their standards for the SQL file layouts and schema version table and write your python version.
We are using command-line mysql-diff: it outputs a difference between two database schemas (from live DB or script) as ALTER script. mysql-diff is executed at application start, and if schema changed, it reports to developer. So developers do not need to write ALTERs manually, schema updates happen semi-automatically.
If you are in the .NET environment then the solution is Tarantino (archived). It handles all of this (including which sql scripts to install) in a NANT build.
I've written a tool which (by hooking into Open DBDiff) compares database schemas, and will suggest migration scripts to you. If you make a change that deletes or modifies data, it will throw an error, but provide a suggestion for the script (e.g. when a column in missing in the new schema, it will check if the column has been renamed and create xx - generated script.sql.suggestion containing a rename statement).
http://code.google.com/p/migrationscriptgenerator/ SQL Server only I'm afraid :( It's also pretty alpha, but it is VERY low friction (particularly if you combine it with Tarantino or http://code.google.com/p/simplescriptrunner/)
The way I use it is to have a SQL scripts project in your .sln. You also have a db_next database locally which you make your changes to (using Management Studio or NHibernate Schema Export or LinqToSql CreateDatabase or something). Then you execute migrationscriptgenerator with the _dev and _next DBs, which creates. the SQL update scripts for migrating across.
For oracle database we use oracle-ddl2svn tools.
This tool automated next process
for every db scheme get scheme ddls
put it under version contol
changes between instances resolved manually