May
13
2019
--

PostgreSQL Minor Versions Released May 9, 2019

PostgreSQL Logo

Usually, the PostgreSQL Community releases minor patches on the Thursday of the second week of the second month of each quarter. This can vary depending on the nature of the fixes. For example, if the fixes include critical fixes as a postgres community response to security vulnerabilities or bugs that might affect data integrity. The previous minor release happened on February 14, 2019. In this case, the fysnc failure issue was corrected, along with some other enhancements and fixes.

The latest minor release, published on May 9, 2019, has some security fixes and bug fixes for these PostgreSQL Major versions.

PostgreSQL 11 (11.3)
PostgreSQL 10 (10.8)
PostgreSQL 9.6 (9.6.13)
PostgreSQL 9.5 (9.5.17)
PostgreSQL 9.4 (9.4.22)

Let’s take a look at some of the security fixes in this release.

Security Fixes

CVE-2019-10130 (Applicable to PostgreSQL 9.5, 9.6, 10 and 11 versions)

When you

ANALYZE

a table in PostgreSQL, statistics of all the database objects are stored in

pg_statistic

. The query planner uses this statistical data is and it may contain some sensitive data, for example, min and max values of a column. Some of the planner’s selectivity estimators apply user-defined operators to values found in

pg_statistic

. There was a security fix :

CVE-2017-7484

in the past, that restricted a leaky user-defined operator from disclosing some of the entries of a data column.

Starting from PostgreSQL 9.5, tables in PostgreSQL not only have SQL-standard privilege system but also row security policies. To keep it short and simple, you can restrict a user so that they can only access specific rows of a table. We call this RLS (Row-Level Security).

CVE-2019-10130

is about restricting a user who has SQL permissions to read a column but is forbidden to read some rows due to RLS policy from discovering the restricted rows through a leaky operator. Through this patch, leaky operators to statistical data are only allowed when there is no relevant

RLS

policy. We shall see more about

RLS

in our future blog posts.

CVE-2019-10129 (Applicable to PostgreSQL 11 only)

This fixes the situation where a user could access arbitrary back end memory with correctly crafted DDLs. This is only applicable to PostgreSQL 11 version and no other major release has been impacted.

Fixes roundup

There have been a good number of fixes around partitioning in both PostgreSQL 10 and 11 versions that included a fix to behaviour of an UPDATE or an INSERT on certain scenarios, failure while ALTER INDEX .. ATTACH PARTITION, tuple routing in multi-level partitioned tables that have dropped attributes. etc. .

We should also mention a couple of interesting bugs addressed in this new release.

Bug # 15631 is about the catalog corruption when a temporary table on commit drop is created with an identity column. Due to this issue, PostgreSQL 11.1 would not allow the creation of temporary tables, and you might have observed this error message prior to this release:

# create temporary table foo ( bar int generated by default as identity ) on
# commit drop;
# CREATE TABLE
# \q
# psql postgres postgres
# create temporary table a (b varchar);
ERROR: could not open relation with OID 16388
LINE 1: create temporary table a (b varchar);

Another bug that got fixed is Bug # 15734 which is about a

Walsender

process crashing when executing

SHOW ALL

using replication protocol.

Some more fixes include:

1. Fix

CREATE VIEW

to allow zero-column views.
2. Add missing support for the

CREATE TABLE IF NOT EXISTS .. AS EXECUTE

  .. statement.
3. Fix incompatibility of GIN-index WAL records that were introduced in 11.2, 10.7, 9.6.12, 9.5.16, and 9.4.21 that affected replica servers running these versions reading in changes to GIN indexes from primary servers of older versions.
4. Make

pg_verify_checksums

verify that the data directory it’s pointed at is of the right PostgreSQL version.
5. Fixes for

postgres_fdw

where an

UPDATE

could lead to incorrect results or a crash.
6. Several memory leak fixes as well as fixes to management of dynamic shared memory.

The postgres community have fixed more than just the bug fixes and enhancements we’ve highlighted. We would recommend you to go through the release notes, which you can access by clicking the appropriate release in the beginning of this blog post. Let us know if you have any specific questions you’d like us to address.

Applying updates

We always recommend that you keep your PostgreSQL databases updated to the latest minor versions. Be aware that applying a minor release might need a restart after updating the new binaries.

Here is the sequence of steps you should follow to upgrade to the latest minor versions after thorough testing :

1. Shutdown the PostgreSQL database server
2. Install the updated binaries
3. Restart your PostgreSQL database server

Most of the time, you can choose to update the minor versions in a rolling fashion in a master-slave (replication) setup, because it avoids downtime for both reads and writes simultaneously. PostgreSQL logoFor a rolling style update, you could perform the update on one server after another. However, the best method that we’d almost always recommend is – shutdown, update and restart all instances at once.

If you are currently running your databases on PostgreSQL 9.3.x or earlier, we recommend that you to prepare a plan to upgrade your PostgreSQL databases to a supported version ASAP. We’ve previously published some blog posts about the various options for upgrading your PostgreSQL databases to a supported major version, and you can read our post archive here. Please subscribe to our blog posts so that you can see more interesting topics around PostgreSQL.

And don’t forget that at Percona Live in Austin, May 28-30 2019, we’ll have two days of PostgreSQL content in a postgres dedicated track. Please see all our PostgreSQL talks here.

Apr
12
2019
--

Fast Upgrade of Legacy PostgreSQL with Minimum Downtime Using pg_upgrade

pg_upgrade to upgrade postgresql

PostgreSQL logoWhen you need to upgrade your PostgreSQL databases, there are a number of options available to you. In this post we’ll take a look at how you can upgrade PostgreSQL versions using pg_upgrade, a built-in tool that allows in-place upgrade of your software. Using pg_upgrade allows you, potentially, to minimize your downtime, an essential consideration for many organizations. It also allows you to perform a postgres upgrade with very minimal effort.

In our previous posts, we discussed various methods and tools that can help us perform a PostgreSQL upgrade – (1) pg_dumpall, (2) pg_dump and pg_restore with pg_dumpall, (3) logical replication and pglogical, and (4) slony. Methods 1 and 2 can involve additional downtime compared to the approaches taken in 3 and 4. Whilst performing an upgrade using logical replication or slony may be time consuming and require a lot of monitoring, it can be worth it if you can minimize downtime. If you have large databases that are busy with a lot of transactions, you may be better served using logical replication or slony.

This post is the fifth of our Upgrading or Migrating Your Legacy PostgreSQL to Newer PostgreSQL Versions series. These posts lead up to a live webinar, where we’ll be exploring different methods available to upgrade your PostgreSQL databases. If it’s beyond the live webinar date when you read this, you’ll find the recording at that same link.

pg_upgrade

pg_upgrade (formerly pg_migrator – until PostgreSQL 8.4) is a built-in tool that helps in upgrading a legacy PostgreSQL server to a newer version without the need of a dump and restore. The oldest version from when you can upgrade your PostgreSQL using pg_upgrade is 8.4.x. It is capable of performing faster upgrades by taking into consideration that system tables are the ones that undergo the most change between two major versions. The internal data storage format is less often affected.

In fact, in one of our tests we were able to perform an upgrade of a 2 TB database server from PostgreSQL 9.6.5 to 11.1 in less than 10 seconds. Now that is fast!

Overview of the process

To understand how it works, consider a PostgreSQL server running on 9.3.3 that needs to upgrade to PostgreSQL 11. You should install the latest binaries for your new PostgreSQL version on the server – let’s say PostgreSQL 11.2 – before you begin the upgrade process.

Preparation and consistency checks

Once you have installed the new PostgreSQL version, initialize a new data directory using the new binaries and start it on another port i.e. a different port to the one used by PostgreSQL 9.3.3, in our example. Use pg_upgrade to perform consistency checks between the two servers – PG 9.3.3 and PG 11.2 – running on two different ports. If you get any errors, such as a missing extension, you need to to fix these before you proceeding to the upgrade. Once the consistency check has been passed, you can proceed.

Here is how the log looks if you should get an error while performing consistency checks.

$ /usr/pgsql-11/bin/pg_upgrade -b /usr/pgsql-9.3/bin -B /usr/pgsql-11/bin -d /var/lib/pgsql/9.3/data -D /var/lib/pgsql/11/data_new -c
Performing Consistency Checks on Old Live Server
------------------------------------------------
Checking cluster versions                                   ok
Checking database user is the install user                  ok
Checking database connection settings                       ok
Checking for prepared transactions                          ok
Checking for reg* data types in user tables                 ok
Checking for contrib/isn with bigint-passing mismatch       ok
Checking for invalid "unknown" user columns                 ok
Checking for hash indexes                                   ok
Checking for roles starting with "pg_"                      ok
Checking for incompatible "line" data type                  ok
Checking for presence of required libraries                 fatal
Your installation references loadable libraries that are missing from the
new installation.  You can add these libraries to the new installation,
or remove the functions using them from the old installation.  A list of
problem libraries is in the file:
    loadable_libraries.txt
Failure, exiting
$ cat loadable_libraries.txt
could not load library "$libdir/pg_repack": ERROR:  could not access file "$libdir/pg_repack": No such file or directory

To proceed beyond the error, in this example you’d need to install this missing extension pg_repack for the new PostgreSQL version, and rerun the check to make sure that you receive no errors and all the checks are passed.

Carrying out the upgrade

Once passed, you can proceed in one of two ways. One option is to let pg_upgrade copy the datafiles of the old data directory to the new data directory initialized by the new PostgreSQL version. The second option is to let pg_upgrade use hard links instead of copying data files. Copying a database of several terabytes may be time consuming. Using the hard links method makes the process really quick as it does not involve copying files.

To use hard links with pg_upgrade, you pass an additional argument -k as you can see in the following command.

$ /usr/pgsql-11/bin/pg_upgrade -b /usr/pgsql-9.3/bin -B /usr/pgsql-11/bin -d /var/lib/pgsql/9.3/data -D /var/lib/pgsql/11/data_new -k

In the Unix file system, a file or a directory is a link to an inode (index node) that stores metadata (disk block location, attributes, etc) of the data stored in them. Each inode is identified by an integer or an inode number. When you use pg_upgrade with hard links, it internally creates another file/directory in the new data directory that links to the same inode as it was in the older data directory for that file/directory. So, it skips the physical copy of the objects, but creates each object and links them to the same inode.

This reduces the disk IO and avoids the need for additional space in the server. An important point to note is that this option works only when you are upgrading your PostgreSQL on the same file system. This means, for example, if you want to upgrade to a new or a faster disk during the database upgrade, the hard link option does not work. In that case, you would need to use the file copy method.

So far, we have seen a high level overview of how pg_upgrade with hard links help you to perform an upgrade with lowest possible downtime. Come see more in action during our Webinar.  And don’t forget at Percona Live in Austin, May 28-30 2019, we’ll have two days of PostgreSQL content in a postgres dedicated track.


Elephant image based on photo from Pexels

Apr
09
2019
--

Continuous Replication From a Legacy PostgreSQL Version to a Newer Version Using Slony

Native streaming replication in PostgreSQL works only between servers running the same major version. We discussed about logical replication in our previous blog post. In that post, we saw how logical replication could help us set up migration between two different PostgreSQL versions. However, logical replication works only for the currently supported versions of PostgreSQL, for example between PostgreSQL 9.4 and PostgreSQL 11. So what about the legacy versions that are older than 9.4? Slony-I could help us meet this replication requirement.

Replication between different PostgreSQL versions with Slony-I is useful for migration from legacy database installations to the latest available version. So what is Slony and how does it work?

This post is the fourth of our Upgrading or Migrating Your Legacy PostgreSQL to Newer PostgreSQL Versions series where we’ll be exploring different methods available to upgrade your PostgreSQL databases.

Slony

Slony is an application-level logical replication implementation for PostgreSQL. Rather, we could say that it is an external replication tool that requires a separate installation and configuration. Slony has been around for a long time. The latest version supports PostgreSQL versions from 8.4 and up to 11.

PostgreSQL logoThe main goal for replication is to ship changes from one database server to another. To better understand the architecture, you should know the terms such as Slon, Events and Slonik in Slony-I.

An aside: Slony means elephants in Russian, and elephants are indeed reputed to have a great memory. A slightly angry, but nevertheless pretty elephant, “Slonik”, looks at you from the PostgreSQL logo image.

Slon

Slon is a daemon that runs on each PostgreSQL node in Slony-I replication. These daemons are used for processing configuration and replication events for each PostgreSQL server. Each PostgreSQL server is called a “node”. All nodes together form a Slony “cluster”.

The “publisher node” is a source for replicated changes. While “subscriber” nodes receive and apply changes from the publisher node.

In order to setup replication, we should specify all replicated tables or “set”. Actual subscription works within a specific set. Changes to the tables being replicated are grouped together into SYNCs. These group of transactions are applied together to the subscriber nodes.

Events

Changes are transferred from the publisher in the form of “events”. When an event is processed by the slon daemon on a remote node, it generates a “confirmation”. Events are also used to notify nodes about configuration changes like adding/removing new nodes, new subscriptions or DDL changes.

Each event has a unique origin identifier, sequence number, transaction id for the snapshot on provider node for this event, multiple arguments, and timestamp with timezone.

Triggers written in PL/pgSQL register all changes in replicated tables. Unfortunately, there is no reliable way yet to handle changes to large objects (BLOBS), DDLs, or changes to users and roles.

slonik

Slonik means a little elephant. It is a command line utility with parser and interpreter and it accepts “slonik scripts” – a simple declarative scripting language. It is designed to overcome the limitations of procedural language. You use slonik commands to set up or modify slony replication and they can be embedded in shell scripts. It can accept commands from standard input or from files. The following example shows how a slonik script being fed to the slonik utility, and then embedded in shell scripts.

The script to create the initial configuration for the simple master-slave setup of our pgbench database looks like this:

#!/bin/sh
slonik <<_EOF_
 cluster name = percona_pg;
 node 1 admin conninfo = 'dbname=pg93 host=pg93_host user=percona_pg93_user';
 node 2 admin conninfo = 'dbname=pg11 host=pg11_host user=percona_pg11_user';
 #--
 # Creates a _$(clustername), this example, _percona_pg schema
 #--
 init cluster ( id=1, comment = 'Legacy PG Node');
 #--
 # Add a list of tables being replicated to a set.
 #--
create set (id=1, origin=1, comment='pgbench');
 set add table (set id=1, origin=1, id=1, fully qualified name = 'public.pgbench_accounts', comment='accounts');
 set add table (set id=1, origin=1, id=2, fully qualified name = 'public.pgbench_branches', comment='branches');
 set add table (set id=1, origin=1, id=3, fully qualified name = 'public.pgbench_tellers', comment='tellers');
 set add table (set id=1, origin=1, id=4, fully qualified name = 'public.pgbench_history', comment='history');
 #--
 # Create the second node (the slave) tell the 2 nodes how to connect to
 # each other and how they should listen for events.
 #--
 store node (id=2, comment = 'Target node', event node=1);
 store path (server = 1, client = 2, conninfo='dbname=pg93 host=pg93_host user=percona_pg93_user');
 store path (server = 2, client = 1, conninfo='dbname=pg11 host=pg11_host user=percona_pg11_user');
_EOF_

Why Slony is useful for migrations?

Despite the benefits of internal logical replication, this external solution is better for migrations between different versions that are older than PostgreSQL 9.4. The trigger-based approach depends on the database API – both older and newer versions should be compatible for PL/pgSQL and SQL syntax.

How to adapt your database for usage with Slony?

  • Your tables have to have primary keys. Add a serial field to all tables without primary key
  • OID blobs will not have their changes replicated. If you have columns with small-length values, you could convert these to BYTEA. For a really large objects like images, it’s better to store data externally e.g. use S3 in Amazon cloud. If it’s too hard to change your application, you could apply blob changes at the last stage of migration.
  • ALTER TABLE and other DDL operations. Slony can’t detect table structure changes. Instead you should use an EXECUTE SCRIPT slonik command to apply a SQL file with DDL or SQL strings to the whole replication cluster.

Online migration from legacy PostgreSQL

  1. Create replication user with superuser privileges. It’s possible to use fine-grained privileges, but they are significantly harder to setup.
  2. Create a database on the destination, setup access by TCP/IP
  3. Copy table definitions from master to slaves
  4. Install Slony-I. On servers with an old OS distribution you might find it simpler to install Slony-I from the source code.
  5. Define cluster, set of tables, and connection information to nodes as a list of slonik commands
  6. Start the slon daemon on each postgresql server. Check standard output or log files for any potential communication errors.
  7. Execute subscription slonik commands to start sync
  8. Test your read-only queries with a newer version of postgres
  9. Once all the data has been replicated and is in sync, stop your applications and repoint them to the new postgres server.
  10. Use “uninstall node” on the newer version of PostgreSQL to remove all traces of Slony replication

Downgrade steps

To downgrade, follow the same procedure as upgrade. Slony allows you to replicate from and to any versions of PosgreSQL supported by your slony version. The minimum supported version is 8.4.

Summary

So far, we have seen a high level overview of how Slony can be helpful to perform an upgrade with the least possible downtime. Come and see more of this in action during our Webinar.  And don’t forget at Percona Live in Austin, May 28-30 2019, we’ll have two days of PostgreSQL content in a postgres dedicated track.


Image derived from photo by Chen Hu on Unsplash

Apr
04
2019
--

Replication Between PostgreSQL Versions Using Logical Replication

postgres read replica from primary

When you need to upgrade PostgreSQL, there are a variety of approaches that you can use. To avoid application downtime, then not all of the options to upgrade postgres are suitable. When avoiding downtime is essential, then you might consider using replication as a means of upgrade, and depending on your scenario, you can choose to approach this task using either logical replication or physical (streaming) replication. Here, we take a look at the difference between logical and physical replication in PostgreSQL. Then we explore how to accomplish an upgrade using logical replication in more detail, and by doing so, avoid application downtime. In a subsequent article, we’ll investigate physical replication.

We have already discussed about a few methods available to perform PostgreSQL upgrades in our previous blog posts – PostgreSQL Upgrade Using pg_dumpall and PostgreSQL Upgrade Using pg_dump/pg_restore – as part of our Upgrading or Migrating Your Legacy PostgreSQL to Newer PostgreSQL Versions series. However, both of these methods involve downtime to application.

Types of logical replication

Here we’ll cover two types of replication you could implement:

  1. Replication between PostgreSQL 10 and 11 versions using built-in logical replication.
  2. Replication between PostgreSQL 9.4 or (<  PG 11) to PostgreSQL 11 using an extension named pglogical .

We might opt to implement replication as a method of upgrade to minimize downtime for the application. Once all the data to date has been replicated to another PostgreSQL server on the latest version, you can simply switch your application to the new server with a minimal downtime… though of course this does depends on the complexity of your application stack.

Logical replication in PostgreSQL allows users to perform a selective replication of a few tables and open a standby for writes. Whereas physical replication in PostgreSQL is a block level replication. In this case, each database in the master is replicated to a standby, and the standby is not open for writes. Going forward, we’ll refer to physical replication as streaming replication.

With logical replication, a standby can have replication enabled from multiple masters. This could be helpful in situations where you need to replicate data from several PostgreSQL databases (OLTP) to a single PostgreSQL server for reporting and data warehousing.

One of the biggest advantages of logical over streaming replication is that logical replication allows us to replicate changes from an older version PostgreSQL to a later version. Streaming replication works only when both the master and standby are of the same major version. We’d recommend they have same minor version too for best practice.

Replication between PostgreSQL 10 and 11 versions

Starting from PostgreSQL 10, logical replication is available with the PostgreSQL source by default. So, you could easily replicate a PostgreSQL 10 database to PostgreSQL 11. Logical Replication uses a publish and subscribe model. The node that sends the changes becomes a publisher. And the node that subscribes to those changes becomes a subscriber. You may have one or more subscriptions to a publication.

Publication

Publication is a set of changes generated from a group of tables. It is referred to as a change set or replication set. Publications can only contains tables and cannot contain any other objects. DMLs on these tables can be replicated but not DDLs.

In a publication, you can choose what type of DML to replicate: INSERT or DELETE or UPDATE or ALL. By default, it is ALL. You must have a replica identity set on the table being published to replicate UPDATES and DELETES to a subscriber. A replica identity set helps in identifying the rows to be updated or deleted.

The primary key of a table is its default replica identity. You can also make a unique index with NO NULL values as a replica identity. If there is no primary key or a unique index with NO NULLs, then you can set the replica_identity to FULL. When a replica identity is set to FULL, postgres uses the entire row as a key. Of course, this may be inefficient.

You might see ERRORS if a table with no primary key and a non-default replica identity has been added to a publication after an UPDATE or a DELETE operation.

Subscription

A subscriber can subscribe to one or more publications. Before adding the subscription, you must ensure that the tables being replicated have been created in the subscriber node. In order to achieve that, you can perform a schema-only dump from publisher to subscriber node.

An example of logical replication

The following example steps work for logical replication between PostgreSQL 10 and 11 versions only.

On the publishing node, create a publication. You can either add all tables or choose to add selected tables to the publication.

-- For adding ALL Tables in Database
CREATE PUBLICATION percpub FOR ALL TABLES;
-- For adding Selected Tables in Database
CREATE PUBLICATION percpub FOR TABLE scott.employee scott.departments;

On the subscriber node, create a subscription that refers to the publication on the publisher node. Perform a DDL dump of the tables to the subscriber node before creating the subscription, as mentioned above,

$ pg_dump -h publisher_server_ip -p 5432 -d percona -Fc -s -U postgres | pg_restore -d percona -h subscriber_node_ip -p 5432 -U postgres
CREATE SUBSCRIPTION percsub CONNECTION 'host=publisher_server_ip dbname=percona user=postgres password=secret port=5432' PUBLICATION percpub;

The above command also copies the pre-existing data from the tables. If you want to disable the copy of the pre-existing data, you can use the following syntax. It will then only start copying the changes to the publisher after you run this command.

CREATE SUBSCRIPTION percsub CONNECTION 'host=publisher_server_ip dbname=percona user=postgres password=oracle port=5432' PUBLICATION percpub WITH (copy_data = false);

Monitor the replication using the following command on the publishing node.

$ psql
\x
select * from pg_stat_replication;

Replication between PostgreSQL 9.4 and PostgreSQL 11

Now, what about the versions that are older than PostgreSQL 10? For this purpose, there is an extension named

pglogical

that works for versions from 9.4 until 11. Using pglogical, you can easily replicate PostgreSQL 9.4 to PostgreSQL 11.

The following sequence of steps demonstrates a high-level procedure to setup replication between PG 9.4 and PG 11 using pglogical extension.

Step 1 : Consider pgserver_94 to be the source server with a database : percona_94 running on PostgreSQL 9.4. Create the following extensions.

[pgserver_94:] $psql -d percona_94 -c "CREATE EXTENSION pglogical_origin"
CREATE EXTENSION
[pgserver_94:] $psql -d percona_94 -c "CREATE EXTENSION pglogical"
CREATE EXTENSION

Step 2 : Now, you can go ahead and add either selected tables or all the tables in a schema or multiple schemas for replication. In the following example, you can see an error when there is no primary key on one of the tables.

[pgserver_94:] $psql -d percona_94
psql (9.4.21)
Type "help" for help.
percona_94=# SELECT pglogical.create_node(node_name := 'provider1',dsn := 'host=192.168.0.24 port=5432 dbname=percona_94');
create_node
-------------
2976894835
(1 row)
percona_94=# SELECT pglogical.replication_set_add_all_tables('default', ARRAY['public']);
ERROR: table pgbench_history cannot be added to replication set default
DETAIL: table does not have PRIMARY KEY and given replication set is configured to replicate UPDATEs and/or DELETEs
HINT: Add a PRIMARY KEY to the table
percona_94=# ALTER TABLE pgbench_history ADD PRIMARY KEY (tid,aid,delta);
ALTER TABLE
percona_94=# SELECT pglogical.replication_set_add_all_tables('default', ARRAY['public']);
replication_set_add_all_tables
--------------------------------
t
(1 row)

Step 3

On the subscriber node, which is our PostgreSQL 11 database, you can run similar commands as follows.

[pgserver_11:] $psql -d percona_11
psql (11.2)
Type "help" for help.
percona_11=# SELECT pglogical.create_node(node_name := 'subscriber1',dsn := 'host=127.0.0.1 port=5432 dbname=percona_11 password=secret');
 create_node
-------------
   330520249
(1 row)
percona_11=# SELECT pglogical.create_subscription(subscription_name := 'subscription1',provider_dsn := 'host=192.168.0.24 port=5432 dbname=percona_94 password=secret');
 create_subscription
---------------------
          1763399739
(1 row)

Step 4 You can then validate the replication status by querying a few tables pglogical always updates:

percona_11=# select * from pglogical.local_sync_status;
 sync_kind | sync_subid | sync_nspname |   sync_relname   | sync_status | sync_statuslsn
-----------+------------+--------------+------------------+-------------+----------------
 f         | 1763399739 | public       | pgbench_accounts | r           | 0/2EB7D48
 f         | 1763399739 | public       | pgbench_history  | r           | 0/2EB7D48
 f         | 1763399739 | public       | pgbench_tellers  | r           | 0/2EB7D48
 f         | 1763399739 | public       | pgbench_branches | r           | 0/2EB7D48
 d         | 1763399739 |              |                  | r           | 0/0
(5 rows)
percona_11=# select * from pglogical.subscription;
   sub_id   |   sub_name    | sub_origin | sub_target | sub_origin_if | sub_target_if | sub_enabled |             sub_slot_name              |         sub_rep
lication_sets          | sub_forward_origins | sub_apply_delay
------------+---------------+------------+------------+---------------+---------------+-------------+----------------------------------------+----------------
-----------------------+---------------------+-----------------
 1763399739 | subscription1 | 2976894835 |  330520249 |    2402836775 |    2049915666 | t           | pgl_percona_11_provider1_subscription1 | {default,defaul
t_insert_only,ddl_sql} | {all}               | 00:00:00
(1 row)

Primary key selection

At step 2, you saw how all the tables of schema : public got added to a replication set by creating a primary key on the table that doesn’t currently have one. The primary key I chose may not be the right one for that table as it is just for demonstration. However, when you choose a primary key, make sure that you are selecting the right one. It needs to be always unique and use column(s) that don’t normally contain NULLs. If you don’t research primary key selection thoroughly, you could cause downtime to your application. Here’s an example error that you could encounter:

[pgserver_94:] $pgbench -c 10 -T 300 -n percona_94
Client 7 aborted in state 12: ERROR: duplicate key value violates unique constraint "pgbench_history_pkey"
DETAIL: Key (tid, aid, delta)=(7, 63268, 2491) already exists.

So far we have seen how you can use pglogical to create replication between an older version to a newer version PostgreSQL. After you have set up replication, you can easily switch your applications to the latest version with a lower downtime.

To see more in action, why not subscribe to our webinar? And don’t forget at Percona Live in Austin, May 28-30 2019, we have two days of PostgreSQL content in a postgres dedicated track.

Mar
27
2019
--

PostgreSQL Upgrade Using pg_dump/pg_restore

pg-dump upgrade postgres

PostgreSQL logoIn this blog post, we will explore 

pg_dump

/

pg_restore

, one of the most commonly used options for performing a PostgreSQL upgrade. It is important to understand the scenarios under which

pg_dump

and

pg_restore

utilities will be helpful.

This post is the second of our Upgrading or Migrating Your Legacy PostgreSQL to Newer PostgreSQL Versions series where we’ll be exploring different methods available to upgrade your PostgreSQL databases.

About pg_dump

pg_dump

is a utility to perform a backup of single database. You cannot backup multiple databases unless you do so using separate commands in parallel. If your upgrade plan needs global objects to be copied over,

pg_dump

need to be supplemented by

pg_dumpall

 . To know more about

pg_dumpall

 , you may refer to our previous blog post.

pg_dump formats

pg_dump

can produce dumps in multiple formats – plain text and custom format – each with own advantages. When you use

pg_dump

with custom format

(-Fc)

, you must use

pg_restore

to restore the dump.

If the dump is taken using a plain-text format, pg_dump generates a script file of multiple SQL commands. It can be restored using psql.

A custom format dump, however, is compressed and is not human-readable.

A dump taken in plain text format may be slightly larger in size when compared to a custom format dump.

At times, you may wish to perform schema changes in your target PostgreSQL database before restore, for example, table partitioning. Or you may wish to restore only a selected list of objects from a dump file.

In such cases, you cannot restore a selected list of tables from a plain format dump of a database. If you take the database dump in custom format,  you can use pg_restore, which will help you choose a specific set of tables for restoration.

Steps involved in upgrade

The most important point to remember is that both dump and restore should be performed using the latest binaries. For example, if we need to migrate from version 9.3 to version 11, we should be using the pg_dump binary of PostgreSQL 11 to connect to 9.3 .

When a server is equipped with two different versions of binaries, it is good practice to specify the full path of the pg_dump from the latest version as follows :

/usr/lib/postgresql/11/bin/pg_dump <connection_info_of_source_system> <options>

Getting the global dumps

In PostgreSQL, users/roles are global to the database cluster, and the same user can have privileges on objects in different databases. These are called “Globals” because they are applicable for all the databases within the instance. Creation of globals in the target system at the earliest opportunity is very important, because rest of the DDLs may contain GRANTs to these users/roles. It is good practice to dump the globals into a file, and to examine the file, before importing into destination system. This can be achieved using the following command :

/usr/lib/postgresql/11/bin/pg_dumpall -g -p 5432 > /tmp/globals_only.sql

Since this produces a plain SQL dump file, it can be fed to

psql

connected to the destination server. If there are no modifications required, the globals can be directly piped to the destination server using the command in the next example. Since this is a plain SQL dump file, it can be fed to psql for restore.

/usr/lib/postgresql/11/bin/pg_dumpall -g <source_connection_info> | psql -p <destination_connection_info>

The above command would work for an upgrade in a local server. You can add an additional argument

-h

for

hostname

in the

<destination_connection_info>

if you are performing an upgrade to a remote database server.

Schema Only Dumps

The next stage of the migration involves the creation of schema objects. At this point, you might want to move different database objects to different tablespaces, and partition a few of the tables. If such schema modifications are part of the plan, then we should extract the schema definition to a plain text file. Here’s an example command that can be used to achieve this :

/usr/lib/postgresql/11/bin/pg_dump -s -d databasename -p 5432 > /tmp/schema_only.sql

In general, the majority of the database objects won’t need any modifications. In such cases, it is good practice to dump the schema objects as such into the destination database using a

PIPE

, using a similar command to this:

/usr/lib/postgresql/11/bin/pg_dump -s -d databasename <source_connection> | psql -d database <destination_connection>

Once all the schema objects are created, we should be able to drop only those objects which need modification. We can then recreate them with their modified definition.

Copying data

This is the stage when the majority of the data transfers between the database servers. If there is good bandwidth between source and destination, we should look to achieve maximum parallelism at this stage. In many situations, we could analyze the foreign key dependency hierarchy and import data in parallel batches for a group of tables. Data-only copying is possible using

-a

or

--data-only

  flag of

pg_dump

 .

Copying the data of individual tables

You might have to incorporate schema changes as part of an upgrade. In this case, you can copy the data of a few tables individually. We provide an example here:

/usr/lib/postgresql/11/bin/pg_dump <sourcedb_connection_info> -d <database> -a -t schema.tablename | psql <destinationdb_connection_info> <databasename>

There could be special situations where you need to append only a partial selection of the data. This happens especially on time-series data. In such cases, you can use copy commands with a WHERE clause cto extract and import specific data. You can see this in the following example :

/usr/lib/postgresql/11/bin/psql <sourcedb_connection_info> -c "COPY (select * from <table> where <filter condition>)” > /tmp/selected_table_data.sql

Summary

pg_dump/pg_restore may be useful if you need to perform a faster upgrade of PostgreSQL server with a modified schema and bloat-free relations. To see more about this method in action, please subscribe to our webinar here.


image based on photos by Skitterphoto and Magda Ehlers from Pexels

Nov
28
2017
--

Percona Monitoring and Management 1.5.0 Is Now Available

Percona Monitoring and Management

Percona announces the release of Percona Monitoring and Management 1.5.0 on November 28, 2017.

This release focuses on the following features:

  • Enhanced support for MySQL on Amazon RDS and Amazon Aurora – Dedicated Amazon Aurora dashboard offers maximum visibility into key database characteristics, eliminating the need for additional monitoring nodes.  We renamed Amazon RDS OS Metrics to Amazon RDS / Aurora MySQL Metrics
  • Simpler configuration – Percona Monitoring and Management now offers easier configuration of key Amazon RDS and Amazon Aurora settings via a web interface
  • One-click data collection – One button retrieves vital information on server performance to assist with troubleshooting
  • Improved interface – A simple, consistent user interface makes it faster and more fluid to switch between Query Analytics and Metrics Monitor

Highlights from our new Amazon RDS / Aurora MySQL Metrics dashboard:

Shared elements for Amazon Aurora MySQL and RDS MySQL

Amazon Aurora MySQL unique elements

Amazon RDS for MySQL unique elements

We’ve integrated Query Analytics into Metrics Monitor, and it appears as a separate dashboard known as PMM Query Analytics.

With this release, Percona Monitoring and Management introduces a new deployment option via AWS Marketplace. This is in addition to our distribution method of Amazon Machine Images (AMI).

We have upgraded Grafana and Prometheus in this release. PMM now includes Grafana 4.6.1. One of the most prominent features that the upgraded Grafana offers is the support of annotations. You can mark a point or select a region in a graph and give it a meaningful description. For more information, see the release highlights.

Prometheus version 1.8.2, shipped with this release, offers a number of bug fixes. For more information, see the Prometheus change log.

New features

  • PMM-434PMM enables monitoring of Amazon RDS and Amazon Aurora metrics
  • PMM-1133Query Analytics is available from Grafana as a dashboard
  • PMM-1470: Integrated Cloudwatch metrics into Prometheus
  • PMM-699: Combined AWS RDS and Amazon Aurora metrics into one dashboard
  • PMM-722: Distributed the MariaDB dashboard graph elements among other existing dashboards and removed the MariaDB dashboard. Further, we renamed the MyISAM dashboard  to MyISAM/Aria Metrics
  • PMM-1258: The DISABLE_UPDATES option enables preventing manual updates when PMM Server is run from a Docker container.
  • PMM-1500: Added InnoDB Buffer Disk Reads to graph InnoDB Buffer Pool Requests to better understand missed InnoDB BP cache hits

Improvements

  • PMM-1577: Updated Prometheus to version 1.8.2
  • PMM-1603: Updated Grafana to version 4.6.1
  • PMM-1669: The representation of numeric values in the Context Switches graph in the System Overview dashboard was changed to improve readability.
  • PMM-1575: Templating rules were improved for the MyRocks and TokuDB dashboards so that only those instances with these storage engines are displayed

Bug fixes

  • PMM-1082: The CPU Usage graph on the Trends dashboard showed incorrect spikes
  • PMM-1549: The authentication of the mongodb:queries monitoring service did not work properly when the name of the database to authenticate was not provided.
  • PMM-1673: Fixed display issue with Microsoft Internet Explorer 11
Oct
20
2017
--

Percona Monitoring and Management 1.4.0 Is Now Available

Percona Monitoring and ManagementPercona announces the release of Percona Monitoring and Management 1.4.0.

This release introduces the support of external Prometheus exporters so that you can create dashboards in the Metrics monitor even for the monitoring services other than those provided with PMM client packages. To attach an existing external Prometheus exporter, run pmm-admin add external:metrics NAME_OF_EXPORTER URL:PORT.

The list of attached monitoring services is now available not only in the tabular format but also as a JSON file to enable automatic verification of your configuration. To view the list of monitoring services in the JSON format run pmm-admin list --json.

In this release, Prometheus and Grafana have been upgraded. Prometheus version 1.7.2, shipped with this release, offers a number of bug fixes that will contribute to its smooth operation inside PMM. For more information, see the Prometheus change log.

Version 4.5.2 of Grafana, included in this release of PMM, offers a number of new tools that will facilitate data analysis in PMM:

  • New query editor for Prometheus expressions features syntax highlighting and autocompletion for metrics, functions and range vectors.
    Percona Monitoring and Management
  • Query inspector provides detailed information about the query. The primary goal of graph inspector is to enable analyzing a graph which does not display data as expected.
    Percona Monitoring and Management

The complete list of new features in Graphana 4.5.0 is available from What’s New in Grafana v4.5.

For install and upgrade instructions, see Deploying Percona Monitoring and Management.

New features

  • PMM-1520: Prometheus upgraded to version 1.7.2.
  • PMM-1521: Grafana upgraded to version 4.5.2.
  • PMM-1091: The pmm-admin list produces a JSON document as output if the --json option is supplied.
  • PMM-507: External exporters are supported with pmm-admin.
  • PMM-1622: docker images of PMM Server are available for downloading as tar packages.

Improvements

  • PMM-1553: Consul upgraded to the 0.8 release.

Bug fixes

  • PMM-1172: In some cases, the TABLES section of a query in QAN could contain no data and display the List of tables is empty error. The Query and Explain sections had the relevant values.
  • PMM-1519: A Prometheus instance could be forced to shut down if it contained too many targets (more than 50). When started the next time, Prometheus initiated a time-consuming crash recovery routine which took long on large installations.
Oct
11
2017
--

Percona Monitoring and Management 1.3.2 Is Now Available

Percona Monitoring Management

Percona Monitoring ManagementPercona announces the release of Percona Monitoring and Management 1.3.2. This release only contains bug fixes related to usability.

For install and upgrade instructions, see Deploying Percona Monitoring and Management.

Bug fixes

  • PMM-1529: When the user selected “Today”, “This week”, “This month” or “This year” range in Metrics Monitor and clicked the Query Analytics button, the QAN page opened reporting no data for the selected range even if the data were available.
    Percona Monitoring and Management
  • PMM-1528: In some cases, the page not found error could appear instead of the QAN page after upgrading by using the Upgrade button.
  • PMM-1498 : In some cases, it was not possible to shut down the virtual machine containing the PMM Server imported as an OVA image.

Other bug fixes in this release: PMM-913, PMM-1215, PMM-1481PMM-1483, PMM-1507

 

Aug
23
2017
--

Percona Monitoring and Management 1.2.2 is Now Available

Percona Monitoring and Management (PMM)

Percona Monitoring and Management (PMM)Percona announces the release of Percona Monitoring and Management 1.2.2 on August 23, 2017.

For install and upgrade instructions, see Deploying Percona Monitoring and Management.

This release contains bug fixes related to performance and introduces various improvements. It also contains an updated version of Grafana.

Changes in PMM Server

We introduced the following changes in PMM Server 1.2.2:

Bug fixes

  • PMM-927: The error “Cannot read property ‘hasOwnProperty’ of undefined” was displayed on the QAN page for MongoDB.

    After enabling monitoring and generating data for MongoDB, the PMM client showed the following error message on the QAN page: “Cannot read property ‘hasOwnProperty’ of undefined”. This bug is now fixed.

  • PMM-949: Percona Server was not detected properly, the log_slow_* variables were not properly detected.

  • PMM-1081: Performance Schema Monitor treated queries that didn’t show up in every snapshot as new queries reporting a wrong number of counts between snapshots.

  • PMM-1272: MongoDB: the query empty abstract. This bug is now fixed.

  • PMM-1277: The QPS Graph had inappropriate Prometheus query. This bug is now fixed.

  • PMM-1279: The MongoDB summary did not work in QAN2 if mongodb authentication was activated. This bug is now fixed.

  • PMM-1284: Dashboards pointed to QAN2 instead of QAN. This bug is now fixed.

Improvements

  • PMM-586: The wsrep_evs_repl_latency parameter is now monitored in Grafana dashboards

  • PMM-624: The Grafana User ID remains the same in the pmm-server docker image

  • PMM-1209: OpenStack support is now enabled during the OVA image creation

  • PMM-1211: It is now possible to configure a static IP for an OVA image

    The root password can only be set from the console. If the root password is not changed from the default, a warning message appears on the console requesting the user to change the root password on the root first login from the console. Web/SSH users can neither use the root account password nor detect if the root password is set to the default value.

  • PMM-1221: Grafana updated to version 4.4.3

About Percona Monitoring and Management

Percona Monitoring and Management (PMM) is an open-source platform for managing and monitoring MySQL and MongoDB performance. Percona developed it in collaboration with experts in the field of managed database services, support and consulting.

PMM is a free and open-source solution that you can run in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL and MongoDB servers to ensure that your data works as efficiently as possible.

A live demo of PMM is available at pmmdemo.percona.com.

We’re always happy to help! Please provide your feedback and questions on the PMM forum.

If you would like to report a bug or submit a feature request, please use the PMM project in JIRA.

Aug
16
2017
--

Percona Monitoring and Management 1.2.1 is Now Available

Percona Monitoring and Management (PMM)

Percona Monitoring and Management (PMM)Percona announces the release of Percona Monitoring and Management 1.2.1 on August 16, 2017.

For install and upgrade instructions, see Deploying Percona Monitoring and Management.

This hotfix release improves memory consumption.

Changes in PMM Server

We’ve introduced the following changes in PMM Server 1.2.1:

Bug fixes

  • PMM-1280: PMM server affected by nGinx CVE-2017-7529. An integer overflow exploit could result in a DOS (Denial of Service) for the affected nginx service with the max_ranges directive not set. This problem is solved by setting the set max_ranges directive to 1 in the nGinx configuration.

Improvements

  • PMM-1232: Update the default value of the METRICS_MEMORY configuration setting. Previous versions of PMM Server used a different value for the METRICS_MEMORY configuration setting which allowed Prometheus to use up to 768MB of memory. PMM Server 1.2.0 used the storage.local.target-heap-size setting, its default value is 256MB. Unintentionally, this value reduced the amount of memory that Prometheus could use. As a result, the performance of Prometheus was affected. To improve the performance of Prometheus, the default setting of storage.local.target-heap-size has been set to 768 MB.

About Percona Monitoring and Management

Percona Monitoring and Management (PMM) is an open-source platform for managing and monitoring MySQL and MongoDB performance. Percona developed it in collaboration with experts in the field of managed database services, support and consulting.

PMM is a free and open-source solution that you can run in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL and MongoDB servers to ensure that your data works as efficiently as possible.

A live demo of PMM is available at pmmdemo.percona.com.

We’re always happy to help! Please provide your feedback and questions on the PMM forum.

If you would like to report a bug or submit a feature request, please use the PMM project in JIRA.

Powered by WordPress | Theme: Aeros 2.0 by TheBuckmaker.com