We've a productive MySQL-Database which private user data inside (passwordhashes, ips, emails etc).
When a developer run a buildjob in jenkins on his developer-vm, we want to include a copy of the live-database so that he get an environment which is very similar to our production one. But we've to clean up the production database before it is copied to the dev-server because of 2 reasons:
Developers shouldn't get a copy of all our user data like hashed passwords or emails
The database is big, so we want to delete some of the contents that the dev has a few real data sets for testing, but not > 100k, that will have no benefit and will increase the time which the dump take
I thought about this and tried a few things, but I found no method which is fast and will do the job.
My first idea was to make a dump of all the data by mysqldump, import it on the dev-machine, and send some MySQL-Querys for setting placeholders instead of private data
UPDATE user_data SET email = "dev#example.com" [...]
On the one hand this is slow because it have to copy the huge database AND do the querys. And I don't like it that all of our user-data is on the dev-machine, even for a short time period. I would like it better when the data gets cleaned first and then exported to the dev-machine. This would be possible by copying the database in a temp one on the production system, then clean the data, export it and delete the copied database on the production system. But this also created a lot of overhead.
What is a good and fast method for doing this?
I thought about something like mysqldump with replacing the data, so that no overhead is created. But i can't find any tool which can do this.
Do you have enough room for two databases on the production server? If so, make a developer db on the same server (or any server, really) which is a nightly dump of production, minus all the sensitive information and bulk.
Developers get access to only this "developer" database, from the production server, which you know has been pruned of anything sensitive. As a bonus, they could connect directly to it, and possibly never need to download it.
Related
Often times I use bash scripts to add massive amounts of data to my localhost site databses, once I see that the new data is working properly in my local website I export the database from phpmyadmin and edit the sql file , granted with vim it is realtively easy to change all inserts to insert ignore and so on to prepare it to be accepted in phpmyadmin in cpanel to finaly add the data to my website. this becomes cumbersome when the database gets bigger and bigger
I am new to this and I don't know how to do this operation in a professional/optimal way. is my entire process wrong? how do you do it ?
thank you for your answers
Ah, I think I understand better. I can't answer for any kind of specific enterprise environment, but I'm sure there are many different systems cobbled together with all sorts of creative baler twine and you could get a wide variety of answers to this question.
I'm actually working on a project right now where we're trying to keep data updated between two systems. The incoming data gets imported to a MySQL database and every now and then, new data is exported to a .sql file. Each row has an auto incrementing primary key "id", so we very simply keep track of the last exported ID and start the export from there (using mysqldump and the --where argument). This is quite simple and doesn't feel like an "enterprise-ready" solution, but it's fine for our needs. That avoids the problem of duplicated inserts.
Another solution would be to export the entire database from your development system, then through some series of actions import it to the production server while deleting the old database entirely. This could depend greatly on the size of your data and how much downtime you're willing to perform. An efficient and robust implementation of this would import to a staging database (and verify there were no import problems) before moving the tables to the "correct" database.
If you are simply referring to schema changes or very small amounts of data, then probably version control is your best bet. This is what I do for some of my database schemas; basically you start out with the base schema, then any change gets written as a script that can be run incrementally. So for instance, in an inventory system I might have originally started with a customer table, with fields for ID and name. Later I added a marketing department, and they want me to get email addresses. 2-email.sql would be this line: ALTER TABLE `customer` ADD `email` VARCHAR(255) NOT NULL AFTER `name`;. Still later, if I decide to handle shipping, I'll need to add mailing addresses, so 3-address.sql adds that to the database. Then on the other end, I just run those through a script (bonus points are awarded for using MySQL logic such as "IF NOT EXISTS" so the script can run as many times as needed without error).
Finally, you might benefit from setting up a replication system. Your staging database would automatically send all changes to the production database. Depending on your development process, this can be quite useful or might just get in the way.
I am looking into migrating my MySQL DB to Azure Database for MySQL https://azure.microsoft.com/en-us/services/mysql/. It currently resides on a server hosted by another company. The DB is about 100 GB. (It worries me that Azure uses the term "relatively large" for 1GB.)
Is there a way to migrate the DB without any or little (a few hours, max) downtime? I obviously can't do a dump and load as the downtime could be days. Their documentation seems to be for syncing with a MySQL server that is already on a MS server.
Is there a way to export the data out of MS Azure if I later want to use something else, again without significant downtime?
Another approach: Use Azure Data Factory to copy the data from your MySQL source to your Azure DB. Set up a sync procedure that updates your Azure Database with new rows. Sync, take MYSQL db offline, sync once more and switch to the Azure DB.
See Microsoft online help
Don't underestimate the complexity of this migration.
With 100GB, it's a good guess that most rows in your tables don't get UPDATEd or DELETEd.
For my suggestion here to work, you will need a way to
SELECT * FROM table WHERE (the rows are new or updated since a certain date)
Some INSERT-only tables will have autoincrementing ID values. In this case you can figure out the ID cutoff value between old and new. Other tables may be UPDATEd. Unless those table have timestamps saying when they were updated, you'll have a challenge figuring it out. You need to understand your data to do that. It's OK if your WHERE (new or updated) operation takes some extra rows that are older. It's NOT OK if it misses INSERTed or UPDATEd rows.
Once you know how to do this for each large table, you can start migrating.
Mass Migration Keeping your old system online and active, you can use mysqldump to migrate your data to the new server. You can take as long as you require to do it. Read this for some suggestions. getting Lost connection to mysql when using mysqldump even with max_allowed_packet parameter
Then, you'll have a stale copy of the data on the new server. Make sure the indexes are correctly built. You may want to use OPTIMIZE TABLE on the newly loaded tables.
Update Migration You can then use your WHERE (the rows are new or updated) queries to migrate the rows that have changed since you migrated the whole table. Again, you can take as long as you want to do this, keeping your old system online. It should take much less time than your first migration, because it will handle far fewer rows.
Final Migration, offline Finally, you can take your system offline and migrate the remaining rows, the ones that changed since your last migration. And migrate your small tables in their entirety, again. Then start your new system.
Yeah but, you say, how will I know I did it right?
For best results, you should script your migration steps, and use the scripts. That way your final migration step will go quickly.
You could rehearse this process on a local server on your premises. While 100GiB is big for a database, it's not an outrageous amount of disk space on a desktop or server-room machine.
Save the very large extracted files from your mass migration step so you can re-use them when you flub your first attempts to load them. That way you'll save the repeated extraction load on your old system.
You should stand up a staging copy of your migrated database (at your new cloud provider) and test it with a staging copy of your application. You may be able to do this with a small subset of your rows. But do test your final migration step with this copy to make sure it works.
Be prepared for a fast rollback to the old system if the new one goes wrong .
AND, maybe this is an opportunity to purge out some old data before you migrate. This kind of migration is difficult enough that you could make a business case for extracting and then deleting old rows from your old server, before you start migrating.
How should you go about restoring (and backing) up a MySQL database "safely"? By "safely" I mean: the restore should create/overwrite a desired database, but not risk altering anything outside that database.
I have already read https://dev.mysql.com/doc/refman/5.7/en/backup-types.html.
I have external users. They & I may want to exchange backups for restore. We do not have a commercial MySQL Enterprise Backup, and are not looking for a third-party commercial offering.
In Microsoft SQL Server there are BACKUP and RESTORE commands. BACKUP creates a file containing just the database you want; both its rows and all its schema/structure are included. RESTORE accepts such a file, and creates or overwrites its structure. The user can restore to a same-named database, or specify a different database name. This kind of behaviour is just what I am looking for.
In MySQL I have come across 3 possibilities:
Most people seem to use mysqldump to create a "dump file", and mysql to read that back in. The dump file contains a list of arbitrary MySQL statements, which are simply executed by mysql. This is quite unacceptable: the file could contain any SQL statements. (Limiting access rights of restoring user to try to ensure it cannot do anything "naughty" is not acceptable.) There is also the issue that the user may have created the dump file with the "Include CREATE Schema" option (MySQL Workbench), which hard-codes the original database name for recreation. This "dump" approach is totally unsuitable to me, and I find it surprising that anyone would use it in a production environment.
I have come across MySQL's SELECT ... INTO OUTFILE and LOAD DATA INFILE statements. At least they do not contain SQL code to execute. However, they look like a lot of work, deal with a table at time not the whole database, and don't deal with the structure of the tables, you have to know that yourself for restoring. There is a mysqlimport helper command-line utility, but I don't see anything for the export side, and I don't see it for restoring a complete database.
The last is to use what MySQL refers to as "Physical (Raw)" rather than "Logical" Backups. This works on the database directories and files themselves. It is the equivalent of SQL Server's detach/attach method for backing up/restoring. But, as per https://dev.mysql.com/doc/refman/5.7/en/backup-types.html, it has all sorts of caveats, e.g. "Backups are portable only to other machines that have identical or similar hardware characteristics." (I have no idea, e.g. some users are Windows versus Windows, I have no idea about their architecture) and "Backups can be performed while the MySQL server is not running. If the server is running, it is necessary to perform appropriate locking so that the server does not change database contents during the backup." (let alone restores).
So can anything satisfy (what I regard as) my modest requirements, as outlined above, for MySQL backup/restore? Am I really the only person who finds the above 3 as the only, yet unacceptable, possible solutions?
1 - mysqldump - I use this quite a bit, usually in environments where I am handling all the details myself. I do have one configuration where I use that to send copies of a development database - to be dumped/restored in its entirety - to other developers. It is probably the fastest solution, has some reasonable configuration options (e.g., to include/exclude specific tables) and generates very functional SQL code (e.g., each INSERT batch is small enough to avoid locking/speed issues). For a "replace entire database" or "replace key tables in a specific database" solution, it works very well. I am not too concerned about the "arbitrary SQL commands" problem - if that is an issue then you likely have other issues with users trying to "do their own thing".
2 - SELECT ... INTO OUTFILE and LOAD DATA INFILE - The problem with these is that if you have any really big tables then the LOAD DATA INFILE statement can cause problems because it is trying to load everything all at once. You also have to add code to create (if needed) or empty the tables before LOAD DATA.
3 - Physical (raw) file transfer. This can work but under limited circumstances. I had one situation with a multi-gigabyte database and decided to compress the raw files, move them to the new machine, uncompress and just tell MySQL "everything is already there". It mostly worked well. But I would not recommend it for any unattended/end-user process due to the MANY possible problems.
What do I recommend?
1 - mysqldump - live with its limitations and risks, set up a script to call mysqldump and compress the file (I am pretty sure there are options in mysqldump to do the compression automatically), include the date in the file name so that there is less confusion as the files are sent around, and make a simple script for users to load the file.
2 - Write your own program. I have done this a few times. This is more work initially but allows you to control every aspect of the process and transfer a file that only contains data without any actual SQL code. You can control the specific database, tables, etc. One catch is that if you make any changes to the table structure, indexes, etc. you will need to make sure that information is somehow transmitted to the receiving problem so that it can change the structures as needed - that is not a problem with mysqldump as it normally replaces the tables, creating the new structures, indexes, etc. This can be written in any language that can connect to MySQL - it does not have to be the same language as your application.
If you're not going to use third party tools (like innobackupex for example) then you're limited to use ... mysqldump, which is in the mysql package.
I can't understand why it is not acceptable for you, why you don't like sql commands in those dumps. Best practice,when restoring a single db into the server, which already contains other databases, is to have a separated user, with rights only to write into the restored db. Then even if the user performing restore, would change the sql commands and tried to write to another db, they will not be able to.
When doing raw backup (physical copy of database files) you need to have all the instances down, mysql server not running. Similar hardware means you need to have the same directories as the source server (unless you would change my.cnf before starting the server, and putting all the files to right directories).
When coming into mysql, try to not compare it to sql server - it's totally different approach and philosophy.
But if you would convinced yourself anyhow to use third party tool - I recommend innobackex from Percona, which is free btw.
The export tool that complements mysqlimport is mysqldump --tab. This outputs CSV files like SELECT...INTO OUTFILE. It also outputs the table structure in much smaller .sql files. So there are two files for each table.
Once you recreate your tables from the .sql files, you can use mysqlimport to import all the data files. You can even use the mysqlimport --use-threads option to make it load multiple data files in parallel.
This way you have more control over which schema to load the data into, and it should run a lot faster than loading a large SQL dump.
I'm working on a group project where we all have a mysql database working on a local machine. The table mainly has filenames and stats used for image processing. We all will run some processing, which updates the database locally with results.
I want to know what the best way is to update everyone else's database, once someone has changed theirs.
My idea is to perform a mysqldump after each processing run, and let that file be tracked by git (which we use religiously). I've written a bunch of python utils for the database, and it would be simple enough to read this dump into the database when we detect that the db is behind. I don't really want to do this though, less it clog up our git repo with unnecessary 10-50Mb files with every commit.
Does anyone know a better way to do this?
*I'll also note that we are Aerospace students. I have some DB experience, but it only comes out of need. We're busy and I'm not looking to become an IT networking guru. Just want to keep it hands off for them since they are DB noobs and get the glazed over look of fear whenever I tell them to do anything with the database. I made it hands off for them thus far.
You might want to consider following the Rails-style database migration concept, whereby as you are developing you provide roll-forward and roll-back SQL statements that work as patches, allowing you to roll your database to any particular revision state that is required.
Of course, this is typically meant for dealing with schema changes only (i.e. you don't worry about revisioning data that might be dynamically populated into tables.). For configuration tables or similar tables that are basically static in content, you can certainly add migrations as well.
A Google search for "rails migrations for python" turned up a number of results, including the following tool:
http://pypi.python.org/pypi/simple-db-migrate
I would suggest to create a DEV MySQL server on any shared hosting. (No DB experience is required).
Allow remote access to this server. (again, no experience is required, everything could be done through Control Panel)
And you and your group of developers will have access to the database at any time from any place and from any device. (As long as you have internet connection)
Background info:
We are currently 3 web programmers (good, real-life friends, no distrust issues).
Each programmers SSH into the single Linux server, where the code resides, under their own username with sudo powers.
We all use work on the different files at one time. We ask the question "Are you in the file __?" sometimes. We use Vim so we know if the file is opened or not.
Our development code (no production yet) resides in /var/www/
Our remote repo is hosted on bitbucket.
I am *very* new to Git. I used subversion before but I was basically spoon-fed instructions and was told exactly what to type to sync up codes and commit.
I read about half of Scott Chacon's Pro Git and that's the extent to most of my Git knowledge.
In case it matters, we run Ubuntu 11.04, Apache 2.2.17, and Git 1.7.4.1.
So Jan Hudec gave me some advice in the previous question. He told me that a good practice to do the following:
Each developer have their own repo on their local computer.
Let the /var/www/ be the repo on the server. Set the .git folder to permission 770.
That would mean that each developer's computer need to have their own LAMP stack (or at least Apache, PHP, MySQL, and Python installed).
The codes are mostly JavaScript and PHP files so it's not a big deal to clone it over. However how do we locally manage the database?
In this case, we only have two tables and it'll be simple to recreate the entire database locally (at least for testing). But in the future when the database gets too big, then should we just remotely log on the MySQL database on the server or should we just have a "sample" data for developing and testing purposes?
What you're doing is transitioning from "everybody works together in one environment" to "everybody has their own development environment". The major benefit is everybody won't be stepping on each other's feet.
Other benefits include a heterogeneous development environment, that is if everyone is developing on the same machine the software will become dependent on that one setup because developers are lazy. If everyone develops in different environments, even just with slightly different versions of the same stuff, they'll be forced to write more robust code to deal with that.
The main drawback, as you've noticed, is setting up the environment is harder. In particular, making sure the database works.
First, each developer should have their own database. This doesn't mean they all have to have their own database server (though its good for heterogeneous purposes) but they should have their own database instance which they control.
Second, you should have a schema and not just whatever's in the database. It should be in a version controlled file.
Third, setting up a fresh database should be automatic. This lets developers set up a clean database with no hassle.
Fourth, you'll need to get interesting test data into that database. Here's where things get interesting...
You have several routes to do that.
First is to make a dump of an existing database which contains realistic data, sanitized of course. This is easy, and provides realistic data, but it is very brittle. Developers will have to hunt around to find interesting data to do their testing. That data may change in the next dump, breaking their tests. Or it just might not exist at all.
Second is to write "test fixtures". Basically each test populates the database with the test data it needs. This has the benefit of allowing the developer to get precisely the data they want, and know precisely the state the database is in. The drawbacks are that it can be very time consuming, and often the data is too clean. The data will not contain all the gritty real data that can cause real bugs.
Third is to not access the database at all and instead "mock" all the database calls. You trick all the methods which normally query a database into instead returning testing data. This is much like writing test fixtures, and has most of the same drawbacks and benefits, but it's FAR more invasive. It will be difficult to do unless your system has been designed to do it. It also never actually tests if your database calls work.
Finally, you can build up a set of libraries which generate semi-random data for you. I call this "The Sims Technique" after the video game where you create fake families, torture them and then throw them away. For example, lets say you have User object who needs a name, an age, a Payment object and a Session object. To test a User you might want users with different names, ages, ability to pay and login status. To control all that you need to generate test data for names, ages, Payments and Sessions. So you write a function to generate names and one to generate ages. These can be as simple as picking randomly from a list. Then you write one to make you a Payment object and one a Session object. By default, all the attributes will be random, but valid... unless you specify otherwise. For example...
# Generate a random login session, but guarantee that it's logged in.
session = Session.sim( logged_in = true )
Then you can use this to put together an interesting User.
# A user who is logged in but has an invalid Visa card
# Their name and age will be random but valid
user = User.sim(
session = Session.sim( logged_in = true ),
payment = Payment.sim( invalid = true, type = "Visa" ),
);
This has all the advantages of test fixtures, but since some of the data is unpredictable it has some of the advantages of real data. Adding "interesting" data to your default sim and rand functions will have wide ranging repercussions. For example, adding a Unicode name to random_name will likely discover all sorts of interesting bugs! It unfortunately is expensive and time consuming to build up.
There you have it. Unfortunately there's no easy answer to the database problem, but I implore you to not simply copy the production database as it's a losing proposition in the long run. You'll likely do a hybrid of all the choices: copying, fixtures, mocking, semi-random data.
A few options, in order of increasing complexity:
You all connect to the live master DB, read/write permissions. This is risky, but I guess you're already doing it. Make sure you have backups!
Use test fixtures to populate a local test DB and just use it. Not sure what tools there are for this in the PHP world.
Copy (mysqldump) the master database and import it into your local machines' MySQL instances, then set up your dev environments to connect to your local MySQL. Repeat the dump/import as necessary
Set up one-way replication from the master to your local instances.
Optionally, set up a read-only user on the main DB, and configure your app to let you switch to a read-only connection to the real master DB in case you can't wait for that next copy of the master data.
Own repo does not mean own Staging server (this config is hardly maintained and extremely bad scaled to 10-20-100 developers)
It's always better to have as soon as possible (semi-)automated build-system, which convert repository-stored source-data to live system (less handwork - less changes to make non-code errors) and (maybe) some type of Continuos Integration (test often, find bugs fast). For build-system (DB-part) you have only to prepare initial data (tables structures, data-dumps) as (versioned) texts, which are
easy mergeable between merges
handled and processed and converted to final usable object by code, not by hand - no human errors, no operation's interferences