Category: MySQL

MySQL related posts

Refactoring replication topologies with Pseudo GTID: a visual tour

MySQL

Orchestrator 1.2.1-beta supports Pseudo GTID (read announcement): a means to refactor the replication topology and connect slaves even without direct relationship; even across failed servers. This post illustrates two such scenarios and shows the visual way of mathcing/re-synching slaves.

Of course, orchestrator is not just a GUI tool; anything done with drag-and-drop is also done via web API (in fact, the drag-and-drop invoke the web API) as well as via command line. I’m mentioning this as this is the grounds for failover automation planned for the future.

Scenario 1: the master unexpectedly dies

The master crashes and cannot be contacted. All slaves are stopped as effect, but each in a different position. Some managed to salvage relay logs just before the master dies, some didn’t. In our scenario, all three slaves are at least caught up with the relay log (that is, whatever they managed to pull through the network, they already managed to execute). So they’re otherwise sitting idle waiting for something to happen. Well, something’s about to happen.

orchestrator-pseudo-gtid-dead-master

Note the green “Safe mode” button to the right. This means operation is through calculation of binary log files & positions with relation to one’s master. But the master is now dead, so let’s switch to adventurous mode; in this mode we can drag and drop slaves onto instances normally forbidden. At this stage the web interface allows us to drop a slave onto its sibling or any of its ancestors (including its very own parent, which is a means of reconnecting a slave with its parent). Anyhow:

orchestrator-pseudo-gtid-dead-master-pseudo-gtid-mode

We notice that orchestrator is already kind enough to say which slave is best candidate to be the new master (127.0.0.1:22990): this is the slave (or one of the slaves) with most up-to-date data. So we choose to take another server and make it a slave of 127.0.0.1:22990: Continue reading » “Refactoring replication topologies with Pseudo GTID: a visual tour”

Orchestrator 1.2.1 BETA: Pseudo GTID support, reconnect slaves even after master failure

MySQL

orchestrator 1.2.1 BETA is released. This version supports Pseudo GTID, and provides one with powerful refactoring of one’s replication topologies, even across failed instances.

orchestrator-pseudo-gtid-dead-relay-master-begin-drag

Depicted: moving a slave up the topology even though its local master is inaccessible

Enabling Pseudo-GTID

You will need to:

  1. Inject a periodic unique entry onto your binary logs
  2. Configure orchestrator to recognize said entry.

Pseudo GTID injection example

We will use the event scheduler (must be enabled) to inject an entry every 10 seconds, recognized both in statement-based and row-based replication.

create database if not exists meta;

drop event if exists meta.create_pseudo_gtid_view_event;

delimiter ;;
create event if not exists
  meta.create_pseudo_gtid_view_event
  on schedule every 10 second starts current_timestamp
  on completion preserve
  enable
  do
    begin
      set @pseudo_gtid := uuid();
      set @_create_statement := concat('create or replace view meta.pseudo_gtid_view as select \'', @pseudo_gtid, '\' as pseudo_gtid_unique_val from dual');
      PREPARE st FROM @_create_statement;
      EXECUTE st;
      DEALLOCATE PREPARE st;
    end
;;

delimiter ;

set global event_scheduler := 1;

Make sure to enable event_scheduler in your my.cnf config file.

An entry in the binary logs would look like this: Continue reading » “Orchestrator 1.2.1 BETA: Pseudo GTID support, reconnect slaves even after master failure”

Refactoring replication topology with Pseudo GTID

MySQL

This post describes in detail the method of using Pseudo GTID to achieve unplanned replication topology changes, i.e. connecting two arbitrary slaves, or recovering from a master failure even as all its slaves are hanging in different positions.

Please read Pseudo GTID and Pseudo GTID, RBR as introduction.

Consider the following case: the master dies unexpectedly, and its three slaves are all hanging, not necessarily at same binary log file/position (network broke down while some slaves managed to salvage more entries into their relay logs than others)

orchestrator-failed-master

(Did you notice the “Candidate for master” message? To be discussed shortly)

GTID

With GTID each transaction (and entry in the binary log) is associated with a unique mark — the Global Transaction ID. Just pick the slave with the most advanced GTID to be the next master, and just CHANGE MASTER TO MASTER_HOST=’chosen_slave’ on the other slaves, and everything magically works. A slave knows which GTID it has already processed, and can look that entry on its master’s binary logs, resuming replication on the one that follows.

How does that work? The master’s binary logs are searched for that GTID entry. I’m not sure how brute-force this is, since I’m aware of a subtlety which requires brute-force scan of all binary logs; I don’t actually know if it’s always like that.

Pseudo GTID

We can mimick that above, but our solution can’t be as fine grained. With the injection of Pseudo GTID we mark the binary log for unique entries. But instead of having a unique identifier for every entry, we have a unique identifier for every second, 10 seconds, or what have you, with otherwise normal, non-unique entries in between our Pseudo GTID entries.

Recognizing which slave is more up to date

Given two slaves, which is more up to date?

  • If both replicate(d) from same master, a SHOW SLAVE STATUS comparison answers (safe method: wait till SQL thread catches up with broken IO thread, compare relay_master_log_file, exec_master_log_pos on both machines). This is the method by which the above “Candidate for master” message is produced.
  • If one is/was descendent of the other, then obviously it is less advanced or equals its ancestor.
  • Otherwise we’re unsure – still solvable via bi-directional trial & error, as explained later on.

For now, let’s assume we know which slave is more up to date (has received and executed more relay logs). Let’s call it S1, whereas the less up-to-date will be S2. This will make our discussion simpler. Continue reading » “Refactoring replication topology with Pseudo GTID”

Pseudo GTID, Row Based Replication

MySQL

This post continues Pseudo GTID, in a series of posts describing an alternative to using MySQL GTIDs.

The solution offered in the last post does not work too well for row based replication. The binary log entries for the INSERT statement look like this:

# at 1020
# at 1074
#141020 12:36:21 server id 1  end_log_pos 1074  Table_map: `test`.`pseudo_gtid` mapped to number 33
#141020 12:36:21 server id 1  end_log_pos 1196  Update_rows: table id 33 flags: STMT_END_F

BINLOG '
lddEVBMBAAAANgAAADIEAAAAACEAAAAAAAEABHRlc3QAC3BzZXVkb19ndGlkAAMDBw8CQAAE
lddEVBgBAAAAegAAAKwEAAAAACEAAAAAAAEAA///+AEAAACL10RUJDg2ZmRhMDk1LTU4M2MtMTFl
NC05NzYyLTNjOTcwZWEzMWVhOPgBAAAAlddEVCQ4Y2YzOWMyYy01ODNjLTExZTQtOTc2Mi0zYzk3
MGVhMzFlYTg=
'/*!*/;

Where’s our unique value? Encoded within something that cannot be trusted to be unique. Issuing mysqlbinlog –verbose helps out:

BEGIN
/*!*/;
# at 183
# at 237
#141020 12:35:51 server id 1  end_log_pos 237   Table_map: `test`.`pseudo_gtid` mapped to number 33
#141020 12:35:51 server id 1  end_log_pos 359   Update_rows: table id 33 flags: STMT_END_F

BINLOG '
d9dEVBMBAAAANgAAAO0AAAAAACEAAAAAAAEABHRlc3QAC3BzZXVkb19ndGlkAAMDBw8CQAAE
d9dEVBgBAAAAegAAAGcBAAAAACEAAAAAAAEAA///+AEAAABt10RUJDc1MWJkYzEwLTU4M2MtMTFl
NC05NzYyLTNjOTcwZWEzMWVhOPgBAAAAd9dEVCQ3YjExZDQzYy01ODNjLTExZTQtOTc2Mi0zYzk3
MGVhMzFlYTg=
'/*!*/;
### UPDATE `test`.`pseudo_gtid`
### WHERE
###   @1=1
###   @2=1413797741
###   @3='751bdc10-583c-11e4-9762-3c970ea31ea8'
### SET
###   @1=1
###   @2=1413797751
###   @3='7b11d43c-583c-11e4-9762-3c970ea31ea8'

and that’s something we can work with. However, I like to do stuff from within MySQL, and rely as little as possible on external tools. How do the binary log entries look via SHOW BINLOG EVENTS? Not good.

master [localhost] {msandbox} (test) > show binlog events in 'mysql-bin.000058' limit 20;
+------------------+------+-------------+-----------+-------------+---------------------------------------+
| Log_name         | Pos  | Event_type  | Server_id | End_log_pos | Info                                  |
+------------------+------+-------------+-----------+-------------+---------------------------------------+
| mysql-bin.000058 |    4 | Format_desc |         1 |         107 | Server ver: 5.5.32-log, Binlog ver: 4 |
| mysql-bin.000058 |  107 | Query       |         1 |         183 | BEGIN                                 |
| mysql-bin.000058 |  183 | Table_map   |         1 |         237 | table_id: 33 (test.pseudo_gtid)       |
| mysql-bin.000058 |  237 | Update_rows |         1 |         359 | table_id: 33 flags: STMT_END_F        |
| mysql-bin.000058 |  359 | Xid         |         1 |         386 | COMMIT /* xid=5460 */                 |
| mysql-bin.000058 |  386 | Query       |         1 |         462 | BEGIN                                 |
| mysql-bin.000058 |  462 | Table_map   |         1 |         516 | table_id: 33 (test.pseudo_gtid)       |
| mysql-bin.000058 |  516 | Update_rows |         1 |         638 | table_id: 33 flags: STMT_END_F        |
| mysql-bin.000058 |  638 | Xid         |         1 |         665 | COMMIT /* xid=5471 */                 |
| mysql-bin.000058 |  665 | Query       |         1 |         741 | BEGIN                                 |
| mysql-bin.000058 |  741 | Table_map   |         1 |         795 | table_id: 33 (test.pseudo_gtid)       |
| mysql-bin.000058 |  795 | Update_rows |         1 |         917 | table_id: 33 flags: STMT_END_F        |
| mysql-bin.000058 |  917 | Xid         |         1 |         944 | COMMIT /* xid=5474 */                 |
| mysql-bin.000058 |  944 | Query       |         1 |        1020 | BEGIN                                 |
| mysql-bin.000058 | 1020 | Table_map   |         1 |        1074 | table_id: 33 (test.pseudo_gtid)       |
| mysql-bin.000058 | 1074 | Update_rows |         1 |        1196 | table_id: 33 flags: STMT_END_F        |
| mysql-bin.000058 | 1196 | Xid         |         1 |        1223 | COMMIT /* xid=5476 */                 |
| mysql-bin.000058 | 1223 | Query       |         1 |        1299 | BEGIN                                 |
| mysql-bin.000058 | 1299 | Table_map   |         1 |        1353 | table_id: 33 (test.pseudo_gtid)       |
| mysql-bin.000058 | 1353 | Update_rows |         1 |        1475 | table_id: 33 flags: STMT_END_F        |
+------------------+------+-------------+-----------+-------------+---------------------------------------+

The representation of row-format entries in the SHOW BINLOG EVENTS output is really poor. Why, there’s nothing to tell me at all about what’s been done, except that this is some operation on test.pseudo_gtid. Obviously I cannot find anything unique over here.

Not all is lost. How about DDL statements? Those are still written in SBR format (there’s no rows to log upon creating a table). A solution could be somehow manipulating a unique value in a DDL statement. There could be various such solutions, and I chose to use a CREATE VIEW statement, dynamically composed of a UUID(): Continue reading » “Pseudo GTID, Row Based Replication”

Pseudo GTID

MySQL

Pseudo GTID is a method to implement a GTID-like solution where slaves are easily connected to one another. This blog post and the following ones will describe work in progress (some 80% completed), where simulation of GTID makes for a good enough basis for refactoring replication topologies. I’m coding this in orchestrator, which already provides a substantial infrastructure support for this.

The final goal: orchestrator will allow you to move a slave below another, using only the data available by those two slaves. The usage is obvious:

  • Easy master failover (master dead? Orchestrator will choose the most advanced slave to promote and make it master of its siblings)
  • Slave promotion in complex topologies (with deep nested topologies, be able to move a slave up the hierarchy even if its local master is corrupted).

This can all happen with your normal, non GTID, MySQL replication, using your normal binary log files & positions.

This work in progress is inspired by Sam Lambert at GitHub, who has worked on a similar solution with different implementation. I also recall discussions with other DBAs having similar solution.

Pseudo GTID

First thing’s first, the basis for proposed solution is a pseudo-GTID. A unique entry in the binary logs (not necessarily sequential; not necessarily in ascending order). While in GTID implementations we have a unique identifier for each entry in the binary log, with pseudo-GTID we accept an occasional (or frequent) unique entry in the binary log.

There are many ways to do so. Certainly a client can generate a unique Id and invoke some statement on MySQL involving that ID. That would serve as valid grounds for the proposed solution. But I like things to be contained within MySQL. Consider, for example, the following event, which would be my preferred choice in Statement Based Replication (for RBR solution, see next post):

drop table if exists test.pseudo_gtid;
create table if not exists test.pseudo_gtid (
  id int unsigned not null primary key,
  ts timestamp,
  gtid varchar(64) charset ascii
);


drop event if exists test.update_pseudo_gtid_event;

delimiter ;;
create event if not exists
  test.update_pseudo_gtid_event
  on schedule every 10 second starts current_timestamp
  on completion preserve
  enable
  do
    begin
      set @pseudo_gtid := uuid();
      insert into test.pseudo_gtid (id, ts, gtid) values (1, NOW(), @pseudo_gtid) on duplicate key update ts=NOW(), gtid=VALUES(gtid);
    end
;;

delimiter ;

The above is based on Making UUID() and RAND() replication safe. What do we get? Once in 10 seconds (or what have you), a unique entry is written to the binary log.

Continue reading » “Pseudo GTID”

Making UUID() and RAND() replication safe

MySQL

MySQL’s UUID() and RAND() functions both provide with (pseudo) indeterministic result. UUID()‘s result is moreover bound to the host on which it executes. For this reason, both are unsafe to replicate with STATEMENT binlog format. As an example, consider:

master> create table test.uuid_test (id int, u varchar(64));

master> insert into test.uuid_test values (1, UUID());
Query OK, 1 row affected, 1 warning (0.03 sec)

master> select * from test.uuid_test;
+------+--------------------------------------+
| id   | u                                    |
+------+--------------------------------------+
|    1 | 7e3596d8-56ac-11e4-b284-3c970ea31ea8 |
+------+--------------------------------------+

The warning we got on the insert directly relates to the following inconsistency on a slave:

slave1> select * from test.uuid_test;
+------+--------------------------------------+
| id   | u                                    |
+------+--------------------------------------+
|    1 | 7e379d63-56ac-11e4-8477-3c970ea31ea8 |
+------+--------------------------------------+

The data on the slave is clearly inconsistent with the master’s. The slave, replicating via STATEMENT binlog format, re-executes the INSERT command and gets a different UUID value.

External

One solution to the above is to generate the UUID value from your application. By the time MySQL gets the INSERT statement, the UUID value is a constant string, as far as MySQL is concerned.

Internal

However there’s a way to do it from within MySQL, by decoupling the UUID() function from the INSERT statement. It takes a session variable. Consider: Continue reading » “Making UUID() and RAND() replication safe”

orchestrator 1.1.18: new features, support for orchestrator-agent

MySQL

Outbrain‘s orchestrator 1.1.18 is released:

  • Support for orchestrator-agent (see announcement): agent pages, support for agent actions, initiation of seeds (provisioning of new/corrupted servers), auditing of seeds.
  • Clusters dashboard
  • Support for long query auditing
  • SSL
  • Proxy authentication (e.g. apache2 serving as reverse-proxy with LDAP)
  • User control
  • Better slave moving rules.

Quick links:

orchestrator now allows for seeding/provisioning of servers via orchestrator-agent. It communicates with agents executing on the MySQL hosts and coordinate transfer of data between them. orchestrator now supports invocation and auditing of seeding operations, and protects you from breaking your seeds. The orchestrator-agent is a solution to Outbrain’s specific use case, and may not appeal to the greater crowd. Nonetheless it is extendible and is released as open source. Continue reading » “orchestrator 1.1.18: new features, support for orchestrator-agent”

Announcing orchestrator-agent

MySQL

orchestrator-agent is a side-kick, complementary project of orchestrator, implementing a daemon service on one’s MySQL hosts which communicates with and accepts commands from orchestrator, built with the original purpose of providing an automated solution for provisioning new or corrupted slaves.

It was built by Outbrain, with Outbrain’s specific use case in mind. While we release it as open source, only a small part of its functionality will appeal to the public (this is why it’s not strictly part of the orchestrator project, which is a general purpose, wide-audience solution). Nevertheless, it is a simple implementation of a daemon, such that can be easily extended by the community. The project is open for pull-requests!

A quick breakdown of orchestrator-agent is as follows:

  • Executes as a daemon on linux hosts
  • Interacts and invokes OS commands (via bash)
  • Does not directly interact with a MySQL server running on that host (does not connect via mysql credentials)
  • Expects a single MySQL service on host
  • Can control the MySQL service (e.g. stop, start)
  • Is familiar with LVM layer on host
  • Can take LVM snapshots, mount snapshots, remove snapshots
  • Is familiar with the MySQL data directory, disk usage, file system
  • Can send snapshot data from a mounted snapshot on a running MySQL host
  • Can prepare data directory and receive snapshot data from another host
  • Recognizes local/remote datacenters
  • Controlled by orchestrator, two orchestrator-agents implement an automated and audited solution for seeding a new/corrupted MySQL host based on a running server.

Continue reading » “Announcing orchestrator-agent”

Get per-object grants via common_schema

MySQL

Did you know common_schema supports a complete breakdown of all accounts on your database server? It can provide you with the GRANT statements required to set up an account, the REVOKE statements to undo the former, and this can be broken down on a per-object & per-object-type basis. Consider the sql_grants view:

Find who has privileges on a table called t:

select * from common_schema.sql_grants where priv_level_name='table' and object_name='t'\G

           GRANTEE: 'power1'@'localhost'
              user: power1
              host: localhost
        priv_level: `mytst`.`t`
   priv_level_name: table
     object_schema: mytst
       object_name: t
current_privileges: SELECT
      IS_GRANTABLE: NO
         sql_grant: GRANT SELECT ON `mytst`.`t` TO 'power1'@'localhost'
        sql_revoke: REVOKE SELECT ON `mytst`.`t` FROM 'power1'@'localhost'
     sql_drop_user: DROP USER 'power1'@'localhost'

or, who has privileges on the test schema:

select * from common_schema.sql_grants where priv_level_name='schema' and object_name='test' \G

           GRANTEE: 'power1'@'localhost'
              user: power1
              host: localhost
        priv_level: `test`.*
   priv_level_name: schema
     object_schema: NULL
       object_name: test
current_privileges: ALTER, ALTER ROUTINE, CREATE, CREATE ROUTINE, CREATE TEMPORARY TABLES, CREATE VIEW, DELETE, DROP, EVENT, EXECUTE, INDEX, INSERT, LOCK TABLES, REFERENCES, SELECT, SHOW VIEW, TRIGGER, UPDATE
      IS_GRANTABLE: NO
         sql_grant: GRANT ALTER, ALTER ROUTINE, CREATE, CREATE ROUTINE, CREATE TEMPORARY TABLES, CREATE VIEW, DELETE, DROP, EVENT, EXECUTE, INDEX, INSERT, LOCK TABLES, REFERENCES, SELECT, SHOW VIEW, TRIGGER, UPDATE ON `test`.* TO 'power1'@'localhost'
        sql_revoke: REVOKE ALTER, ALTER ROUTINE, CREATE, CREATE ROUTINE, CREATE TEMPORARY TABLES, CREATE VIEW, DELETE, DROP, EVENT, EXECUTE, INDEX, INSERT, LOCK TABLES, REFERENCES, SELECT, SHOW VIEW, TRIGGER, UPDATE ON `test`.* FROM 'power1'@'localhost'
     sql_drop_user: DROP USER 'power1'@'localhost'

           GRANTEE: 'test'@'localhost'
              user: test
              host: localhost
        priv_level: `test`.*
   priv_level_name: schema
     object_schema: NULL
       object_name: test
current_privileges: ALTER, ALTER ROUTINE, CREATE, CREATE ROUTINE, CREATE TEMPORARY TABLES, CREATE VIEW, DELETE, DROP, EVENT, EXECUTE, INDEX, INSERT, LOCK TABLES, REFERENCES, SELECT, SHOW VIEW, TRIGGER, UPDATE
      IS_GRANTABLE: NO
         sql_grant: GRANT ALTER, ALTER ROUTINE, CREATE, CREATE ROUTINE, CREATE TEMPORARY TABLES, CREATE VIEW, DELETE, DROP, EVENT, EXECUTE, INDEX, INSERT, LOCK TABLES, REFERENCES, SELECT, SHOW VIEW, TRIGGER, UPDATE ON `test`.* TO 'test'@'localhost'
        sql_revoke: REVOKE ALTER, ALTER ROUTINE, CREATE, CREATE ROUTINE, CREATE TEMPORARY TABLES, CREATE VIEW, DELETE, DROP, EVENT, EXECUTE, INDEX, INSERT, LOCK TABLES, REFERENCES, SELECT, SHOW VIEW, TRIGGER, UPDATE ON `test`.* FROM 'test'@'localhost'
     sql_drop_user: DROP USER 'test'@'localhost'

In the same manner, you can easily SELECT for all grants that are defined per-table, per-schema, … priv_level_name: is any one of ‘user’, ‘schema’, ‘table’, ‘column’, ‘routine’.

The above is a view, which aggregates data from all relevant INFORMATION_SCHEMA tables, normalizing and de-normalizing as necessary.

You might also want to look at sql_show_grants which provides with a no-breakdown GRANT for all accounts. It’s like a SHOW ALL GRANTS which doesn’t exist, plus it’s SELECTable.

Also, thanks to eval(), the above make for executable code. Consider: Continue reading » “Get per-object grants via common_schema”

Three wishes for a new year

MySQL

Another new year by Jewish calendar. What do I wish for the following year?

  1. World peace
  2. Good health to all
  3. Multi-core execution for queries

After having evaluated a few columnar databases, and having seen how a single query gets 24 cores busy, I can’t look at MySQL the same way again. The fact that a single query consumes a single core only doesn’t seem right in the year 2014. Shard-query is a cool application-level attempt to solve the above; I would like to see stuff like this implemented inside the server (or inside the storage engine where possible).

None of my wishes in previous years [2010], [2011], [2012], [2013] came true (and mostly gone worse). I’m still willing to settle for two out of three.