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slow response from PMM grafana

Lastest Forum Posts - February 2, 2017 - 1:48pm
Hi,
There are 15 RDS aurora clusters to monitor, I'm using EC2 instance with t2.large instance class. I'm still seeing very slow response from grafana window and some times QAN is completely not responding. I see some metrics after restarting the admin client. Please let me know, Is there some thing I can do to get better response.

Vote Percona in LinuxQuestions.org Members Choice Awards 2016

Latest MySQL Performance Blog posts - February 2, 2017 - 12:40pm

Percona is calling on you! Vote for Percona for Database of the Year in LinuxQuestions.org Members Choice Awards 2016. Help Percona get recognized as one of the best database options for data performance. Percona provides free, fully compatible, enhanced, open source drop-in replacement database software with superior performance, scalability and instrumentation.

LinuxQuestions.org, or LQ for short, is a community-driven, self-help website for Linux users. Each year, LinuxQuestions.org holds an annual competition to recognize the year’s best-in-breed technologies. The online Linux community determines the winners of each category!

You can vote now for your favorite database of 2016 (Percona, of course!). This is your chance to be heard!

Voting ends on February 7, 2017. You must be a registered member of LinuxQuestions.org with at least one post on their forums to vote.

DML command rejected when PXC mode set to Enforcing

Lastest Forum Posts - February 2, 2017 - 9:31am
I'm working on a 3 node Percona XtraDB POC. My test app is a commercial product called Artifactory. The app successfully starts, but when testing some functions I'm running into errors when pxc mode is set to enforcing. Below appears to be the SQL in the logs being run and the error being returned. Are there any real issues with setting percona in permissive mode all the time when an app tries to use functions like this?

Code: 2017-02-02 09:25:37,451 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.u.JdbcHelper:255) - Executing SQL: 'SELECT repo_key FROM permission_target_repos WHERE perm_target_id = 436406'. 2017-02-02 09:25:37,500 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.u.JdbcHelper:113) - Query returned in 48.42 millis : 'SELECT repo_key FROM permission_target_repos WHERE perm_target_id = 436406' 2017-02-02 09:25:37,502 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.u.JdbcHelper:255) - Executing SQL: 'UPDATE permission_targets SET perm_target_name = 'Anonymous', includes = '**', excludes = NULL WHERE perm_target_id = 436406'. 2017-02-02 09:25:37,551 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.u.JdbcHelper:166) - Query returned with 1 results in 48.25 millis : 'UPDATE permission_targets SET perm_target_name = 'Anonymous', includes = '**', excludes = NULL WHERE perm_target_id = 436406' 2017-02-02 09:25:37,552 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.u.JdbcHelper:255) - Executing SQL: 'DELETE FROM permission_target_repos WHERE perm_target_id = 436406'. 2017-02-02 09:25:37,601 [http-nio-8081-exec-9] [TRACE] (o.a.s.d.s.DbTransactionManager:939) - Triggering beforeCompletion synchronization 2017-02-02 09:25:37,602 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.s.DbTransactionManager:847) - Initiating transaction rollback 2017-02-02 09:25:37,602 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.s.DbTransactionManager:284) - Rolling back JDBC transaction on Connection [ProxyConnection[PooledConnection[com.mysql.jdbc.JDBC4Connection@46bb9a77]]] 2017-02-02 09:25:37,627 [http-nio-8081-exec-9] [TRACE] (o.a.s.d.s.DbTransactionManager:968) - Triggering afterCompletion synchronization 2017-02-02 09:25:37,627 [http-nio-8081-exec-9] [TRACE] (o.a.s.d.f.s.SqlStorageSession:81) - Release all locks of lm=851775068 2017-02-02 09:25:37,628 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.s.SessionSynchronization:95) - Session completed: 'org.artifactory.storage.db.security.service.AclServiceImpl.updateAcl' in 228.28 millis 2017-02-02 09:25:37,677 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.s.DbTransactionManager:66) - Releasing JDBC Connection [ProxyConnection[PooledConnection[com.mysql.jdbc.JDBC4Connection@46bb9a77]]] after transaction 2017-02-02 09:25:37,677 [http-nio-8081-exec-9] [DEBUG] (o.a.s.d.s.DbTransactionManager:67) - Connection was successfully released 2017-02-02 09:25:37,691 [http-nio-8081-exec-9] [DEBUG] (o.a.s.f.l.a.LockingAdvice:81) - Received exception on method invocation: ReflectiveMethodInvocation: public abstract void org.artifactory.storage.security.service.AclStoreService.updateAcl(org.artifactory.security.MutableAclInfo); target is of class [org.artifactory.storage.db.security.service.AclServiceImpl] org.artifactory.storage.StorageException: Could not update ACL org.artifactory.model.xstream.security.AclImpl@fa86944d Caused by: java.sql.SQLException: Percona-XtraDB-Cluster prohibits use of DML command on a table (artifactory.permission_target_repos) without an explicit primary key with pxc_strict_mode = ENFORCING or MASTER

InnoDB Issue. Percona CLuster

Lastest Forum Posts - February 2, 2017 - 8:24am
for the past 2 months my cluster went do 2 times, and looks like this error is causing the problem, any ideas.

2017-01-24 10:52:47 7f50044bd7e0 InnoDB: Error: table `tmp`.`#sql3843_343b7a_a` does not exist in the InnoDB internal
InnoDB: data dictionary though MySQL is trying to drop it.
InnoDB: Have you copied the .frm file of the table to the
InnoDB: MySQL database directory from another database?
InnoDB: You can look for further help from
InnoDB: http://dev.mysql.com/doc/refman/5.6/...eshooting.html
2017-01-24 10:52:47 7f50044bd7e0 InnoDB: Error: table `tmp`.`#sql3843_343b7f_a` does not exist in the InnoDB internal
InnoDB: data dictionary though MySQL is trying to drop it.
InnoDB: Have you copied the .frm file of the table to the
InnoDB: MySQL database directory from another database?
InnoDB: You can look for further help from
InnoDB: http://dev.mysql.com/doc/refman/5.6/...eshooting.html

Percona Server for MySQL 5.5.54-38.6 is now available

Lastest Forum Posts - February 1, 2017 - 12:55pm
Perconaannounces the release of Percona Server for MySQL 5.5.54-38.6 on February 1, 2017. Based on MySQL 5.5.54, including all the bug fixes in it, Percona Server for MySQL 5.5.54-38.6 is now the current stable release in the 5.5 series.

Percona Server for MySQL is open-source and free. You can find release details in the 5.5.54-38.6 milestone on Launchpad. Downloads are available here and from the Percona Software Repositories.

Percona Server for MySQL 5.5.54-38.6 is now available

Latest MySQL Performance Blog posts - February 1, 2017 - 12:46pm

Percona announces the release of Percona Server for MySQL 5.5.54-38.6 on February 1, 2017. Based on MySQL 5.5.54, including all the bug fixes in it, Percona Server for MySQL 5.5.54-38.6 is now the current stable release in the 5.5 series.

Percona Server for MySQL is open-source and free. You can find release details in the 5.5.54-38.6 milestone on Launchpad. Downloads are available here and from the Percona Software Repositories.

Bugs Fixed:
  • Fixed new compilation warnings with GCC 6. Bugs fixed #1641612 and #1644183.
  • CONCURRENT_CONNECTIONS column in the USER_STATISTICS table was showing incorrect values. Bug fixed #728082.
  • Audit Log Plugin when set to JSON format was not escaping characters properly. Bug fixed #1548745.
  • mysqld_safe now limits the use of rm and chown to avoid privilege escalation. chown can now be used only for /var/log directory. Bug fixed #1660265.

Other bugs fixed: #1638897, #1644174, #1644547, and #1644558.

Find the release notes for Percona Server for MySQL 5.5.54-38.6 in our online documentation. Report bugs on the launchpad bug tracker.

Display hostname in alert emails

Lastest Forum Posts - February 1, 2017 - 8:42am
Has anyone got email alerts to display the actual hostname - the name of the host/node that has triggered the alert.

So far I have tried labels and altering the alert name/description, but still not able to see the hostname within an alert email.

Third node does not start MySQL

Lastest Forum Posts - February 1, 2017 - 2:35am

Hello,

Three-node cluster ( Percona XtraDB Cluster (GPL), Release rel37.0, Revision 853, WSREP version 25.11, wsrep_25.11.r4027), running HPELinux (Debian), two nodes runs OK, but the third is unable to start database.

Happened after a file system full, apparently withiut any modification on the previous running configuration (previous system managerresigned and I'm trying to understand the issues).

Here below is the error log.

Any hint about restart succesfully the third node?

Many thanks in advance for any help!

Max

-
State from failing machine:

root@helion-cp1-c1-m1-mgmt:/etc/mysql# cat /var/lib/mysql/grastate.dat
# GALERA saved state
version: 2.1
uuid: 00000000-0000-0000-0000-000000000000
seqno: -1
cert_index:

- Logfile:



170201 08:09:01 mysqld_safe mysqld from pid file /var/run/mysqld/mysqld.pid ended
170201 08:23:36 mysqld_safe Starting mysqld daemon with databases from /var/lib/mysql
170201 08:23:36 mysqld_safe WSREP: Running position recovery with --log_error='/var/lib/mysql/wsrep_recovery.Qbt51O' --pid-file='/var/lib/mysql/helion-cp1-c1-m1-mgmt-recover.pid'
170201 8:23:36 [Warning] Using unique option prefix key_buffer instead of key_buffer_size is deprecated and will be removed in a future release. Please use the full name instead.
170201 8:23:36 [Warning] The syntax '--log-slow-queries' is deprecated and will be removed in a future release. Please use '--slow-query-log'/'--slow-query-log-file' instead.
170201 08:23:40 mysqld_safe WSREP: Recovered position 9c3eced4-70eb-11e6-9bc5-6fd14ff56422:62955021
170201 8:23:40 [Warning] Using unique option prefix key_buffer instead of key_buffer_size is deprecated and will be removed in a future release. Please use the full name instead.
170201 8:23:40 [Warning] The syntax '--log-slow-queries' is deprecated and will be removed in a future release. Please use '--slow-query-log'/'--slow-query-log-file' instead.
170201 8:23:40 [Note] WSREP: wsrep_start_position var submitted: '9c3eced4-70eb-11e6-9bc5-6fd14ff56422:62955021'
170201 8:23:40 [Note] WSREP: Read nil XID from storage engines, skipping position init
170201 8:23:40 [Note] WSREP: wsrep_load(): loading provider library '/usr/lib/libgalera_smm.so'
170201 8:23:40 [Note] WSREP: wsrep_load(): Galera 2.12(r318911d) by Codership Oy <info@codership.com> loaded successfully.
170201 8:23:40 [Note] WSREP: Found saved state: 00000000-0000-0000-0000-000000000000:-1
170201 8:23:40 [Note] WSREP: Reusing existing '/var/lib/mysql//galera.cache'.
170201 8:23:40 [Note] WSREP: Passing config to GCS: base_host = 10.3.1.174; base_port = 4567; cert.log_conflicts = no; debug = no; evs.inactive_check_period = PT0.5S; evs.inactive_timeout = PT15S; evs.join_retrans_period = PT1S; evs.max_install_timeouts = 3; evs.send_window = 4; evs.stats_report_period = PT1M; evs.suspect_timeout = PT5S; evs.user_send_window = 2; evs.view_forget_timeout = PT24H; gcache.dir = /var/lib/mysql/; gcache.keep_pages_size = 0; gcache.mem_size = 0; gcache.name = /var/lib/mysql//galera.cache; gcache.page_size = 128M; gcache.size = 128M; gcs.fc_debug = 0; gcs.fc_factor = 1.0; gcs.fc_limit = 16; gcs.fc_master_slave = no; gcs.max_packet_size = 64500; gcs.max_throttle = 0.25; gcs.recv_q_hard_limit = 9223372036854775807; gcs.recv_q_soft_limit = 0.25; gcs.sync_donor = no; gmcast.listen_addr = tcp://10.3.1.174:4567; gmcast.version = 0; pc.announce_timeout = PT3S; pc.checksum = false; pc.ignore_quorum = false; pc.ignore_sb = false; pc.npvo = false; pc.version = 0; pc.wait_prim = true; pc.wait_prim_timeout = P30S;
170201 8:23:40 [Note] WSREP: Assign initial position for certification: -1, protocol version: -1
170201 8:23:40 [Note] WSREP: wsrep_sst_grab()
170201 8:23:40 [Note] WSREP: Start replication
170201 8:23:40 [Note] WSREP: Setting initial position to 00000000-0000-0000-0000-000000000000:-1
170201 8:23:40 [Note] WSREP: protonet asio version 0
170201 8:23:40 [Note] WSREP: backend: asio
170201 8:23:40 [Note] WSREP: GMCast version 0
170201 8:23:40 [Note] WSREP: (bc5caf9a, 'tcp://10.3.1.174:4567') listening at tcp://10.3.1.174:4567
170201 8:23:40 [Note] WSREP: (bc5caf9a, 'tcp://10.3.1.174:4567') multicast: , ttl: 1
170201 8:23:40 [Note] WSREP: EVS version 0
170201 8:23:40 [Note] WSREP: PC version 0
170201 8:23:40 [Note] WSREP: gcomm: connecting to group 'Vs01zdJ71', peer 'helion-cp1-c1-m1-mgmt:,helion-cp1-c1-m2-mgmt:,helion-cp1-c1-m3-mgmt:'
170201 8:23:40 [Note] WSREP: (bc5caf9a, 'tcp://10.3.1.174:4567') turning message relay requesting on, nonlive peers:
170201 8:23:40 [Note] WSREP: declaring ad7803c2 at tcp://10.3.1.178:4567 stable
170201 8:23:40 [Note] WSREP: declaring e2ca1084 at tcp://10.3.1.177:4567 stable
170201 8:23:40 [Note] WSREP: Node ad7803c2 state prim
170201 8:23:40 [Note] WSREP: gcomm: connected
170201 8:23:40 [Note] WSREP: Changing maximum packet size to 64500, resulting msg size: 32636
170201 8:23:40 [Note] WSREP: Shifting CLOSED -> OPEN (TO: 0)
170201 8:23:40 [Note] WSREP: Opened channel 'Vs01zdJ71'
170201 8:23:40 [Note] WSREP: New COMPONENT: primary = yes, bootstrap = no, my_idx = 1, memb_num = 3
170201 8:23:40 [Note] WSREP: Waiting for SST to complete.
170201 8:23:40 [Note] WSREP: STATE EXCHANGE: Waiting for state UUID.
170201 8:23:40 [Note] WSREP: STATE EXCHANGE: sent state msg: 34aed4c9-e868-11e6-8acf-1eb66790547e
170201 8:23:40 [Note] WSREP: STATE EXCHANGE: got state msg: 34aed4c9-e868-11e6-8acf-1eb66790547e from 0 (helion-cp1-c1-m3-mgmt)
170201 8:23:40 [Note] WSREP: STATE EXCHANGE: got state msg: 34aed4c9-e868-11e6-8acf-1eb66790547e from 2 (helion-cp1-c1-m2-mgmt)
170201 8:23:40 [Note] WSREP: STATE EXCHANGE: got state msg: 34aed4c9-e868-11e6-8acf-1eb66790547e from 1 (helion-cp1-c1-m1-mgmt)
170201 8:23:40 [Note] WSREP: Quorum results:
version = 2,
component = PRIMARY,
conf_id = 16,
members = 2/3 (joined/total),
act_id = 66631754,
last_appl. = -1,
protocols = 0/4/3 (gcs/repl/appl),
group UUID = 9c3eced4-70eb-11e6-9bc5-6fd14ff56422
170201 8:23:40 [Note] WSREP: Flow-control interval: [28, 28]
170201 8:23:40 [Note] WSREP: Shifting OPEN -> PRIMARY (TO: 66631754)
170201 8:23:40 [Note] WSREP: State transfer required:
Group state: 9c3eced4-70eb-11e6-9bc5-6fd14ff56422:66631754
Local state: 00000000-0000-0000-0000-000000000000:-1
170201 8:23:40 [Note] WSREP: New cluster view: global state: 9c3eced4-70eb-11e6-9bc5-6fd14ff56422:66631754, view# 17: Primary, number of nodes: 3, my index: 1, protocol version 3
170201 8:23:40 [Warning] WSREP: Gap in state sequence. Need state transfer.
170201 8:23:40 [Note] WSREP: Running: 'wsrep_sst_xtrabackup --role 'joiner' --address '10.3.1.174' --auth 'sst_user:JgEfDXKG1F' --datadir '/var/lib/mysql/' --defaults-file '/etc/mysql/my.cnf' --parent '22943''
WSREP_SST: [INFO] Streaming with tar (20170201 08:23:40.717)
WSREP_SST: [INFO] Using socat as streamer (20170201 08:23:40.719)
WSREP_SST: [INFO] Evaluating socat -u TCP-LISTEN:4444,reuseaddr stdio | tar xfi - --recursive-unlink -h; RC=( ${PIPESTATUS[@]} ) (20170201 08:23:40.730)
2017/02/01 08:23:40 socat[23111] E bind(12, {AF=2 0.0.0.0:4444}, 16): Address already in use
tar: This does not look like a tar archive
tar: Exiting with failure status due to previous errors
170201 8:23:40 [Note] WSREP: Prepared SST request: xtrabackup|10.3.1.174:4444/xtrabackup_sst
170201 8:23:40 [Note] WSREP: wsrep_notify_cmd is not defined, skipping notification.
170201 8:23:40 [Note] WSREP: Assign initial position for certification: 66631754, protocol version: 2
170201 8:23:40 [Warning] WSREP: Failed to prepare for incremental state transfer: Local state UUID (00000000-0000-0000-0000-000000000000) does not match group state UUID (9c3eced4-70eb-11e6-9bc5-6fd14ff56422): 1 (Operation not permitted)
at galera/src/replicator_str.cpprepare_for_IST():447. IST will be unavailable.
170201 8:23:40 [Note] WSREP: Node 1 (helion-cp1-c1-m1-mgmt) requested state transfer from '*any*'. Selected 0 (helion-cp1-c1-m3-mgmt)(SYNCED) as donor.
170201 8:23:40 [Note] WSREP: Shifting PRIMARY -> JOINER (TO: 66631759)
170201 8:23:40 [Note] WSREP: Requesting state transfer: success, donor: 0
WSREP_SST: [ERROR] Error while getting data from donor node: exit codes: 1 2 (20170201 08:23:40.757)
WSREP_SST: [ERROR] Cleanup after exit with status:32 (20170201 08:23:40.759)
WSREP_SST: [INFO] Removing the sst_in_progress file (20170201 08:23:40.761)
170201 8:23:40 [ERROR] WSREP: Process completed with error: wsrep_sst_xtrabackup --role 'joiner' --address '10.3.1.174' --auth 'sst_user:JgEfDXKG1F' --datadir '/var/lib/mysql/' --defaults-file '/etc/mysql/my.cnf' --parent '22943': 32 (Broken pipe)
170201 8:23:40 [ERROR] WSREP: Failed to read uuid:seqno from joiner script.
170201 8:23:40 [ERROR] WSREP: SST failed: 32 (Broken pipe)
170201 8:23:40 [ERROR] Aborting

170201 8:23:41 [Warning] WSREP: 0 (helion-cp1-c1-m3-mgmt): State transfer to 1 (helion-cp1-c1-m1-mgmt) failed: -1 (Operation not permitted)
170201 8:23:41 [ERROR] WSREP: gcs/src/gcs_group.cpp:long int gcs_group_handle_join_msg(gcs_group_t*, const gcs_recv_msg_t*)():717: Will never receive state. Need to abort.
170201 8:23:41 [Note] WSREP: gcomm: terminating thread
170201 8:23:41 [Note] WSREP: gcomm: joining thread
170201 8:23:41 [Note] WSREP: gcomm: closing backend
170201 8:23:41 [Note] WSREP: gcomm: closed
170201 8:23:41 [Note] WSREP: /usr/sbin/mysqld: Terminated.
Aborted
170201 08:23:41 mysqld_safe mysqld from pid file /var/run/mysqld/mysqld.pid ended
root@helion-cp1-c1-m1-mgmt:/etc/mysql#

Docker Security Vulnerability CVE-2016-9962

Latest MySQL Performance Blog posts - January 31, 2017 - 9:39am

Docker 1.12.6 was released to address CVE-2016-9962. CVE-2016-9962 is a serious vulnerability with RunC.

Quoting the coreos page (linked above):

“RunC allowed additional container processes via runc exec to be ptraced by the pid 1 of the container. This allows the main processes of the container, if running as root, to gain access to file-descriptors of these new processes during the initialization and can lead to container escapes or modification of runC state before the process is fully placed inside the container.”

In short, IF processes run as root inside a container they could potentially break out of the container and gain access over the host.

My recommendation at this time is to apply the same basic security tenants for containers as you would (I hope) for VM and baremetal installs. In other words, ensure you are adhering to a Path of Least Privilege as a best practice and not running as root for conevience’s sake.

Prior to this, we made changes to PMM prior to version 1.0.4 to reduce the number of processes within the container that ran as root. As such, only the processes required to do so run as root. All other processes run as a lower privilege user.

Check here for documentation on PMM, and use the JIRA project to raise bugs (JIRA requires registration).

To comment on running a database within docker, I’ve reviewed the following images

  • percona-server image: I have verified it does not run as root, and runs as a mysql user (for 5.7.16 at least)
  • percona-server-mongodb: I have worked with our teams internally and can confirm that the latest image no longer runs as root (you will to run the latest image, however, to see this change via docker pull)

Please comment below with any questions.

Query Analytic timezone changing

Lastest Forum Posts - January 31, 2017 - 1:44am
Hi!
Currently Query Analytic timezone is set to UTC, in spite of the fact that i use "TZ="Europe/Kiev"(UTC+2) in time of "docker run". Metric Monitore use correct time sone(UTC+2), but not Query Analytic.
Is there some ability to set Query Analytic timezone to UTC+2?

MySQL Sharding Models for SaaS Applications

Latest MySQL Performance Blog posts - January 30, 2017 - 3:16pm

In this blog post, I’ll discuss MySQL sharding models, and how they apply to SaaS application environments.

MySQL is one of the most popular database technologies used to build many modern SaaS applications, ranging from simple productivity tools to business-critical applications for the financial and healthcare industries.

Pretty much any large scale SaaS application powered by MySQL uses sharding to scale. In this blog post, we will discuss sharding choices as they apply to these kinds of applications.

In MySQL, unlike in some more modern technologies such as MongoDB, there is no standard sharding implementation that the vast majority of applications use. In fact, if anything “no standard” is the standard. The common practice is to roll your own sharding framework, as famous MySQL deployments such as Facebook and Twitter have done. MySQL Cluster – the MySQL software that has built-in Automatic Sharding functionality – is rarely deployed (for a variety of reasons). MySQL Fabric, which has been the official sharding framework, has no traction either.

When sharding today, you have a choice of rolling your own system from scratch, using comprehensive sharding platform such as Vitess or using a proxy solution to assist you with sharding. For proxy solutions, MySQL Router is the official solution. But in reality, third party solutions such as open source ProxySQL, commercial ScaleArc and semi-commercial (BSL)  MariaDB MaxScale are widely used. Keep in mind, however, that traffic routing is only one of the problems that exist in large scale sharding implementations.

Beneath all these “front end” choices for sharding on the application database connection framework or database proxy, there are some lower level decisions that you’ve got to make. Namely, around how your data is going to be led out and organized on the MySQL nodes.

When it comes to SaaS applications, at least one answer is simple. It typically makes sense to shard your data by “customer” or “organization” using some sort of mapping tables. In the vast majority of cases, single node (or replicated cluster) should be powerful enough to handle all the data and load coming from each customer.

What Should I Ask Myself Now?

The next set questions you should ask yourself are around your SaaS applications:

  • How much revenue per customer are you generating?
  • Do your customers (or regulations) require data segregation?
  • Are all the customers about the same, or are there outliers?
  • Are all your customers running the same database schema?

I address the answers in the sections below.

How Much Revenue?

How much revenue per customer you’re generating is an important number. It defines how much infrastructure costs per customer you can afford. In the case of “freemium” models, and customers generating less than $1 a month an average, you might need to ensure low overhead per customer (even if you have to compromise on customer isolation).

How much revenue per customer you’re generating is an important number. It defines how much infrastructure costs per customer you can afford. In the case of “freemium” models, and customers generating less than $1 a month an average, you might need to ensure low overhead per customer (even if you have to compromise on customer isolation).

Typically with low revenue customers, you have to co-locate the data inside the same MySQL instance (potentially even same tables). In the case of high revenue customers, isolation in separate MySQL instances (or even containers or virtualized OS instances) might be possible.

Data Segregation?

Isolation is another important area of consideration. Some enterprise customers might require that their data is physically separate from others. There could also be government regulations in play that require customer data to be stored in a specific physical location. If this is the case, you’re looking at completely dedicated customer environments. Or at the very least, separate database instances (which come with additional costs).

Customer Types?

Customer size and requirements are also important. A system designed to handle all customers of approximately the same scale (for example, personal accounting) is going to be different than if you are in the business of blog hosting. Some blogs might be 10,000 times more popular than the average.

Same Database Schema?

Finally, there is a there is the big question of whether all your customers are running the same database schema and same software version. If you want to support different software versions (if your customers require a negotiated maintenance window for software upgrades, for example) or different database schemas (if the schema is dependent on the custom functionality and modules customers might use, for example), keeping such customers in different MySQL schemas make sense.

Sharding Models

This gets us to the following sharding isolation models, ranging from lowest to highest:

  • Customers Share Schemas. This is the best choice when you have very large numbers of low-revenue customers. In this case, you would map multiple customers to the same set of tables, and include something like a customer_id field in them to filter customer data. This approach minimizes customer overhead and reduces customer isolation. It’s harder to backup/restore data for individual customers, and it is easier to introduce coding mistakes that can access other customers data. This method does not mean there is only one schema, but that there is a one-to-many relationship between schemas and customers.  For example, you might have 100 schema’s per MySQL instance, each handling 1000 to 10000 customers (depending on the application). Note that with a well-designed sharding implementation, you should be able to map customers individually to schemas. This allows you to have key customer data stored in dedicated schemas, or even on dedicated nodes.
  • Schema per Customer. This is probably the most common sharding approach in MySQL powered SaaS applications. Especially ones that have substantial revenue ($10+ per month / per customer). In this model, each customer’s data is stored in its own schema (database). This makes it very easy to backup/restore individual customers. It allows customers to have different schemas (i.e., add custom tables). It also allows them to run different versions of the application if desired. This approach allows the application server to use different MySQL users connecting on behalf of different customers, which adds an extra level of protection from accidental (or intentional) access of data that belongs to different customers. The schema per customer approach also makes it easier to move the shards around, and limits maintenance impact. The downside of this approach is higher overhead. It also results in a large number of tables per instance, and potentially larger numbers of files (which can be hard to manage).
  • Database Instance per Customer. You achieve even better isolation by having a MySQL instance per customer. This approach, however, increases overhead even further. The recent rise of light virtualization technologies and containers has reduced its usage.
  • OS Instance/Container per Customer. This approach allows you to improve isolation even further. It can be used for any customer, but can also be applied to selected customers in a model that uses Schema per Customer model for a majority of them.  Dedicated OS Instance, with improved isolation and better performance SLAs, might be a feature of some premium customer tiers. This method not only allows better isolation, but it also let’s you handle outliers better. You might chose to run a majority of your customers on the hardware (or cloud instance) that has best price/performance numbers, and also place some of the larger customers on the highest performance nodes.
  • Environment per customer. Finally, if you take this all the way you can build completely separate environments for customers. This includes databases, application servers and other required components. This is especially useful if you need to deploy the application close to the customer – which includes the appliance model, or deployment in the customer’s data center or cloud provider. This also allows you to accommodate customers if their data must be stored in a specific location. This is often due to government regulations. It is worth noting that many SaaS applications, even if they do not quite have one environment per customer, have multiple independent environments. These are often hosted in different locations or availability zones. Such setups allow you to reduce the impact of large-scale failures to only a portion of your customers. This avoids overloading your customer service group and allowing the operational organization to focus on repairing smaller environments.

The farther you go down this route – from the shared schema to an environment per customer – the more important is to have a high level of automation. With a shared schema, you often can get by with little automation (and some environments manually set up) and all the schema’s pre-created. If customer sign up requires setting up dedicated database instance or the whole environment, manual implementation doesn’t scale. For this type of setup, you need state-of-the-art automation and orchestration.

Conclusion

I hope this helps you to understand your options for MySQL sharding models. Each of the different sharding models for SaaS applications powered by MySQL have benefits and drawbacks. As you can see, many of these approaches require you to work with a large number of tables in the MySQL – this will be the topic of one of my next posts!

ERROR qan-analyzer driver: bad connection

Lastest Forum Posts - January 30, 2017 - 10:40am
Hi!
After starting "pmm-admin start --all" everything works fine, for a few time. After 2-3 hours approximately, Query Analytics stop to show data. We have 2 servers for now, and they both have the same problem.
In /var/log/pmm-mysql-queries-0.log we can see:

[mysql] 2017/01/30 20:29:09 packets.go:59: unexpected EOF
[mysql] 2017/01/30 20:29:09 packets.go:386: busy buffer
2017/01/30 20:29:09.538585 ERROR qan-analyzer-1342087d driver: bad connection
2017/01/30 20:30:00.001315 WARNING qan-analyzer-1342087d-worker Interval out of sequence: got 186, expected 182
2017/01/30 20:30:08.733680 ERROR qan-analyzer-1342087d-worker Got class twice: registry_dev2 e1fecd37897b7375d76acae411ed0f5b
2017/01/30 20:31:00.011321 WARNING qan-analyzer-1342087d Skipping interval '187 2017-01-30 18:30:00 UTC to 2017-01-30 18:31:00 UTC (0-0)' because interval '186 2017-01-30 18:29:00 UTC to 2017-01-30 18:30:00 UTC (0-0)' is still being parsed
2017/01/30 20:32:00.005720 WARNING qan-analyzer-1342087d Skipping interval '188 2017-01-30 18:31:00 UTC to 2017-01-30 18:32:00 UTC (0-0)' because interval '186 2017-01-30 18:29:00 UTC to 2017-01-30 18:30:00 UTC (0-0)' is still being parsed
2017/01/30 20:33:00.001729 WARNING qan-analyzer-1342087d Skipping interval '189 2017-01-30 18:32:00 UTC to 2017-01-30 18:33:00 UTC (0-0)' because interval '186 2017-01-30 18:29:00 UTC to 2017-01-30 18:30:00 UTC (0-0)' is still being parsed
[mysql] 2017/01/30 20:33:28 packets.go:59: unexpected EOF
[mysql] 2017/01/30 20:33:28 packets.go:386: busy buffer
[mysql] 2017/01/30 20:33:28 connection.go:307: invalid connection
2017/01/30 20:33:28.778027 ERROR qan-analyzer-1342087d driver: bad connection
2017/01/30 20:34:00.003532 WARNING qan-analyzer-1342087d-worker Interval out of sequence: got 190, expected 187
2017/01/30 20:34:04.971836 ERROR qan-analyzer-1342087d-worker Got class twice: registry_dev2 e1fecd37897b7375d76acae411ed0f5b

After "pmm-admin restart --all" there is no errors for some time, Query Analytics works fine. But not for long. Same errors.

Server and clients was reinstalled by documentation 3 times. No effect.
How can i fix this problem?

MariaDB ColumnStore

Latest MySQL Performance Blog posts - January 30, 2017 - 9:29am

Last month, MariaDB officially released MariaDB ColumnStore, their column store engine for MySQL. This post discusses what it is (and isn’t), why it matters and how you can approach a test of it.

What is ColumnStore?

ColumnStore is a storage engine that turns traditional MySQL storage concepts on their head. Instead of storing the data by row, a column store stores the data by column (obviously). This provides advantages for certain types of data, and certain types of queries run against that data. See my previous post for more details on column-based storage systems.

ColumnStore is a fork of InfiniDB and carries forward many of the concepts behind that product. InfiniDB ceased operations in 2014. With the front end managed through MariaDB, you get access to all of the expected security and audit options of MariaDB. MariaDB designed ColumnStore as a massively parallel database, working best in an environment with multiple servers. This is somewhat different than a traditional row store database.

ColumnStore stores columnar data in a concept called an “extent.” An extent contains a range of values for a single column. Each extent contains no more than 8 million values. It stores additional values in a new extent. The extents for a single column get distributed across the database nodes, known as “Performance Modules” in ColumnStore. It stores each unique extent on more than one node, thus providing data redundancy and removing the need for replication. If a node is down, and it contains an extent needed for a query, that same extent is found on another node in the environment. This data redundancy also provides a high availability environment.

The query engine determines which extents process query requests. Since the data in an extent is often preordered (time series data, for example), many queries can ignore individual extents since they cannot contain any data needed for the query. If we are only looking for data from February 2017, for example, extents containing data outside of that range get ignored. However, if a query requires data from many or all extents on a single column, the query takes much longer to complete.

Unlike some traditional column store vendors, that take an all or nothing approach to storage, MariaDB decided to go with a mixed concept. In a MariaDB MySQL database, you can mix traditional InnoDB storage with the new ColumnStore storage, just like you used to mix InnoDB and MyISAM. This presents some nice options, not the least of which is that it provides a way to “dip your toe” into the world of column stores. On the other hand, it could lead to people using the ColumnStore engine in non-optimal ways. Also, the differences in what is considered optimal architecture between these two storage options make it hard to see how this plays out in the real world.

Data Definition

As discussed in the earlier post, column storage works great for specific types of data and queries. It is important that your data definitions are as tight as possible, and that your queries are appropriate for column-based data.

Many people set their field definition as VARCHAR(256) when setting up a new database. They might not know what type of data gets stored in the new field. This broad definition allows you to store whatever you throw at the database. The negative effect for row store is that it can cause over-allocation of storage – but it only has a minimal effect on queries.

In a column store, the field definition can drive decisions about the compression methods for storing the data, along with sorting implications. Columnar data can use storage more efficiently than a row store, since the data for a single column is well-defined. This leads to selecting the best compression algorithm for the data. If that data is poorly defined, the selected compression algorithm might not be the best for the data.

Sorting is also a problem in a column store when the data types are not well-defined. We’ve all seen integer or date data that is sorted alphabetically. While it can be annoying, we can still adjust to that sorting method to find what we need. Since a column store is often used to perform analytical queries over a range of data, this poorly-sorted data can present a bigger problem. If you specify a column to be VARCHAR and only include date information, that data is sorted alphabetically. The same column defined as DATE causes the data to be sorted by date. This chart shows the difference (date format is mm/dd/yy)

Alphabetic Sort Date Sort 01/01/17 01/01/17 01/11/17 01/02/17 01/02/17 01/04/17 01/21/17 01/11/17 01/4/17 01/21/17 11/01/17 02/01/17 11/02/17 11/01/17 02/01/17 11/02/17

 

Imagine running a query over a range of dates (requesting all activity in the months of January and February 2017, for example). In the alphabetic sort, this requires working through the whole file, since the data for November shows up between the data for January and February. In the date sort, the query only reads the until the end of February. We know there can be no more matching data after that. The alphabetic sort leads to more I/O, more query time and less happiness on the part of the user.

Why Should You Care About ColumnStore?

The first reason is that it allows you to try out column storage without doing a massive shift in technology and with minimal effort. By setting up some tables in a MariaDB database to use the ColumnStore engine, you can benefit from the storage efficiencies and faster query capabilities, provided that the data you’ve selected for this purpose is sound. This means that the data definitions should be tight (always a good plan anyway), and the queries should be more analytical than transactional. For a purely transactional workflow, a row store is the logical choice. For a purely analytical workflow, a column store is the logical choice. ColumnStore allows you to easily mix the two storage options so that you can have the best match possible. It is still important to know what type of workflow you’re dealing with, and match the storage engine to that need.

Another solid reason is that it is a great fit if you are already doing analysis over massive amounts of data. Any column store shines when asked to look at relatively few columns of data (ideally the column or two that are being aggregated and other columns to locate and group the data). If you are already running these types of queries in MySQL, ColumnStore would likely be a good fit.

But There Be Dragons!

As with any new technology, ColumnStore might not be a good fit for everyone. Given that you can mix and match your storage engines, with ColumnStore for some tables and InnoDB for others, it can be tempting to just go ahead with a ColumnStore test doing things the same way you always did in the past. While this still yields results, those results might not be a true test of the technology. It’s like trying to drive your minivan the same way you used to drive your sports car. “Hey, my Alfa Romeo never flipped over taking these turns at high speed!”

To effectively use ColumnStore, it’s important to match it to a proper analytical workload. This means that you will likely do more bulk loading into these tables, since there is additional overhead in writing the data out into the column files. The overall workflow should be more read-intensive. The queries should only look for data from a small set of fields, but can span massive amounts of data within a single column. In my earlier post, there’s also a discussion about normalization of data and how denormalizing data is more common in columnar databases.

You should address these issues in your testing for a valid conclusion.

The minimum specifications for ColumnStore also point to a need for a more advanced infrastructure than is often seen for transactional data. This is to support batch loading, read intensive workloads and possibly different ETL processes for each type of data. In fact, MariaDB states in the installation documentation for ColumnStore that it must be completed as a new installation of MariaDB. You must remove any existing installations of MariaDB or MySQL before installing the ColumnStore-enabled RPM on a system.

Is It Right for Me?

ColumnStore might fit well into your organization. But like haggis, it’s not for everyone. If you need analytical queries, it is a great option. If your workload is more read-intensive, it could still work for you. As we move to a more Internet of Things (IoT) world, we’re likely to see a need for more of this type of query work. In order to accurately present each user with the best possible Internet experience, we might want to analyze their activities over spans of time and come up with the best match for future needs.

Seriously consider if making the move to ColumnStore is right for you. It is newer software (version 1.0.6, the first GA version, was released on December 14, 2016, and 1.0.7 was released on January 23, 2017), so it might go through changes as it matures. Though a new product, it is based on InfiniDB concepts (which are somewhat dated). MariaDB has lots of plans for additional integrations and support for ancillary products that are absent in the current release.

MariaDB took a huge step forward with ColumnStore. But do yourself a favor and consider whether it is right for you before testing it out. Also, make sure that you are not trying to force your current workflow into the column store box. Kids know that we cannot put a square peg in a round hole, but we adults often try to do just that. Finding the right peg saves you lots of time, hassle and annoyance.

Warnings in Error log on a Slave/Master node

Lastest Forum Posts - January 30, 2017 - 5:56am
Hello- We have a 3-node Percona XtraDB (5.6.34) cluster set up, with a slave server hanging off of one of the nodes. We also have this slave server (also running XtraDB 5.6.34) set up as a master as we use it to replicate to an off-site DR Percona server. We noticed that the below warning started showing up in the log on this slave server last week. The warning shows up numerous times every second. I have not been able to find much online in regards to this warning. I see the warning mentions WSREP, which has to do with Galera, but this slave is not part of the cluster. I have verified that the replication is running fine on both this slave, as well as the DR slave, as I see current data on both:

=> Skipping replication
2017-01-30 08:47:05 14855 [Warning] WSREP: SQL statement was ineffective, THD: 2, buf: 276
schema: (null)
QUERY: (null)
=> Skipping replication
2017-01-30 08:47:05 14855 [Warning] WSREP: SQL statement was ineffective, THD: 2, buf: 329
schema: (null)
QUERY: (null)
=> Skipping replication
2017-01-30 08:48:08 14855 [Warning] WSREP: SQL statement was ineffective, THD: 2, buf: 407
schema: (null)
QUERY: (null)

If anyone has specific info on what this warning means and how to fix it, I would appreciate the feedback- thanks!

Ron

Percona Software News and Roadmap Update with CEO Peter Zaitsev: Q1 2017

Latest MySQL Performance Blog posts - January 27, 2017 - 2:06pm

This blog post is a summary of the webinar Percona Software News and Roadmap Update – Q1 2017 given by Peter Zaitsev on January 12, 2017.

Over the last few months, I’ve had the opportunity to meet and talk with many of Percona’s customers. I love these meetings, and I always get a bunch of questions about what we’re doing, what our plans are and what releases are coming.

I’m pleased to say there is a great deal going on at Percona, and I thought giving a quick talk about our current software and services, along with our plans, would provide a simple reference for many of these questions.

A full recording of this webinar, along with the presentation slide deck, can be found here.

Percona Solutions and Services

Let me start by laying out Percona’s company purpose:

To champion unbiased open source database solutions.

What does this mean? It means that we write software to offer you better solutions, and we use the best of what software and technology exist in the open source community.

Percona stands by a set of principles that we feel define us as a company, and are a promise to our customers:

  • 100% free and open source software
  • Focused on finding solution to maximize your success
  • Open source database strategy consulting and implementation
  • No vendor lock-in required

We offer trusted and unbiased expert solutions, support and resource in a broad software ecosystem, including:

We also have specialization options for PaaS, IaaS, and SaaS solutions like Amazon Web Services, OpenStack, Google Cloud Platform, OpenShift, Ceph, Docker and Kubernetes.

Percona’s immediate business focus includes building long-term partnership relationships through support and managed services.

The next few sections detail our current service offerings, with some outlook on our plans.

98% Customer Satisfaction Rating

Over the last six months, Percona has consistently maintained a 98% Customer Satisfaction Rating!

Customer Success Team

Our expanded Customer Success Team is here to ensure you’re getting most out of your Percona Services Subscription.

Managed Services Best Practices

  • Unification based on best practices
  • Organization changes to offer more personal service
  • Increased automation

Ongoing Services

Consulting and Training. Our consulting and training services are available to assist you with whatever project or staff needs you have.

  • Onsite and remote
  • 4 hours to full time (weeks or months)
  • Project and staff augmentation

Advanced HA Included with Enterprise and Premier Support. Starting this past Spring, we included advance high availability (HA) support as part of our Enterprise and Premier support tiers. This advanced support includes coverage for:

  • Percona XtraDB Cluster
  • MariaDB Galera Cluster
  • Galera Cluster for MySQL
  • Upcoming MySQL group replication
  • Upcoming MySQL Innodb Cluster

Enterprise Wide Support Agreements. Our new Enterprise Wide Support option allows you to buy per-environment support coverage that covers all of the servers in your environment, rather than on a per-server basis. This method of support can save you money, because it:

  • Covers both “MySQL” and “MongoDB”
  • Means you don’t have to count servers
  • Provides highly customized coverage

 

Simplified Support Pricing. Get easy to understand support pricing quickly.

To discuss how Percona Support can help your business, please call us at +1-888-316-9775 (USA),
+44 203 608 6727 (Europe), or have us contact you.

New Percona Online Store – Easy to Buy, Pay Monthly

Percona Software

Below are the latest and upcoming features in Percona’s software. All of Percona’s software adheres to the following principles:

  • 100% free and open source
  • No restricted “Enterprise” version
  • No “open core”
  • No BS-licensing (BSL)
Percona Server for MySQL 5.7

Overview

  • 100% Compatible with MySQL 5.7 Community Edition
  • 100% Free and Open Source
  • Includes Alternatives to Many MySQL Enterprise Features
  • Includes TokuDB Storage Engine
  • Focus on Performance and Operational Visibility

Latest Improvements

Features about to be Released 

  • Integration of TokuDB and Performance Schema
  • MyRocks integration in Percona Server
  • MySQL Group Replication
  • Starting to look towards MySQL 8
Percona XtraBackup 2.4

Overview

  • #1 open source binary hot backup solution for MySQL
  • Alternative to MySQL Enterprise backup
  • Parallel backups, incremental backups, streaming, encryption
  • Supports MySQL, MariaDB, Percona Server

New Features

  • Support SHA256 passwords and secure connection to server
  • Improved Security (CVE-2016-6225)
  • Wrong passphrase detection
Percona Toolkit

Overview

  • “Swiss Army Knife” of tools
  • Helps DBAs be more efficient
  • Helps DBAs make fewer mistakes
  • Supports MySQL, MariaDB, Percona Server, Amazon RDS MySQL

New Features

  • Improved fingerprinting in pt-query-digest
  • Pause file for pt-online-schema-change
  • Provide information about transparent huge pages

Coming Soon

  • Working towards Percona Toolkit 3.0 release
  • Comprehensive support for MongoDB
  • New tools are now implemented in Go
Percona Server for MongoDB 3.2

Overview

  • 100% compatible with MongoDB 3.2 Community Edition
  • 100% open source
  • Alternatives for many MongoDB Enterprise features
  • MongoRocks (RocksDB) storage engine
  • Percona Memory Engine

New

  • Percona Server for MongoDB 3.2 – GA
  • Support for MongoRocks storage engine
  • PerconaFT storage engine depreciated
  • Implemented Percona Memory Engine

Coming Soon

  • Percona Server for MongoDB 3.4
  • Fully compatible with MongoDB 3.4 Community Edition
  • Updated RocksDB storage engine
  • Universal hot backup for WiredTiger and MongoRocks
  • Profiling rate limiting (query sampling)
Percona Memory Engine for MongoDB

Benchmarks

Percona Memory Engine for MongoDB® is a 100 percent open source in-memory storage engine for Percona Server for MongoDB.

Based on the in-memory storage engine used in MongoDB Enterprise Edition, WiredTiger, Percona Memory Engine for MongoDB delivers extremely high performance and reduced costs for a variety of use cases, including application cache, sophisticated data manipulation, session management and more.

Below are some benchmarks that we ran to demonstrate Percona Memory Engine’s performance.

Percona XtraDB Cluster 5.7

Overview

  • Based on Percona Server 5.7
  • Easiest way to bring HA in your MySQL environment
  • Designed to work well in the cloud
  • Multi-master replication with no conflicts
  • Automatic node provisioning for auto-scaling and self-healing

Goals

  • Brought PXC development in-house to server our customers better
  • Provide complete clustering solution, not set of LEGO pieces
  • Improve usability and ease of use
  • Focus on quality

Highlights

  • Integrated cluster-aware load balancer with ProxySQL
  • Instrumentation with Performance Schema
  • Support for data at rest encryption (InnoDB tablespace encryption)
  • Your data is safe by default with “strict mode” – prevents using features that do not work correctly
  • Integration with Percona Monitoring and Management (PMM)

New in Percona XtraDB Cluster 5.7

  • One option to secure all network communication: pxc-encrypt-cluster-traffic
  • Zero downtime maintenance with ProxySQL and Maintenance Mode
Percona Monitoring and Management

Overview

  • Comprehensive database-focused monitoring
  • 100% open source, roll-your-own solution
  • Easy to install and use
  • Supports MySQL and MongoDB
  • Version 1.0 focuses on trending and query analyses
  • Management features to come

Examples of PMM Screens

What queries are causing the load?

Why are they causing this load?

How to fix them:

System information:

What happens on OS and hardware level:

As well as the database level:

New in Percona Monitoring and Management

  • Continuing to improve and expand dashboards with every release
  • Includes Grafana 4.0 (with basic Alerting)
  • SSL support for server-agent communications
  • Supports authentication for server-agent communication
  • Added support for Amazon RDS
  • Reduced space consumption by using advanced compression

Coming Soon 

  • PMM server available as AMI and Virtual Appliance image
  • Better MongoDB dashboards
  • Continuing work on dashboards Improvement
  • Query analytics application refinements
  • Short term continuing focus on monitoring functionality

Check out the Demo

Percona Live Open Source Database Conference 2017 is right around the corner!

The Percona Live Open Source Database Conference is the premier event for the diverse and active open source database community, as well as businesses that develop and use open source database software. The conferences have a technical focus with an emphasis on the core topics of MySQL, MongoDB, PostgreSQL and other open source databases. Tackling subjects such as analytics, architecture and design, security, operations, scalability and performance, Percona Live provides in-depth discussions for your high-availability, IoT, cloud, big data and other changing business needs. This conference is an opportunity to network with peers and technology professionals by bringing together accomplished DBA’s, system architects and developers from around the world to share their knowledge and experience – all to help you learn how to tackle your open source database challenges in a whole new way

This conference has something for everyone!

Register now and get the early bird rate, but hurry prices go up Jan 31st.

Sponsorship opportunities are available as well. Become a Percona Live Sponsor, download the prospectus here.

 

Hiding example queries in qan

Lastest Forum Posts - January 27, 2017 - 11:57am
I'm trying to figure out how to hide example queries in qan for all hosts. I unchecked the "Send real query examples" option in the management gui but qan is still showing them.

Ideally I'd like to do this on a client-by-client basis in the config.yml file...is this possible?

PMM grafana alert config setup

Lastest Forum Posts - January 27, 2017 - 11:52am
Hi,
I wanted to set up PMM alerts. I couldn't find a way to set up the alert alarming. I followed a link by Percona,
https://www.percona.com/blog/2017/01..._hsmi=41494144

The problem is I couldn't find grafana config file in my EC2 instance. Any help is appreciated.

When MySQL Lies: Wrong seconds_behind_master with slave_parallel_workers > 0

Latest MySQL Performance Blog posts - January 27, 2017 - 11:03am

In today’s blog, I will show an issue with seconds_behind_master that one of our clients faced when running slave_parallel_works > 0. We found out that the reported seconds_behind_master from SHOW SLAVE STATUS was lying. To be more specific, I’m talking about bugs #84415 and #1654091.

The Issue

MySQL will not report the correct slave lag if you have slave_parallel_workers> 0. Let’s show it in practice.

I’ll use MySQL Sandbox to speed up one master and two slaves on MySQL version 5.7.17, and sysbench to populate the database:

# Create sandboxes make_replication_sandbox /path/to/mysql/5.7.17 # Create table with 1.5M rows on it sysbench --test=/usr/share/sysbench/tests/db/oltp.lua --mysql-host=localhost --mysql-user=msandbox --mysql-password=msandbox --mysql-socket=/tmp/mysql_sandbox20192.sock --mysql-db=test --oltp-table-size=1500000 prepare # Add slave_parallel_workers=5 and slave_pending_jobs_size_max=1G" on node1 echo "slave_parallel_workers=5" >> node1/my.sandbox.cnf echo "slave_pending_jobs_size_max=1G" >> node1/my.sandbox.cnf node1/restart

Monitor Replication lag via SHOW SLAVE STATUS:

for i in {1..1000}; do ( node1/use -e "SHOW SLAVE STATUSG" | grep "Seconds_Behind_Master" | awk '{print "Node1: " $2}' & sleep 0.1 ; node2/use -e "SHOW SLAVE STATUSG" | grep "Seconds_Behind_Master" | awk '{print "Node2: " $2}' & ); sleep 1; done

On a separate terminal, DELETE some rows in the test.sbtest1 table on the master, and monitor the above output once the master completes the delete command:

DELETE FROM test.sbtest1 WHERE id > 100;

Here is a sample output:

master [localhost] {msandbox} (test) > DELETE FROM test.sbtest1 WHERE id > 100; Query OK, 1499900 rows affected (46.42 sec) . . . Node1: 0 Node2: 0 Node1: 0 Node2: 48 Node1: 0 Node2: 48 Node1: 0 Node2: 49 Node1: 0 Node2: 50 . . . Node1: 0 Node2: 90 Node1: 0 Node2: 91 Node1: 0 Node2: 0 Node1: 0 Node2: 0

As you can see, node1 (which is running with slave_parallel_workers = 5) doesn’t report any lag.

The Workaround

We can workaround this issue by querying performance_schema.threads:

SELECT PROCESSLIST_TIME FROM performance_schema.threads WHERE NAME = 'thread/sql/slave_worker' AND (PROCESSLIST_STATE IS NULL or PROCESSLIST_STATE != 'Waiting for an event from Coordinator') ORDER BY PROCESSLIST_TIME DESC LIMIT 1;

Let’s modify our monitoring script, and use the above query to monitor the lag on node1:

for i in {1..1000}; do ( node1/use -BNe "SELECT PROCESSLIST_TIME FROM performance_schema.threads WHERE NAME = 'thread/sql/slave_worker' AND (PROCESSLIST_STATE IS NULL or PROCESSLIST_STATE != 'Waiting for an event from Coordinator') ORDER BY PROCESSLIST_TIME DESC LIMIT 1 INTO @delay; SELECT IFNULL(@delay, 0) AS 'lag';" | awk '{print "Node1: " $1}' & sleep 0.1 ; node2/use -e "SHOW SLAVE STATUSG" | grep "Seconds_Behind_Master" | awk '{print "Node2: " $2}' & ); sleep 1; done

master [localhost] {msandbox} (test) > DELETE FROM test.sbtest1 WHERE id > 100; Query OK, 1499900 rows affected (45.21 sec) Node1: 0 Node2: 0 Node1: 0 Node2: 0 Node1: 45 Node2: 45 Node1: 46 Node2: 46 . . . Node1: 77 Node2: 77 Node1: 78 Node2: 79 Node1: 0 Node2: 80 Node1: 0 Node2: 81 Node1: 0 Node2: 0 Node1: 0 Node2: 0

Please note that in our query to performance_schema.threads, we are filtering PROCESSLIST_STATE “NULL” and “!= Waiting for an event from Coordinator”. The correct state is “Executing Event”, but it seems like it doesn’t correctly report that state (#84655).

Summary

MySQL parallel replication is a nice feature, but we still need to make sure we are aware of any potential issues it might bring. Most monitoring systems use the output of SHOW SLAVE STATUS to verify whether or not the slave is lagging behind the master. As shown above, it has its caveats.

As always, we should test, test and test again before implementing any change like this in production!

Percona Live Featured Tutorial with Frédéric Descamps — MySQL InnoDB Cluster & Group Replication in a Nutshell: Hands-On Tutorial

Latest MySQL Performance Blog posts - January 26, 2017 - 3:58pm

Welcome to another post in the series of Percona Live featured tutorial speakers blogs! In these blogs, we’ll highlight some of the tutorial speakers that will be at this year’s Percona Live conference. We’ll also discuss how these tutorials can help you improve your database environment. Make sure to read to the end to get a special Percona Live 2017 registration bonus!

In this Percona Live featured tutorial, we’ll meet Frédéric Descamps, MySQL Community Manager at Oracle. Frédéric is probably better known in the community as “LeFred” (Twitter: @lefred)! His tutorial is MySQL InnoDB Cluster and Group Replication in a Nutshell: Hands-On Tutorial (along with  Part 2). Frédéric is delivering this talk with Percona’s MySQL Practice Manager Kenny Gryp. Attendees will get their hands on virtual machines and migrate standard Master/Slave architecture to the new MySQL InnoDB Cluster (native Group Replication) with minimal downtime. I had a chance to speak with Frédéric and learn a bit more about InnoDB Cluster and Group Replication:

Percona: How did you get into database technology? What do you love about it?

Frédéric: I started with SQL on VMS and DBASE during my IT courses. I wrote my thesis on SQLServer replication. To be honest, the implementation at the time wasn’t particularly good. At the same time, I enjoyed hacking a Perl module that allowed you to run SQL queries against plain text files. Then I worked as a Progress developer for MFG/Pro (a big customized ERP). When I decided to work exclusively for an open source company, I was managing more and more customers’ databases in MySQL (3.23 and 4.x), so my colleagues and I took MySQL training. It was still MySQL AB at that time. I passed my MySQL 4.1 Core and Professional Certification, and I ended up delivering MySQL Training for MySQL AB too. Some might also remember that I worked for a company called Percona for a while, before moving on to Oracle!

Percona: Your and Kenny’s tutorial is called “MySQL InnoDB Cluster & Group Replication in a nutshell: hands-on tutorial.” Why would somebody want to migrate to this technology?

Frédéric: The main reason to migrate to MySQL InnoDB is to achieve high availability (HA) easily for your MySQL database, while still maintaining performance.

Thanks to  MySQLShell’s adminAPI, you can create a cluster in less than five minutes. All the management can be done remotely, with just some shell commands. Additionally, for Group Replication our engineers have leveraged existing standard MySQL infrastructures (GTIDs, Multi-Source Replication, Multi-threaded Slave Applier, Binary Logs, etc.), which are already well known by the majority of MySQL DBAs.

Percona: How can moving to a high availability environment help businesses?

Frédéric: Time is money! Many businesses can’t afford downtime anymore. Having a reliable HA solution is crucial for businesses on the Internet. Expectations have changed: users want this to be natively supported inside the database technology versus externally. For example, when I started to work in IT, it was very common to have several maintenance windows during the night. But currently, and almost universally, the customer base is spread worldwide. Any time is during business hours somewhere in the world!

Percona: What do you want attendees to take away from your tutorial session? Why should they attend?

Frédéric: I think that current HA solutions are too complex to setup and manage. They use external tools. In our tutorial, Kenny and I will demonstrate how MySQL InnoDB Cluster, being an internal implementation, is extremely easy to use. We will also cover some scenarios where things go wrong, and how to deal with them. Performance and ease-of-use were two key considerations in the design of InnoDB Cluster.

Percona: What are you most looking forward to at Percona Live?

Frédéric: Like every time I’ve attended, my main goal is to bring to the audience all the new and amazing stuff we are implementing in MySQL. MySQL has evolved quickly these last few years, and we don’t really plan to slow down. I also really enjoy the feedback from users and other MySQL professionals. This helps focus us on what really matters for our users. And finally, it’s a great opportunity to re-connect with ex-colleagues and friends.

You can find out more about Frédéric Descamps and his work with InnoDB Cluster at his Twitter handle @lefredRegister for Percona Live Data Performance Conference 2017, and see Frédéric and Kenny present their MySQL InnoDB Cluster and Group Replication in a Nutshell: Hands-On Tutorial talk. Use the code FeaturedTalk and receive $30 off the current registration price!

Percona Live Data Performance Conference 2017 is the premier open source event for the data performance ecosystem. It is the place to be for the open source community as well as businesses that thrive in the MySQL, NoSQL, cloud, big data and Internet of Things (IoT) marketplaces. Attendees include DBAs, sysadmins, developers, architects, CTOs, CEOs, and vendors from around the world.

The Percona Live Data Performance Conference will be April 24-27, 2017 at the Hyatt Regency Santa Clara & The Santa Clara Convention Center.

FEATURE REQUEST (ban changes sql_mode on session level)

Lastest Forum Posts - January 26, 2017 - 11:30am
We have global variable sql_mode set to STRICT_ALL_TABLES(mysqld.cnf).
But someone changes this variable on session level, and from time to time we have problem with data in our database.
And there is no ability to ban changing sql_mode on session level.
I think many others have same problem, and it could be good decision to have some mysqld.cnf parameter(global variable) than allow to ban changing sql_mode on session level.
Actually, great decision is to have ability to ban setting session variables listed in some global variable, for example
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