Schema Patches Practices - postgresql

We've got a schema in Postgres, and we want to institute a good method to apply schema patches.
Currently, we have a series of DDL files that create the schema, tables, sequences, functions, etc. We also have a population script for test environments. Those files are all used to recreate our database environments, for development, testing, etc.
We also have a number of 'patch' files that correspond to versions of our system. ie. patches/1.0.0.sql, patches/1.0.1.sql, etc. These files are used to update our staging and production databases.
This process works for us so far, but there has been some debate in-house how to best patch the schema.
I'm curious what others out there have, as a process, to patch staging and production schema's and how to manage versions of the database.
Thanks!

At work, for SQL Server, we write schema change scripts that first roll back the change to be made (idempotently, so the rollback section runs fine even if the schema change isn't applied yet), and then a section to apply the change. In TSQL it's easy to peek in the system catalogue or other tables to see if tables/columns/indices/rows already exist and do nothing if not.
In PostgreSQL, you're a bit more constrained with what commands you can simply send to the server-- but on the other hand, DDL is transactional, so a half-applied schema change shouldn't happen. I've adapted the scheme I'm used to at work to use on my own little projects quite well (overkill? but even here I have a dev/test db and a "real" db), for example:
\echo Rolling back schema change #35
BEGIN;
DELETE FROM schema_version WHERE schema_id = 35;
DROP TABLE IF EXISTS location_coordinates;
DROP FUNCTION IF EXISTS location_coordinates_populate();
END;
\echo Applying schema change #35
BEGIN;
INSERT INTO schema_version(schema_id, description) VALUES(35, 'Add location_coordinates table');
CREATE TABLE location_coordinates(
location_id INT PRIMARY KEY REFERENCES location(location_id),
latitude FLOAT NOT NULL,
longitude FLOAT NOT NULL,
earth_coordinates earth NOT NULL,
box_10miles cube NOT NULL
);
GRANT SELECT, INSERT, UPDATE, DELETE ON location_coordinates TO ui;
CREATE FUNCTION location_coordinates_populate() RETURNS TRIGGER LANGUAGE 'plpgsql' AS $$
BEGIN
new.earth_coordinates := ll_to_earth(new.latitude, new.longitude);
new.box_10miles := earth_box(new.earth_coordinates, 10 * 1609.344);
RETURN new;
END
$$;
CREATE TRIGGER location_coordinates_populate BEFORE INSERT OR UPDATE ON location_coordinates
FOR EACH ROW EXECUTE PROCEDURE location_coordinates_populate();
INSERT INTO location_coordinates(location_id, latitude, longitude)
SELECT location_id, latitude, longitude FROM location WHERE latitude IS NOT NULL AND longitude IS NOT NULL;
CREATE INDEX location_coordinates_10miles ON location_coordinates USING gist (box_10miles);
END;
\echo Done
This script can be run on the database just with "psql -f schema-changes/35.sql". By just cutting out up to the "applying..." message, I can get the commands to roll it back. And as you can see, the change maintains a metadata table "schema_version" so I can see which changes are applied. The entire change is done as a transaction, data migration and all. Here I've used the "IF EXISTS" capability of the DROP commands to make the rollback section happy even when the change is unapplied. Istr one thing we did at work for Oracle was write schema changes as PL/SQL-- you could perhaps have some functions in plpgsql to help with making changes?
Note that in the change above, where I'm migrating the "latitude" and "longitude" columns (which were nullable) out of "location" to a separate "location_coordinates" relation (and adding in the earthdistance stuff), I didn't drop the old columns. One thing we have to be careful of is to make schema changes backwards-compatible if possible. So I can apply this schema change before updating the app to use the new tables. I'd have a second change to drop the old columns to apply after updating the app. At work, these would be done in two different release cycles, so during release X we still have the optional of rolling back the app to release X-1 without having to roll back all the schema changes first; as well as being able to deploy schema changes in a separate window before the apps. (Technically I should have written a trigger so updates to the old table are synced to the new table, but I haven't because that's too much like work :))
We also have things like an application that spiders all our databases to see what's in the schema_version table, and tracks changes, so people can even see what changes were made without having to connect, and get an idea of the history of each change (we track "rolled back in dev", "applied in dev" etc). At work our schema_version table also includes authorship information etc. A magic way of applying the version information from version control would be cool- one problem we have is that if a SC gets applied in QA, for instance, then changed in Perforce, maybe no-one notices. So a way to track that schema change 35 revision #4 was applied would be good.
One thing to note- schema changes for us are numbered independently of application versions. Obviously they are related--- that's another thing the spidering app allows people to enter--- but we try to have lots of small changes rather than a giant "here's everything for release X" patch. Schema changes are also used for things like adding new indices, so might not be app-driven at all. In general, schema changes are "owned" by developers, not DBAs- although in the "create index" example above, the DBA is basically acting in a developer role and owning the schema change. Yes, we insist on a high level of SQL-ability from developers- although other groups in the company work a bit differently and give more work to the DB team.

Related

Migrating `int` to `bigint` in PostgresSQL without any downtime?

I have a database that is going to experience the integer exhaustion problem that Basecamp famously faced back in November. I have several months to figure out what to do.
Is there a no-downtime-required, proactive solution to migrating this column type? If so what is it? If not, is it just a matter of eating the downtime and migrating the column when I can?
Is this article sufficient, assuming I have several days/weeks to perform the migration now before I'm forced to do it when I run out of ids?
Use logical replication.
With logical replication you can have different data types at primary and standby.
Copy the schema with pg_dump -s, change the data types on the copy and then start logical replication.
Once all data is copied over, switch the application to use the standby.
For zero down time, the application has to be able to reconnect and retry, but that's always a requirement in such a case.
You need PostgreSQL v10 or better for that, and your database
shouldn't modify the schema, as DDL is not replicated.
should not use sequence (SERIAL or IDENTITY), as the last used value would not be replicated
Another solution for pre-v10 databases where all transactions are short:
Add a bigint column to the table.
Create a BEFORE trigger that sets the new column whenever a row is added or updated.
Run a series of updates that set the new column from the old one where it IS NULL. Keep those batches short so you don't lock long and don't deadlock much. Make sure these transaction run with session_replication_role = replica so they don't trigger triggers.
Once all rows are updated, create a unique index CONCURRENTLY on the new column.
Add a unique constraint USING the index you just created. That will be fast.
Perform the switch:
BEGIN;
ALTER TABLE ... DROP oldcol;
ALTER TABLE ... ALTER newcol RENAME TO oldcol;
COMMIT;
That will be fast.
Your new column has no NOT NULL set. This cannot be done without a long invasive lock. But you can add a check constraint IS NOT NULL and create it NOT VALID. That is good enough, and you can later validate it without disruptions.
If there are foreign key constraints, things get a little more complicated. You have to drop these and create NOT VALID foreign keys to the new column.
Create a copy of the old table but with modified ID field. Next create a trigger on the old table that inserts new data to both tables. Finally copy data from the old table to the new one (it would be a good idea to distinguish pre-trigger data with post-trigger for example by id if it is sequential). Once you are done switch tables and delete the old one.
This obviously requires twice as much space (and time for copy) but will work without any downtime.

Is it possible to have database-wide table aliases?

I am about to model a PostgreSQL database, based on an Oracle database. The latter is old and its tables have been named after a 3-letter-scheme.
E.g. a table that holds parameters for tasks would be named TSK_PAR.
As I model the new database, I'd like to rename those tables to a more descriptive name using actual words. My problem is, that some parts of the software might rely on these old names until they're rewritten and adapted to the new scheme.
Is it possible to create something like an alias that's being used for the whole database?
E.g. I create a new task_parameters database, but add a TSK_PAR alias to it, so if a SELECT * FROM TSK_PAR is being used, it automatically refers to the new name?
Postgres has no synonyms like Oracle.
But for your intended use case, views should do just fine. A view that simply does select * from taks_parameters is automatically updateable (see here for an online example).
If you don't want to clutter your default schema (usually public) with all those views, you can create them in a different schema, and then adjust the user's search path to include that "synonym schema".
For example:
create schema synonyms;
create table public.task_parameters (
id integer primary key,
....
);
create view synonyms.task_par
as
select *
from public.task_parameters;
However, that approach has one annoying drawback: if a table is used by a view, the allowed DDL statements on it are limited, e.g. you can't drop a column or rename it.
As we manage our schema migrations using Liquibase, we always drop all views before applying "normal" migrations, then once everything is done, we simply re-create all views (by running the SQL scripts stored in Git). With that approach, ALTER TABLE statements never fail because there are not views using the tables. As creating a view is really quick, it doesn't add overhead when deploying a migration.

Backup a table using pg_dump

I am new to PostgreSQL. I have a database name employee (id , name, address , Phonenumber , salary). I would like to make a backup of the employee details if anyone of Phno,addres and salary is changed.
Is there any way of doing it using pg_dump or I should be satisfied with trigger method that output original Tuples onto another Table say Backup if any changes are made .
Please , if someone could elaborate in detailed manner how to get start with this using pg_dump.
pg_dump scripts out the current state of the database. That's all it does, with some fine-tuning to let you get at individual tables, schemas, etc. It does not watch for changes, it does not work at the row level (barring some zany row-level security setup), and it is not an audit log.
What you're describing -- backing up individual rows when they're modified -- is an audit log, so pg_dump is the wrong tool for the job. An update trigger which inserts the original row into an audit table is the canonical way to accomplish this, so you're on the right track there. If you need to generate scripts of the audit table, that's where pg_dump comes in.

On INSERT to a table INSERT data in connected tables

I have two tables that have a column named id_user in common. These two tables are created in my Drupal webpage at some point (that I don't know because I didn't created the Netbeans project).
I checked on the internet and found that probably by adding REFERENCES 1sttable (id_user) to the second table, it should copy the value of the 1sttable (that is always created when a new user arrives) to the id_user value of the 2ndtable (that I don't know at which point is created). Is it correct?
If it's not correct I would like to know a way in pgAdmin that could make me synchronize those tables, or at least create both of them in the same moment.
The problem I have is that the new user has a new row on 1sttable automatically as soon as he registers, while to get a new row on 2ndtable it needs some kind of "activation" like inserting all of the data. What I'm looking for is a way that as soon as there is a new row in the 1sttable, it automatically creates the new row on the other table too. I don't know how to make it more clear (English is not my native language).
The solution you gave me seems clear for the question, but the problem is a little bigger: the two tables presents different kinds of variables, and it should be that they are, one in mySQL, with the user data (drupal default for users), then i have 2 in postgresql, both with the same primary key (id_user):
the first has 118 columns, most of them real integer;
the second has 50 columns, with mixed types.
the web application i'm using needs both this column with all the values NOT EMPTY (otherwise i get a NullPointerException) to work, so what i'm searching for is (i think):
when the user register -inserting his email- in drupal, automatically it creates the two fulfilled columns, to make the web automatically works as soon as the email is stored in mysql. Is it possible? Is it well explained?
My environment is:
windows server 2008 enterprise edition
glassfish 2.1
netbeans 6.7.1
drupal 6.17
postgresql 8.4
mysql 5.1.48
pgAdmin is just the GUI. You mean PostgreSQL, the RDBMS.
A foreign key constraint, like you have only enforces that no value can be used, that isn't present in the referenced column. You can use ON UPDATE CASCADE or ON DELETE CASCADE to propagate changes from the referenced column, but you cannot create new rows with it like you describe. You got the wrong tool.
What you describe could be achieved with a trigger. Another, more complex way would be a RULE. Go with a trigger here.
In PostgreSQL you need a trigger function, mostly using plpgsql, and a trigger on a table that makes use of it.
Something like:
CREATE OR REPLACE FUNCTION trg_insert_row_in_tbl2()
RETURNS trigger AS
$func$
BEGIN
INSERT INTO tbl2 (my_id, col1)
VALUES (NEW.my_id, NEW.col1) -- more columns?
RETURN NEW; -- doesn't matter much for AFTER trigger
END
$func$ LANGUAGE plpgsql;
And a trigger AFTER INSERT on tbl1:
CREATE TRIGGER insaft
AFTER INSERT ON tbl1
FOR EACH ROW EXECUTE PROCEDURE trg_insert_row_in_tbl2();
You might want to read about using Drupal hooks to add extra code to be run when a user is registered. Once you know how to use hooks, you can write code (in a module) to insert a corresponding record in the 2nd table. A good candidate hook to use here would be hook_user for Drupal 6 or hook_user_insert for Drupal 7.
The REFERENCES you read about is part of an SQL command to define a foreign key constraint from the second table to the first. This is not strictly necessary to solve your problem, but it can help in keeping your database consistent. I suggest you read up on database structures and constraints if you want to learn more on this topic.

Creating Stored Procedures that can work with different tables

I need to use the same Stored Procedures against many tables all with the same structure in my DB. This is data loaded from customers,with one table/customer and the data needs calculations/checks run before it's loaded to our DataWarehouse.
So far these are the options and issues I've found and I'm looking for a better pattern/approach.
Create a view that points to the
table I want to process, the SPs
then talk to that view. This works
well (especially once I'd worked out
how to create views 'automagically'
based on their columns). But the
view can only be used with one table
at a time, forcing the system to
deal with one customer at a time.
Use dynamic sql within each SP -
makes the SPs much harder to
read/debug and for those reasons has
been ruled out
Create a partitioned view across
all the tables and then use a
paramatised table function to return
just the data we're interested in -
ah but then I can't update the data
as the function returns a table that
can be only used for select
Use dynamic sql inside a function
(can't be done) to create a view
(which also can't be done) .... give
up
Within the SP create a temp table
with over the target table using
dynamic sql, but then the temp table
only exists in the session that runs
the dynamic sql not the 'parent'
session that's running the SP ...
give up
Create a global temp table using
dynamic SQL to avoid the scope issue
of 5, then run the SP against the
global temp table. Still run into
the single customer issue.
Create the view as in 1 within a
transaction and then run all the SPs
and then commit - works fine for one
user, but any others are now blocked
trying to create a new view of the
same name
Use a temporary view ... can't in
T/Sql
Move all the code into .Net - but
we have environment issues where
tsql is much easier to host/run
I know I'm not the only person who has this problem, have any of you good people solved it, please help.
Maybe your approach is wrong, I will go deep in details in a while but it seems that your problem can be solved using SSIS
-- Updated answer:
First, the big picture:
The most affordable way to process the tables dynamically is using a script instead of a stored procedure. If you want to make table access randomly chosen, you certainly will not use any of the performance advantages of stored procedures, i.e. execution plans. A SQL Script can be easily upgraded to point one table at runtime using placeholders and replacing it before executing.
The script can be loaded from the filesystem, a variable, a text column in a table, etc. The loading process consists in read the script content to a string variable. This step occurs once.
The next step is the preparation stage. This step will be executed for each table to be processed. The main business of this step is to replace the table placeholders with the current table being processed. Also is possible to set parameter values like any parameter you can need to pass into the sp that you already wrote.
The last step is the execution of the script. As is already loaded into a variable and the placeholders were set to the current table name, you can safely call a ExecuteSQLTask with the sql variable as the input. This process of course happens for each table you want to process.
Ok. Now let's see this in action.
This is a sample database model:
CREATE TABLE [dbo].[t_n](
[id] [int] IDENTITY(1,1) NOT NULL,
[name] [varchar](50) NOT NULL,
[start] [datetime] NULL,
CONSTRAINT [PK_t_n] PRIMARY KEY CLUSTERED ([id] ASC)
) ON [PRIMARY]
where t_n represents any table (t_1, t_2, t_3, etc).
This is your current stored procedure:
CREATE PROCEDURE SpProcessT_n
AS
BEGIN
SET NOCOUNT ON;
SELECT * FROM [t1];
END
GO
Now, transform this stored procedure to a Sql script, placing a placeholder instead of the table name
SET NOCOUNT ON;
SELECT * FROM [$table_name];
I choose to save this in a .sql file in the filesystem to keep the POC as simple as possible.
Next, create a SSIS Package like this:
These are the settings I choose to set up the loop:
And this is the way you can assign the table name to a variable called appropriately _table_name_
This is the setup of the script task, here you find that the variable _table_name_ has read only access, while a new variable called SqlExec has read/write access:
And this is it's Main function:
public void Main()
{
String Table_Name = Dts.Variables["table_name"].Value.ToString();
String SqlScript;
Regex reg = new Regex(#"\$table_name", RegexOptions.Compiled);
using (var f = File.OpenText(#"c:\sqlscript.sql")) {
SqlScript = f.ReadToEnd();
f.Close();
}
SqlScript = reg.Replace(SqlScript, Table_Name);
Dts.Variables["SqlExec"].Value = SqlScript;
Dts.TaskResult = (int)ScriptResults.Success;
}
You can notice that the Dts Variable SqlExec contains the sql script that will be executed. Now you can set the following options in your ExecuteSqlTask:
Successfully tested in MSSQL 2008, if you put a insert inside the script file you will notice new rows in each table.
Hope this helps!
If your application can afford to have one cut-off day late, then you can have a nightly scheduled job to run an SSIS package that will consolidate all 150+ tables into one single huge table. Since the freshness of the results of the queries against that huge table will then be 1 'date' late, this solution will not include any rows that recently been loaded.
You can actually time the running of this package. If it is still amazingly fast, say within 30 minutes, then you can bet to run it in every few hours, like during: the start of work day, lunch break, and end of day. This way you can have a nearly fresh data to query with.
Write a partitioned view including table names?
SELECT 'TableName', t.* FROM TableName t
UNION ALL
SELECT 'TableName2', t.* FROM TableName2 t
Then write a single instead of trigger which uses dynamic SQL for writing (less testing involved with that use of dynamic SQL because you'd just write the simple CRUD operations once for all tables I'd think)
I would not do this with SQL. What you are describing sounds like a traditional ETL situation.
Since all of the customer tables are the same, I would create a table in the data warehouse with all the columns from the client table, a surrogate key column, and a type identifier. You have an option to create a "staging" table here that will only have data in it during the ETL process, or just working on a single "live" table. I would create the staging table.
Then within SSIS package (don't worry you can still schedule from SQL Server agent, it hasn't totally left the DB server), start the ETL process...
E(xtract): copy the data from your source into the staging table in the data warehouse. You most likely want to use a sub-package within a foreach loop and changing the name of the table that you want to process from an external store (most people would say put this in the warehouse, but its up to you).
T(ransform): run the calculations/checks you were talking about, but do it on the whole set...
L(oad): Copy it to your real within the data warehouse.
There are a couple things I would NOT do.
1. Modify the data in the source table.
2. Try to do this in t-sql. Its just not what tsql is good at.
If you need more detail on this approach, I would probably ask the question with some Business Intelligence tags. I'll be traveling for the next week or so, but I will try to look at the comments to clear anything up if you need me to.
I am fairly certain that the standard way to solve this is using dynamic SQL in each sp (your option 2), which has already been ruled out.
Your goal is to make generic, multi-table SQL. I don't see how you intend to accomplish that without sacrificing some efficiency and readability.