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Uptime of a MariaDB Galera Cluster

Fri, 2019-03-15 17:58

A while ago somebody on Google Groups asked for the Uptime of a Galera Cluster. The answer is easy... Wait, no! Not so easy... The uptime of a Galera Node is easy (or not?). But Uptime of the whole Galera Cluster?

My answer then was: "Grep the error log." My answer now is still: "Grep the error log." But slightly different:

$ grep 'view(view_id' * 2019-03-07 16:10:26 [Note] WSREP: view(view_id(PRIM,0e0a2851,1) memb { 2019-03-07 16:14:37 [Note] WSREP: view(view_id(PRIM,0e0a2851,2) memb { 2019-03-07 16:16:23 [Note] WSREP: view(view_id(PRIM,0e0a2851,3) memb { 2019-03-07 16:55:56 [Note] WSREP: view(view_id(NON_PRIM,0e0a2851,3) memb { 2019-03-07 16:56:04 [Note] WSREP: view(view_id(PRIM,6d80bb1a,5) memb { 2019-03-07 17:00:28 [Note] WSREP: view(view_id(NON_PRIM,6d80bb1a,5) memb { 2019-03-07 17:01:11 [Note] WSREP: view(view_id(PRIM,24f67954,7) memb { 2019-03-07 17:18:58 [Note] WSREP: view(view_id(NON_PRIM,24f67954,7) memb { 2019-03-07 17:19:31 [Note] WSREP: view(view_id(PRIM,a380c8cb,9) memb { 2019-03-07 17:20:27 [Note] WSREP: view(view_id(PRIM,a380c8cb,11) memb { 2019-03-08 7:58:38 [Note] WSREP: view(view_id(PRIM,753a350f,15) memb { 2019-03-08 11:31:38 [Note] WSREP: view(view_id(NON_PRIM,753a350f,15) memb { 2019-03-08 11:31:43 [Note] WSREP: view(view_id(PRIM,489e3c67,17) memb { 2019-03-08 11:31:58 [Note] WSREP: view(view_id(PRIM,489e3c67,18) memb { ... 2019-03-22 7:05:53 [Note] WSREP: view(view_id(NON_PRIM,49dc20da,49) memb { 2019-03-22 7:05:53 [Note] WSREP: view(view_id(PRIM,49dc20da,50) memb { 2019-03-26 12:14:05 [Note] WSREP: view(view_id(NON_PRIM,49dc20da,50) memb { 2019-03-27 7:33:25 [Note] WSREP: view(view_id(NON_PRIM,22ae25aa,1) memb {

So this Cluster had an Uptime of about 18 days and 20 hours. Why can I seed this? Simple: In the brackets there is a number at the very right. This number seems to be the same as wsrep_cluster_conf_id which is reset by a full Galera Cluster shutdown.

So far so good. But, wait, what is the definition of Uptime? Hmmm, not so helpful, how should I interpret this for a 3-Node Galera Cluster?

I would say a good definition for Uptime of a Galera Cluster would be: "At least one Galera Node must be available for the application for reading and writing." That means PRIM in the output above. And we still cannot say from the output above if there was at least on Galera Node available (reading and writing) at any time. For this we have to compare ALL 3 MariaDB Error Logs... So it does not help, we need a good Monitoring solution to answer this question...

PS: Who has found the little fake in this blog?

Taxonomy upgrade extras: galera clusteruptime

Linux system calls of MySQL process

Fri, 2019-03-15 17:06

We had the problem today that a MySQL Galera Cluster node with the multi-tenancy pattern caused a lot of system time (sy 75%, load average about 30 (you really must read this article by Brendan Gregg, it is worth it!)) so we wanted to find what system calls are being used to see what could cause this issue (to verify if it is a TOC or a TDC problem:

$ sudo strace -c -p $(pidof -s mysqld) -f -e trace=all Process 5171 attached with 41 threads Process 16697 attached ^C Process 5171 detached ... Process 5333 detached Process 16697 detached % time seconds usecs/call calls errors syscall ------ ----------- ----------- --------- --------- ---------------- 66.85 1.349700 746 1810 io_getevents 25.91 0.523055 1298 403 197 futex 4.45 0.089773 1069 84 22 read 2.58 0.052000 13000 4 3 restart_syscall 0.19 0.003802 1901 2 select 0.01 0.000235 3 69 1 setsockopt 0.01 0.000210 18 12 getdents 0.00 0.000078 2 32 write 0.00 0.000056 1 49 fcntl 0.00 0.000026 4 6 openat 0.00 0.000012 2 6 close 0.00 0.000000 0 2 2 open 0.00 0.000000 0 22 stat 0.00 0.000000 0 2 mmap 0.00 0.000000 0 7 mprotect 0.00 0.000000 0 16 pread 0.00 0.000000 0 1 access 0.00 0.000000 0 1 sched_yield 0.00 0.000000 0 5 madvise 0.00 0.000000 0 1 accept 0.00 0.000000 0 1 getsockname 0.00 0.000000 0 1 clone 0.00 0.000000 0 1 set_robust_list ------ ----------- ----------- --------- --------- ---------------- 100.00 2.018947 2537 225 total $ man io_getevents ...

See also: Configuration of MySQL for Shared Hosting.

Taxonomy upgrade extras: system calltable_open_cachetable_definition_cachesystem timeload averageopen_files_limitLimitNOFILE

Linux system calls of MySQL process

Fri, 2019-03-15 17:06

We had the problem today that a MySQL Galera Cluster node with the multi-tenancy pattern caused a lot of system time (sy 75%, load average about 30 (you really must read this article by Brendan Gregg, it is worth it!)) so we wanted to find what system calls are being used to see what could cause this issue (to verify if it is a TOC or a TDC problem:

$ sudo strace -c -p $(pidof -s mysqld) -f -e trace=all Process 5171 attached with 41 threads Process 16697 attached ^C Process 5171 detached ... Process 5333 detached Process 16697 detached % time seconds usecs/call calls errors syscall ------ ----------- ----------- --------- --------- ---------------- 66.85 1.349700 746 1810 io_getevents 25.91 0.523055 1298 403 197 futex 4.45 0.089773 1069 84 22 read 2.58 0.052000 13000 4 3 restart_syscall 0.19 0.003802 1901 2 select 0.01 0.000235 3 69 1 setsockopt 0.01 0.000210 18 12 getdents 0.00 0.000078 2 32 write 0.00 0.000056 1 49 fcntl 0.00 0.000026 4 6 openat 0.00 0.000012 2 6 close 0.00 0.000000 0 2 2 open 0.00 0.000000 0 22 stat 0.00 0.000000 0 2 mmap 0.00 0.000000 0 7 mprotect 0.00 0.000000 0 16 pread 0.00 0.000000 0 1 access 0.00 0.000000 0 1 sched_yield 0.00 0.000000 0 5 madvise 0.00 0.000000 0 1 accept 0.00 0.000000 0 1 getsockname 0.00 0.000000 0 1 clone 0.00 0.000000 0 1 set_robust_list ------ ----------- ----------- --------- --------- ---------------- 100.00 2.018947 2537 225 total $ man io_getevents ...

See also: Configuration of MySQL for Shared Hosting.

Taxonomy upgrade extras: system calltable_open_cachetable_definition_cachesystem timeload average

MariaDB and MySQL Database Consolidation

Thu, 2019-03-14 23:05

We see at various customers the request for consolidating their MariaDB and MySQL infrastructure. The advantage of such a measure is clear in the first step: Saving costs! And this request comes typically from managers. But what we unfortunately see rarely is to question this request from the IT engineering perspective. Because it comes, as anything in life, with some "costs". So, saving costs with consolidation on one side comes with "costs" for operation complexity on the other side.

To give you some arguments for arguing with managers we collected some topics to consider before consolidating:

  • Bigger Database Instances are more demanding in handling than smaller ones:
    • Backup and Restore time takes longer. Copying files around takes longer, etc.
    • Possibly your logical backup with mysqldump does not restore any longer in a reasonable amount of time (Mean Time to Repair/Recover (MTTR) is not met any more). You have to think about some physical backup methods including MariaDB or MySQL Enterprise Backup solutions.
    • Consolidated database instances typically contain many different schemas of various different applications. In case of problems you typically want to restore and possibly recover only one single schema and not all schemas. And this becomes much more complicated (depending on your backup strategy). MariaDB/MySQL tooling is not yet (fully) prepared for this situation (#17365). Possibly your old backup strategy is not adequate any more?
    • Binary Logs are written globally, not per schema. Have you considered how to do a PiTR for one or several schemas on your consolidated instance? Not an easy game.
    • When you restore a schema you do not want the application interfering with your restore. How can you properly exclude the one application from your database instance while you are restoring? Locking accounts (possible only with MariaDB 10.4 and MySQL 5.7 and newer). Tricks like --skip-networking, adding Firewall rules, --read-only, database port change (--port=3307), do not work any more (as easy)!
    • In short the costs are: Restore/Recovery Operations become more demanding!
  • Do NOT mix schemas of different criticalities into the same database instance! The worst cases we have seen were some development schemas which were on the same high-availability Cluster like highly critical transactional systems. The developers did some nasty things on their development systems (which IMHO is OK for them on a development system). What nobody considered in this case was that the troubles from the development schema brought down the whole production schema which was located on the same machine... Cost: Risk of failure of your important services caused by some non-important services AND planning becomes more expensive and you need to know more about all instances and other instances.
  • This phenomena is also called Noisy Neighbor effect. Noisy Neighbors become a bigger issue with consolidated systems. You have to know much more in detail what you and everybody else is doing on the system! Do you...? Costs are: More know-how is required, better education and training of people, more clever people, better planning, better monitoring, etc.
  • When you consolidate different applications into one system it becomes more critical than the previous ones on their own. So you have to think about High-Availability solutions. Costs are: 1 to 4 new instances (for HA), more complexity, more know-how, more technologies... Do you plan to buy an Enterprise Support subscription?
  • Do NOT mix different maintenance windows (Asia vs. Europe vs. America) or daily online-business and nightly job processing. You get shorter maintenance windows. Costs are: Better planning is needed, costly night and weekend maintenance time, etc...

    Europe12:00China19:00(7 hours ahead of us)US east07:00(5 hours behind us)US west04:00(8 hours behind us)
  • Resource Fencing becomes more tricky. Within the same instance resource fencing becomes more tricky and is not really doable atm. MySQL 8.0 shows some firsts steps with the Resource Groups but this is pretty complicated and is by far not complete and usable yet. A better way would be to install several instances on the same machine an fence them with some O/S means like Control Groups. This comes at the costs of know-how, complexity and more complicated set-ups.
  • Naming conflicts can happen: Application a) is called `wiki` and application b) is called `wiki` as well and for some reasons you cannot rename them (any more).
  • Monitoring becomes much more demanding and needs to be done more fine grained. You want to know exactly what is going on your system because it can easily have some side effects on many different schemas/applications. Example of today: We were running out of kernel file descriptors (file-max) and we did not recognize it in the beginning.
  • Consolidated things are a much a higher Bulk Risk (this is true also for SAN or Virtualisation Clusters). When you have an outage not only one application is down but the whole company is down. We have seen this already for SAN and Virtualisation Clusters and we expect to see that soon also on highly consolidated Database Clusters. Costs: Damage on the company is bigger for one incident.
  • Different applications have different configuration requirements which possibly conflict with other requirements from other applications (Jira from Atlassian is a good example for this).
    Server variables cannot be adjusted any more according to somebody’s individual wishes...
    • sql_mode: Some old legacy applications still require ONLY_FULL_GROUP_BY) :-(
    • The requirements are conflicting: Performance/fast vs. Safe/durability: innodb_flush_log_at_trx_commit, sync_binlog, crash-safe binary logging, etc.
    • Transaction isolation: transaction_isolation = READ-COMMITTED (old: tx_isolation, Jira again as an example) vs. REPEATABLE-READ (default). Other applications which do not assume, that transaction isolation behaviour changes. And cannot cope with it. Have you ever asked your developers if their application can cope with a different transaction isolation levels? :-) Do they know what you are talking about?
    • Character set (utf8_bin for Jira as example again), which can be changed globally or on a schema level, but it has to be done correctly for all participants.
  • Some applications require MariaDB some application require MySQL. They are not the same databases any more nowadays (8.0 vs. 10.3/10.4). So you cannot consolidate them (easily).
  • You possibly get a mixture of persistent connections (typically Java with connection pooling) and non-persistent connections (typically PHP and other languages). Which causes different database behaviour, which has an impact on how you configure the database instance. Which is more demanding and needs more knowledge of the database AND the application or you solve it with more RAM.
  • You need to know much more about you application to understand what it does and how could it interfere with others...
  • When you consolidate more and more schemas into your consolidated database server you have to adjust your database setting as well from time to time (innodb_buffer_pool_size, table_open_cache, table_definition_cache, O/S File descriptors, etc). And possibly add more RAM, CPU and stronger I/O. When is your network saturated? Have you thought about this already?
  • Upgrading MariaDB/MySQL and changes in database configuration becomes more demanding in communication and coordination. Potentially several development teams are affected. And they possibly have event different requirements/needs in O/S, forks and database versions. Or are even not willing or capable to update.
  • If you have different schemas on the same Instance it is easier to access data in different schemas at the same time in the same query. This can cause (unwanted) dependencies between those schemas. The database becomes the interface between applications. Here you have to be very restrictive with user privileges to avoid these dependencies. From an architecture point of view it would be more preferable to use clearly defined interfaces outside of the database. For example APIs. But those APIs require much more development resources than a simple SQL query. The problem comes later: If you want to separate the schemas again into different instances the effort is increasing significantly to split/rewrite the JOIN queries and the underlying data sets. Or the depending schemas must be moved all together which causes longer downtimes for applications and requires more coordination between teams.

This leads us to the result that consolidation let us save some costs on infrastructure but adds additional costs on complexity, skills etc. Theses costs will grow exponentially and thus at some point it is not worth the effort any more. This will end up in not only one big consolidated instance but possibly in a hand full of them.

Where this point is for you you have to find yourself...

Alternatives to consolidating everything into one instance
  • 1 Machine can contain 1 to many Database Instances can contain 1 to many Schemas. Instead of putting all schemas into one machine, think about installing several instances on one machine. This comes at the cost of more complexity. MyEnv will help you to manage this additional complexity.
  • 1 Machine can contain 1 to many Virtual Machines (VMs, kvm, XEN, VMWare, etc.) can contain 1 to many Instance(s) can contain 1 to many Schemas. This comes at the cost of even more complexity and pretty complex technology (Virtualization).

A big thanks to Antoniya K. for here valuable feedback!

Taxonomy upgrade extras: consolidationcentralizationMyEnv

MariaDB and MySQL Database Consolidation

Thu, 2019-03-14 23:05

We see at various customers the request for consolidating their MariaDB and MySQL infrastructure. The advantage of such a measure is clear in the first step: Saving costs! And this requests comes typically from managers. But what we unfortunately see rarely is to question this request from the IT engineering perspective. Because it comes, as anything in life, with some "costs". So, saving costs with consolidation on one side comes with "costs" for operation complexity on the other side.

To give you some arguments for arguing with managers we collected some topics to consider before consolidating:

  • Bigger Database Instances are more demanding in handling than smaller ones:
    • Backup and Restore time takes longer. Copying files around takes longer, etc.
    • Possibly your logical backup with mysqldump does not restore any longer in a reasonable amount of time (Mean Time to Repair/Recover (MTTR) is not met any more). You have to think about some physical backup methods including MariaDB or MySQL Enterprise Backup solutions.
    • Consolidated database instances typically contain many different schemas of various different applications. In case of problems you typically want to restore and possibly recover only one single schema and not all schemas. And this becomes much more complicated (depending on you backup strategy). MariaDB/MySQL tooling is not yet (fully) prepared for this situation (#17365). Possibly your old backup strategy is not adequate any more?
    • When you restore a schema you do not want the application interfering with your restore. How can you properly exclude the one application from your database instance while you are restoring? Locking accounts (possible only with MariaDB 10.4 and MySQL 5.7 and newer). Tricks like --skip-networking, adding Firewall rules, --read-only, database port change (--port=3307), do not work any more (as easy)!
    • In short the costs are: Restore/Recovery Operations becomes more demanding!
  • Do NOT mix schemas of different criticalities into the same database instance! The worst cases we have seen were some development schemas which were on the same high-availability Cluster like highly critical transactional systems. The developers did some nasty things on their development systems (which IMHO is OK for them on a development system). What nobody considered in this case was that the troubles from the development schema brought down the whole production schema which was located on the same machine... Cost: Risk of failure of your important services caused by some non-important services AND planing becomes more expensive and you need to know more about all instances and other instances.
  • This phenomena is also called Noisy Neighbor effect. Noisy Neighbors become a bigger issues with consolidated systems. You have to know much more in detail what you and everybody else is doing on the system! Do you...? Costs are: More know-how is required, better education and training of people, more clever people, better planning, better monitoring, etc.
  • When you consolidate different applications into one system it becomes more critical than the previous ones on their own. So you have to think about High-Availability solutions. Costs are: 1 to 4 new instances (for HA), more complexity, more know-how, more technologies... Do you plan to buy an Enterprise Support subscription?
  • Do NOT mix different maintenances windows (Asia vs. Europe vs. America) or daily online-business and nightly job processing. You get shorter maintenance windows. Costs are: Better planning is needed, costly night and weekend maintenance time, etc...

    Europe12:00China19:00(7 hours ahead of us)US east07:00(5 hours behind us)US west04:00(8 hours behind us)
  • Resource Fencing becomes more tricky. Within the same instance resource fencing becomes more tricky and is not really doable atm. MySQL 8.0 shows some firsts steps with the Resource Groups but this is pretty complicated and is by far not complete and usable yet. A better way would be to install several instances on the same machine an fence them with some O/S means like Control Groups. This comes at the costs of know-how, complexity and more complicated set-ups.
  • Naming conflicts can happen: Application a) is called `wiki` and application b) is called `wiki` as well and for some reasons you cannot rename them (any more).
  • Monitoring becomes much more demanding and needs to be done more fine grained. You want to know exactly what is going on your system because it can easily have some side effects on many different schemas/applications. Example of today: We were running out of kernel file descriptors (file-max) and we did not recognize it in the beginning.
  • Consolidated things are a much a higher Bulk Risk (this is true also for SAN or Virtualisation Clusters). When you have an outage not only one application is down but the whole company is down. We have seen this already for SAN and Virtualisation Clusters and we expect to see that soon also on highly consolidated Database Clusters. Costs: Damage on the company is bigger for one incident.
  • Different applications have different configuration requirements which possibly conflict with other requirements from other applications (Jira from Atlassian is a good example for this).
    Server variables cannot be adjusted any more according to somebody’s individual wishes...
    • sql_mode: Some old legacy applications still require ONLY_FULL_GROUP_BY) :-(
    • The requirements are conflicting: Performance/fast vs. Safe/durability: innodb_flush_log_at_trx_commit, sync_binlog, crash-safe binary logging, etc.
    • Transaction isolation: transaction_isolation = READ-COMMITTED (old: tx_isolation, Jira again as an example) vs. REPEATABLE-READ (default). Other applications which do not assume, that transaction isolation behaviour changes. And cannot cope with it. Have you ever asked your developers if their application can cope with a different transaction isolation levels? :-) Do they know what you are talking about?
    • Character set (utf8_bin for Jira as example again), which can be changed globally or on a schema level, but it has to be done correctly for all participants.
  • Some applications require MariaDB some application require MySQL. They are not the same databases any more nowadays (8.0 vs. 10.3/10.4). So you cannot consolidate them (easily).
  • You possibly get a mixture of persistent connections (typically Java with connection pooling) and non-persistent connections (typically PHP and other languages). Which causes different database behaviour, which has an impact on how you configure the database instance. Which is more demanding and needs more knowledge of the database AND the application or you solve it with more RAM.
  • You need to know much more about you application to understand what it does and how could it interfere with others...
  • When you consolidate more and more schemas into your consolidated database server you have to adjust your database setting as well from time to time (innodb_buffer_pool_size, table_open_cache, table_definition_cache, O/S File descriptors, etc). And possibly add more RAM, CPU and stronger I/O. When is your network saturated? Have you thought about this already?

This leads us to the result that consolidation let us save some costs on infrastructure but adds additional costs on complexity, skills etc. Theses costs will grow exponentially and thus at some point it is not worth the effort any more. This will end up in not only one big consolidated instance but possibly in a hand full of them.

Where this point is for you you have to find yourself...

Alternatives to consolidating everything into one instance
  • 1 Machine can contain 1 to many Database Instances can contain 1 to many Schemas. Instead of putting all schemas into one machine, think about installing several instances on one machine. This comes at the cost of more complexity. MyEnv will help you to manage this additional complexity.
  • 1 Machine can contain 1 to many Virtual Machines (VMs, kvm, XEN, VMWare, etc.) can contain 1 to many Instance(s) can contain 1 to many Schemas. This comes at the cost of even more complexity and pretty complex technology (Virtualization).

Taxonomy upgrade extras: consolidationcentralizationMyEnv

FromDual Performance Monitor for MariaDB and MySQL 1.0.2 has been released

Wed, 2019-03-13 20:58

FromDual has the pleasure to announce the release of the new version 1.0.2 of its popular Database Performance Monitor for MariaDB, MySQL, Galera Cluster and Percona Server fpmmm.

The new FromDual Performance Monitor for MariaDB and MySQL (fpmmm) can be downloaded from here. How to install and use fpmmm is documented in the fpmmm Installation Guide.

In the inconceivable case that you find a bug in the FromDual Performance Manager for MariaDB and MySQL please report it the FromDual Bugtracker or just send us an email.

Any feedback, statements and testimonials are welcome as well! Please send them to feedback@fromdual.com.

Monitoring as a Service (MaaS)

You do not want to set-up your Database monitoring yourself? No problem: Choose our MariaDB and MySQL Monitoring as a Service (Maas) program to safe costs!

Upgrade from 1.0.x to 1.0.2 shell> cd /opt shell> tar xf /download/fpmmm-1.0.2.tar.gz shell> rm -f fpmmm shell> ln -s fpmmm-1.0.2 fpmmm
Changes in FromDual Performance Monitor for MariaDB and MySQL 1.0.2

This release contains various bug fixes.

You can verify your current FromDual Performance Monitor for MariaDB and MySQL version with the following command:

shell> fpmmm --version
fpmmm agent
  • Server entropy probe added.
  • Processlist empty state is covered.
  • Processlist statements made more robust.
  • Error caught properly after query.
  • Branch for Ubuntu is different, fixed.
  • PHP Variable variables_order is included into program.
  • Fixed the documentation URL in file INSTALL.
  • Connection was not set to utf8. This is fixed now.
  • fprint error fixed.
  • Library myEnv.inc updated from MyEnv project.

fpmmm Templates
  • Backup template added.
  • SQL thread and IO thread error more verbose and running again triggers implemented. Typo in slave template fixed.
  • Forks graph fixed, y axis starts from 0.

fpmmm agent installer
  • Error messages made more flexible.

For subscriptions of commercial use of fpmmm please get in contact with us.

Taxonomy upgrade extras: performancemonitormonitoringfpmmmmaasrelease

FromDual Performance Monitor for MariaDB and MySQL 1.0.2 has been released

Wed, 2019-03-13 20:58

FromDual has the pleasure to announce the release of the new version 1.0.2 of its popular Database Performance Monitor for MariaDB, MySQL, Galera Cluster and Percona Server fpmmm.

The new FromDual Performance Monitor for MariaDB and MySQL (fpmmm) can be downloaded from here. How to install and use fpmmm is documented in the fpmmm Installation Guide.

In the inconceivable case that you find a bug in the FromDual Performance Manager for MariaDB and MySQL please report it the FromDual Bugtracker or just send us an email.

Any feedback, statements and testimonials are welcome as well! Please send them to feedback@fromdual.com.

Monitoring as a Service (MaaS)

You do not want to set-up your Database monitoring yourself? No problem: Choose our MariaDB and MySQL Monitoring as a Service (Maas) program to safe costs!

Upgrade from 1.0.x to 1.0.2 shell> cd /opt shell> tar xf /download/fpmmm-1.0.2.tar.gz shell> rm -f fpmmm shell> ln -s fpmmm-1.0.2 fpmmm
Changes in FromDual Performance Monitor for MariaDB and MySQL 1.0.2

This release contains various bug fixes.

You can verify your current FromDual Performance Monitor for MariaDB and MySQL version with the following command:

shell> fpmmm --version
fpmmm agent
  • Server entropy probe added.
  • Processlist empty state is covered.
  • Processlist statements made more robust.
  • Error caught properly after query.
  • Branch for Ubuntu is different, fixed.
  • PHP Variable variables_order is included into program.
  • Fixed the documentation URL in file INSTALL.
  • Connection was not set to utf8. This is fixed now.
  • fprint error fixed.
  • Library myEnv.inc updated from MyEnv project.

fpmmm Templates
  • Backup template added.
  • SQL thread and IO thread error more verbose and running again triggers implemented. Typo in slave template fixed.
  • Forks graph fixed, y axis starts from 0.

fpmmm agent installer
  • Error messages made more flexible.

For subscriptions of commercial use of fpmmm please get in contact with us.

Taxonomy upgrade extras: performancemonitormonitoringfpmmmmaasrelease

MariaDB and MySQL consulting by plane

Fri, 2019-03-01 15:27

Since January 2019 FromDual tries to contribute actively a little bit against global warming too.

The best for the climate would be to NOT travel to the customer at all! For this cases we have our FromDual remote-DBA services for MariaDB and MySQL.

But sometimes customer wants or needs us on-site for our FromDual in-house trainings or our FromDual on-site consulting engagements. In these cases we try to travel by train. Travelling by train is after walking or travelling by bicycle the most climate friendly way to travel:


But some customers are located more than 7 to 8 hours far away by train. For these customers we have to take the plan which is not good for the climate at all. But at least we will compensate for our CO2 emission via MyClimate.org:

Taxonomy upgrade extras: consultingtrainingremote-dbamysqlmariadbservices

MariaDB and MySQL consulting by plane

Fri, 2019-03-01 15:27

Since January 2019 FromDual tries to contribute actively a little bit against global warming too.

The best for the climate would be to NOT travel to the customer at all! For this cases we have our FromDual remote-DBA services for MariaDB and MySQL.

But sometimes customer wants or needs us on-site for our FromDual in-house trainings or our FromDual on-site consulting engagements. In these cases we try to travel by train. Travelling by train is after walking or travelling by bicycle the most climate friendly way to travel:


But some customers are located more than 7 to 8 hours far away by train. For these customers we have to take the plan which is not good for the climate at all. But at least we will compensate for our CO2 emission via MyClimate.org:

Taxonomy upgrade extras: consultingtrainingremote-dbaclimatemysqlmariadbservices

FromDual Backup and Recovery Manager for MariaDB and MySQL 2.1.0 has been released

Fri, 2019-02-22 17:14

FromDual has the pleasure to announce the release of the new version 2.1.0 of its popular Backup and Recovery Manager for MariaDB and MySQL (brman).

The new FromDual Backup and Recovery Manager can be downloaded from here. How to install and use the Backup and Recovery Manager is describe in FromDual Backup and Recovery Manager (brman) installation guide.

In the inconceivable case that you find a bug in the FromDual Backup and Recovery Manager please report it to the FromDual Bugtracker or just send us an email.

Any feedback, statements and testimonials are welcome as well! Please send them to feedback@fromdual.com.

Upgrade from 1.2.x to 2.1.0

brman 2.1.0 requires a new PHP package for ssh connections.

shell> sudo apt-get install php-ssh2 shell> cd ${HOME}/product shell> tar xf /download/brman-2.1.0.tar.gz shell> rm -f brman shell> ln -s brman-2.1.0 brman
Changes in FromDual Backup and Recovery Manager 2.1.0

This release is a new major release series. It contains a lot of new features. We have tried to maintain backward-compatibility with the 1.2 and 2.0 release series. But you should test the new release seriously!

You can verify your current FromDual Backup Manager version with the following command:

shell> fromdual_bman --version shell> bman --version
FromDual Backup Manager
  • Usage (--help) updated.
  • Some WARN severities downgraded to INFO to keep mail output clean.
  • Error messages made more flexible and fixed PHP library advice.
  • Split some redundant code from bman library into brman library.
  • Security fix: Password from config file is hidden now.
  • Bug on simulation of physical backup fixed (xtrabackup_binlog_info not found).
  • Options --backup-name and --backup-overwrite introduced for restore automation.
  • Minor typo bugs fixed.
  • Option --options remove.
  • Sort order for schema backup changed to ORDER BY ASC.
  • 2 PHP errors fixed for simulation.
  • Maskerade API added.
  • Physical backup sftp archiving with special characters (+foodmarat) in archive directory name fixed.

FromDual Recovery Manager
  • Rman has progress report.
  • Full logical restore is implemented.
  • Schema logical restore is implemented.
  • Physical restore is implemented.
  • Physical restore of compressed backups is implemented.
  • Option --cleanup-first was implemented for physical backup as well.
  • Option: --stop-instance implemented.

FromDual Backup Manager Catalog
  • No changes.

Subscriptions for commercial use of FromDual Backup and Recovery Manager you can get from from us.

Taxonomy upgrade extras: BackupRestoreRecoverypitrbrmanreleasebmanrman

MySQL Enterprise Backup Support Matrix

Tue, 2019-02-19 19:13

MySQL Enterprise Backup (MEB) is a bit limited related to support of older MySQL versions. So you should consider the following release matrix:

MEB/MySQLSupported 5.5  5.6  5.7  8.0 3.11.xNOxx3.12.xYESxx4.0.xNOx4.1.xYESx8.0.xYES8.0.x*

* MySQL Enterprise Backup 8.0.15 only supports MySQL 8.0.15. For earlier versions of MySQL 8.0, use the MySQL Enterprise Backup version with the same version number as the server.

MySQL Enterprise Backup is available for download from the My Oracle Support (MOS) website. This release will be available on Oracle eDelivery (OSDC) after the next upload cycle. MySQL Enterprise Backup is a commercial extension to the MySQL family of products.

As an Open Source alternative Percona XtraBackup for MySQL databases is available.

Compatibility with MySQL Versions: 3.11, 3.12, 4.0, 4.1, 8.0.

MySQL Enterprise Backup User's Guide: 3.11, 3.12, 4.0, 4.1, 8.0.

Taxonomy upgrade extras: MySQL Enterprise BackupBackupmebenterprisesupportmatrix

MariaDB/MySQL Environment MyEnv 2.0.2 has been released

Thu, 2019-01-17 19:35

FromDual has the pleasure to announce the release of the new version 2.0.2 of its popular MariaDB, Galera Cluster and MySQL multi-instance environment MyEnv.

The new MyEnv can be downloaded here. How to install MyEnv is described in the MyEnv Installation Guide.

In the inconceivable case that you find a bug in the MyEnv please report it to the FromDual bug tracker.

Any feedback, statements and testimonials are welcome as well! Please send them to feedback@fromdual.com.

Upgrade from 1.1.x to 2.0

Please look at the MyEnv 2.0.0 Release Notes.

Upgrade from 2.0.x to 2.0.2 shell> cd ${HOME}/product shell> tar xf /download/myenv-2.0.2.tar.gz shell> rm -f myenv shell> ln -s myenv-2.0.2 myenv
Plug-ins

If you are using plug-ins for showMyEnvStatus create all the links in the new directory structure:

shell> cd ${HOME}/product/myenv shell> ln -s ../../utl/oem_agent.php plg/showMyEnvStatus/
Upgrade of the instance directory structure

From MyEnv 1.0 to 2.0 the directory structure of instances has fundamentally changed. Nevertheless MyEnv 2.0 works fine with MyEnv 1.0 directory structures.

Changes in MyEnv 2.0.2 MyEnv
  • Error message fixed.
  • bind_address 0.0.0.0 is optimized to *.
  • State up and down are coloured now.
  • Complaint on missing symbolic link to my.cnf added.
  • New start-timeout configuration variable added. Important for Galera SST.
  • Default MariaDB my.cnf hash added to avoid complaints.
  • mysqld is consistently searched in sbin, bin and libexec now for RHEL/CentOS 7 compatibility.
  • Avoid EGPCS error messages during MyEnv start/stop.
  • Not used aReleaseVersion removed, side effect is to not have performance issues any more on up in huge MyEnv set-ups with older MySQL releases.

MyEnv Installer
  • Function answerQuestion on previous error message works now.
  • Try and catch for existing configuration file improved.
  • Default answer is "q" on error and instance name and blacklist name check is fixed.
  • myenv.conf backup file has a correct timestamp now.
  • Create symlink to datadir for my.cnf.
  • Purge of database is done from instancedir and not datadir any more.

MyEnv Utilities
  • galera_monitor.sh output made nicer.
  • Script az_test.php added, initial test found already a bug in MariaDB 10.3.
  • Script slave_monitor.sh added.
  • Option check made more careful for drop_partition.php and merge_partition.php.
  • Timestamp problem fixed for year change in split_partition.php.

For subscriptions of commercial use of MyEnv please get in contact with us.

Taxonomy upgrade extras: MyEnvmulti-instancevirtualizationconsolidationSaaSOperationsreleaseupgrademysqld_multi

Using tmux for MariaDB database support and surveillance

Tue, 2018-12-25 16:14

See also our older article: Using screen for support and/or surveillance.

First simple steps

The command tmux starts a tmux server and opens a new session with a (pseudo) terminal:

shell> tmux

To leave a tmux session again just type Ctrl+d inside your tmux session or:

tmux> exit

If you want to give a tmux session a specific name you can start tmux as follows to created a named session:

shell> tmux new -s mariadb

or if you are already inside tmux:

tmux> Ctrl+b $

followed by a session name where only the first 9 characters are shown in the overview:

List available tmux sessions

To list the available tmux sessions we have the tmux list-sessions command:

shell> tmux list-sessions 1: 1 windows (created Sun Dec 23 13:35:37 2018) [117x33] mariadb-104: 1 windows (created Sun Dec 23 13:13:46 2018) [130x41] (attached)

If there is no session available we will get the following error:

shell> tmux ls failed to connect to server
tmux help

To get more information about tmux you can run:

shell> man tmux shell> tmux --help shell> tmux ls --help tmux> Ctrl+b ?
Detach and re-attach to a tmux session

With the command:

tmux> Ctrl+b d

you will detach from a tmux session. With tmux ls you can list the available sessions and to reattach to a tmux session you can type:

shell> tmux attach shell> tmux attach -t 1 shell> tmux a -t mariadb-104
Split window (session) into different panes

A tmux session uses a window and this window can be split into different panes (pseudo terminals):

  • Ctrl+b % Splits a window into 2 panes vertically.
  • Ctrl+b " Splits a window into 2 panes horizontally.

To switch between the panes you can use:

tmux> Ctrl+b arrow {up|down|left|right}

If you want to make a pane full-screen you can use the Ctrl+b z to toggle.

Ctrl+b Ctrl+Cursor {up|down|left|right} resizes the current pane.

Scroll within a pane

To switch to the scroll mode you have to use the following key combination:

tmux> Ctrl+b [

Then you can navigate with Cursor {up|down|left|right} or {PgUp|PgDown}. To leave the navigation scroll mode you just have to type q.

An other possibility to switch to the scroll mode is to press the key Ctrl+b PgUp.

Taxonomy upgrade extras: tmuxscreenterminalsupportssh

To NULL, or not to NULL, that is the question!

Fri, 2018-12-14 08:33

As we already stated in earlier articles in this blog [1 and 2] it is a good idea to use NULL values properly in MariaDB and MySQL.

One of my Mantras in MariaDB performance tuning is: Smaller tables lead to faster queries! One consequence out of this is to store NULL values instead of some dummy values into the columns if the value is not known (NULL: undefined/unknown).

To show how this helps related to space used by a table we created a little example:

CREATE TABLE big_null1 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NOT NULL , c02 VARCHAR(32) NOT NULL , c03 VARCHAR(32) NOT NULL , c04 VARCHAR(32) NOT NULL , c05 VARCHAR(32) NOT NULL , c06 VARCHAR(32) NOT NULL , c07 VARCHAR(32) NOT NULL , c08 VARCHAR(32) NOT NULL , c09 VARCHAR(32) NOT NULL , c10 VARCHAR(32) NOT NULL , c11 VARCHAR(32) NOT NULL , c12 VARCHAR(32) NOT NULL , INDEX (c03) , INDEX (c06) , INDEX (c09) ); CREATE TABLE big_null2 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NOT NULL , c02 VARCHAR(32) NOT NULL , c03 VARCHAR(32) NOT NULL , c04 VARCHAR(32) NOT NULL , c05 VARCHAR(32) NOT NULL , c06 VARCHAR(32) NOT NULL , c07 VARCHAR(32) NOT NULL , c08 VARCHAR(32) NOT NULL , c09 VARCHAR(32) NOT NULL , c10 VARCHAR(32) NOT NULL , c11 VARCHAR(32) NOT NULL , c12 VARCHAR(32) NOT NULL , INDEX (c03) , INDEX (c06) , INDEX (c09) );

Now we fill the table with default values (empty string or dummy values) because we do not know yet the contents:

INSERT INTO big_null1 VALUES (NULL, '', '', '', '', '', '', '', '', '', '', '', ''); INSERT INTO big_null1 SELECT NULL, '', '', '', '', '', '', '', '', '', '', '', '' FROM big_null1; ... up to 1 Mio rows INSERT INTO big_null2 VALUES (NULL, 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.' , 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.'); INSERT INTO big_null2 SELECT NULL, 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.' , 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.' FROM big_null2; ... up to 1 Mio rows ANALYZE TABLE big_null1; ANALYZE TABLE big_null2; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2') ORDER BY table_name; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | +------------+------------+----------------+-------------+--------------+-----------+

The opposite example is a table which allows NULL values for unknown fields:

CREATE TABLE big_null3 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NULL , c02 VARCHAR(32) NULL , c03 VARCHAR(32) NULL , c04 VARCHAR(32) NULL , c05 VARCHAR(32) NULL , c06 VARCHAR(32) NULL , c07 VARCHAR(32) NULL , c08 VARCHAR(32) NULL , c09 VARCHAR(32) NULL , c10 VARCHAR(32) NULL , c11 VARCHAR(32) NULL , c12 VARCHAR(32) NULL , INDEX (c03) , INDEX (c06) , INDEX (c09) );

Also this table is filled with unknown values but this time with value NULL instead of an empty string:

INSERT INTO big_null3 (id) VALUES (NULL); INSERT INTO big_null3 (id) SELECT NULL FROM big_null3; ... up to 1 Mio rows ANALYZE TABLE big_null3; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3') ORDER BY table_name ; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | +------------+------------+----------------+-------------+--------------+-----------+

We see, that this table already uses much less space when we make correct use of NULL values...

So let us do some simple query run time tests:

big_null1big_null2big_null3SELECT * FROM big_nullx1.1 s1.3 s0.9 sSELECT * FROM big_nullx AS t1
  JOIN big_nullx AS t2 ON t2.id = t1.id
  JOIN big_nullx AS t3 ON t1.id = t3.id5.0 s5.7 s4.2 s

One of my advices is, to fill the columns with NULL values if possible. So let us try this advice as well:

CREATE TABLE big_null4 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c02 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c03 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c04 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c05 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c06 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c07 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c08 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c09 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c10 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c11 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c12 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , INDEX (c03) , INDEX (c06) , INDEX (c09) ); INSERT INTO big_null4 (id) VALUES (NULL); INSERT INTO big_null4 (id) SELECT NULL FROM big_null4; ... up to 1 Mio rows ANALYZE TABLE big_null4; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3', 'big_null4') ORDER BY table_name ; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | | big_null4 | 998533 | 383 | 382599168 | 118358016 | 6291456 | +------------+------------+----------------+-------------+--------------+-----------+

So following my advice we fill with NULL values:

UPDATE big_null4 SET c01 = NULL, c02 = NULL, c03 = NULL, c04 = NULL, c05 = NULL, c06 = NULL , c07 = NULL, c08 = NULL, c09 = NULL, c10 = NULL, c11 = NULL, c12 = NULL; ANALYZE TABLE big_null4; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3', 'big_null4') ORDER BY table_name; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | | big_null4 | 1047285 | 364 | 381779968 | 126222336 | 33554432 | +------------+------------+----------------+-------------+--------------+-----------+

It seems like we do not see the effect yet. So lets optimize the table to reclaim the space:

OPTIMIZE TABLE big_null4; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3', 'big_null4') ORDER BY table_name ; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | | big_null4 | 1047180 | 30 | 32030720 | 39370752 | 4194304 | +------------+------------+----------------+-------------+--------------+-----------+

And you see there we get much of the space back... NULL is a good thing!

Taxonomy upgrade extras: nullperformanceoptimizeBackuptabledefault

To NULL, or not to NULL, that is the question!

Fri, 2018-12-14 08:33

As we already stated in earlier articles in this blog [1 and 2] it is a good idea to use NULL values properly in MariaDB and MySQL.

One of my Mantras in MariaDB performance tuning is: Smaller tables lead to faster queries! One consequence out of this is to store NULL values instead of some dummy values into the columns if the value is not known (NULL: undefined/unknown).

To show how this helps related to space used by a table we created a little example:

CREATE TABLE big_null1 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NOT NULL , c02 VARCHAR(32) NOT NULL , c03 VARCHAR(32) NOT NULL , c04 VARCHAR(32) NOT NULL , c05 VARCHAR(32) NOT NULL , c06 VARCHAR(32) NOT NULL , c07 VARCHAR(32) NOT NULL , c08 VARCHAR(32) NOT NULL , c09 VARCHAR(32) NOT NULL , c10 VARCHAR(32) NOT NULL , c11 VARCHAR(32) NOT NULL , c12 VARCHAR(32) NOT NULL , INDEX (c03) , INDEX (c06) , INDEX (c09) ); CREATE TABLE big_null2 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NOT NULL , c02 VARCHAR(32) NOT NULL , c03 VARCHAR(32) NOT NULL , c04 VARCHAR(32) NOT NULL , c05 VARCHAR(32) NOT NULL , c06 VARCHAR(32) NOT NULL , c07 VARCHAR(32) NOT NULL , c08 VARCHAR(32) NOT NULL , c09 VARCHAR(32) NOT NULL , c10 VARCHAR(32) NOT NULL , c11 VARCHAR(32) NOT NULL , c12 VARCHAR(32) NOT NULL , INDEX (c03) , INDEX (c06) , INDEX (c09) );

Now we fill the table with default values (empty string or dummy values) because we do not know yet the contents:

INSERT INTO big_null1 VALUES (NULL, '', '', '', '', '', '', '', '', '', '', '', ''); INSERT INTO big_null1 SELECT NULL, '', '', '', '', '', '', '', '', '', '', '', '' FROM big_null1; ... up to 1 Mio rows INSERT INTO big_null2 VALUES (NULL, 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.' , 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.'); INSERT INTO big_null2 SELECT NULL, 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.' , 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.', 'Some dummy value.' FROM big_null2; ... up to 1 Mio rows ANALYZE TABLE big_null1; ANALYZE TABLE big_null2; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2') ORDER BY table_name; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | +------------+------------+----------------+-------------+--------------+-----------+

The opposite example is a table which allows NULL values for unknown fields:

CREATE TABLE big_null3 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NULL , c02 VARCHAR(32) NULL , c03 VARCHAR(32) NULL , c04 VARCHAR(32) NULL , c05 VARCHAR(32) NULL , c06 VARCHAR(32) NULL , c07 VARCHAR(32) NULL , c08 VARCHAR(32) NULL , c09 VARCHAR(32) NULL , c10 VARCHAR(32) NULL , c11 VARCHAR(32) NULL , c12 VARCHAR(32) NULL , INDEX (c03) , INDEX (c06) , INDEX (c09) );

Also this table is filled with unknown values but this time with value NULL instead of an empty string:

INSERT INTO big_null3 (id) VALUES (NULL); INSERT INTO big_null3 (id) SELECT NULL FROM big_null3; ... up to 1 Mio rows ANALYZE TABLE big_null3; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3') ORDER BY table_name ; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | +------------+------------+----------------+-------------+--------------+-----------+

We see, that this table already uses much less space when we make correct use of NULL values...

So let us do some simple query run time tests:

big_null1big_null2big_null3SELECT * FROM big_nullx1.1 s1.3 s0.9 sSELECT * FROM big_nullx AS t1
  JOIN big_nullx AS t2 ON t2.id = t1.id
  JOIN big_nullx AS t3 ON t1.id = t3.id5.0 s5.7 s4.2 s

One of my advices is, to fill the columns with NULL values if possible. So let us try this advice as well:

CREATE TABLE big_null4 ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , c01 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c02 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c03 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c04 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c05 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c06 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c07 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c08 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c09 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c10 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c11 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , c12 VARCHAR(32) NULL DEFAULT 'Some dummy value here...!' , INDEX (c03) , INDEX (c06) , INDEX (c09) ); INSERT INTO big_null4 (id) VALUES (NULL); INSERT INTO big_null4 (id) SELECT NULL FROM big_null4; ... up to 1 Mio rows ANALYZE TABLE big_null4; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3', 'big_null4') ORDER BY table_name ; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | | big_null4 | 998533 | 383 | 382599168 | 118358016 | 6291456 | +------------+------------+----------------+-------------+--------------+-----------+

So following my advice we fill with NULL values:

UPDATE big_null4 SET c01 = NULL, c02 = NULL, c03 = NULL, c04 = NULL, c05 = NULL, c06 = NULL , c07 = NULL, c08 = NULL, c09 = NULL, c10 = NULL, c11 = NULL, c12 = NULL; ANALYZE TABLE big_null4; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3', 'big_null4') ORDER BY table_name; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | | big_null4 | 1047285 | 364 | 381779968 | 126222336 | 33554432 | +------------+------------+----------------+-------------+--------------+-----------+

It seems like we do not see the effect yet. So lets optimize the table to reclaim the space:

OPTIMIZE TABLE big_null4; SELECT table_name, table_rows, avg_row_length, data_length, index_length, data_free FROM information_schema.tables WHERE table_name IN ('big_null1', 'big_null2', 'big_null3', 'big_null4') ORDER BY table_name ; +------------+------------+----------------+-------------+--------------+-----------+ | table_name | table_rows | avg_row_length | data_length | index_length | data_free | +------------+------------+----------------+-------------+--------------+-----------+ | big_null1 | 1046760 | 37 | 39387136 | 36225024 | 4194304 | | big_null2 | 1031990 | 264 | 273416192 | 89899008 | 6291456 | | big_null3 | 1047800 | 26 | 27852800 | 36225024 | 7340032 | | big_null4 | 1047180 | 30 | 32030720 | 39370752 | 4194304 | +------------+------------+----------------+-------------+--------------+-----------+

And you see there we get much of the space back... NULL is a good thing!

Taxonomy upgrade extras: nullperformanceoptimizeBackuptabledefault

UNDO logs in InnoDB system tablespace ibdata1

Wed, 2018-12-05 21:55

We see sometimes at customers that they have very big InnoDB system tablespace files (ibdata1) although they have set innodb_file_per_table = 1.

So we want to know what else is stored in the InnoDB system tablespace file ibdata1 to see what we can do against this unexpected growth.

First let us check the size of the ibdata1 file:

# ll ibdata1 -rw-rw---- 1 mysql mysql 109064486912 Dez 5 19:10 ibdata1

The InnoDB system tablespace is about 101.6 Gibyte in size. This is exactly 6'656'768 InnoDB blocks of 16 kibyte block size.

So next we want to analyse the InnoDB system tablespace ibdata1 file. For this we can use the tool innochecksum:

# innochecksum --page-type-summary ibdata1 Error: Unable to lock file:: ibdata1 fcntl: Resource temporarily unavailable

But... the tool innochecksum throughs an error. It seems like it is not allowed to analyse the InnoDB system tablespace with a running database. So then let us stop the database first and try it again. Now we get a useful output:

# innochecksum --page-type-summary ibdata1 File::ibdata1 ================PAGE TYPE SUMMARY============== #PAGE_COUNT PAGE_TYPE =============================================== 349391 Index page 5.25% 6076813 Undo log page 91.29% 18349 Inode page 0.28% 174659 Insert buffer free list page 2.62% 36639 Freshly allocated page 0.55% 405 Insert buffer bitmap 0.01% 98 System page 1 Transaction system page 1 File Space Header 404 Extent descriptor page 0.01% 0 BLOB page 8 Compressed BLOB page 0 Other type of page ------------------------------------------------------- 6656768 Pages total 100.00% =============================================== Additional information: Undo page type: 3428 insert, 6073385 update, 0 other Undo page state: 1 active, 67 cached, 249 to_free, 1581634 to_purge, 0 prepared, 4494862 other

So we can see that about 91% (about 92 Gibyte) of the InnoDB system tablespace ibdata1 blocks are used by InnoDB UNDO log pages. To avoid growing of ibdata1 you have to create a database instance with separate InnoDB UNDO tablespaces: Undo Tablespaces.

Taxonomy upgrade extras: undoinnodbtablespaceibdata1

UNDO logs in InnoDB system tablespace ibdata1

Wed, 2018-12-05 21:55

We see sometimes at customers that they have very big InnoDB system tablespace files (ibdata1) although they have set innodb_file_per_table = 1.

So we want to know what else is stored in the InnoDB system tablespace file ibdata1 to see what we can do against this unexpected growth.

First let us check the size of the ibdata1 file:

# ll ibdata1 -rw-rw---- 1 mysql mysql 109064486912 Dez 5 19:10 ibdata1

The InnoDB system tablespace is about 101.6 Gibyte in size. This is exactly 6'656'768 InnoDB blocks of 16 kibyte block size.

So next we want to analyse the InnoDB system tablespace ibdata1 file. For this we can use the tool innochecksum:

# innochecksum --page-type-summary ibdata1 Error: Unable to lock file:: ibdata1 fcntl: Resource temporarily unavailable

But... the tool innochecksum throughs an error. It seems like it is not allowed to analyse the InnoDB system tablespace with a running database. So then let us stop the database first and try it again. Now we get a useful output:

# innochecksum --page-type-summary ibdata1 File::ibdata1 ================PAGE TYPE SUMMARY============== #PAGE_COUNT PAGE_TYPE =============================================== 349391 Index page 5.25% 6076813 Undo log page 91.29% 18349 Inode page 0.28% 174659 Insert buffer free list page 2.62% 36639 Freshly allocated page 0.55% 405 Insert buffer bitmap 0.01% 98 System page 1 Transaction system page 1 File Space Header 404 Extent descriptor page 0.01% 0 BLOB page 8 Compressed BLOB page 0 Other type of page ------------------------------------------------------- 6656768 Pages total 100.00% =============================================== Additional information: Undo page type: 3428 insert, 6073385 update, 0 other Undo page state: 1 active, 67 cached, 249 to_free, 1581634 to_purge, 0 prepared, 4494862 other

So we can see that about 91% (about 92 Gibyte) of the InnoDB system tablespace ibdata1 blocks are used by InnoDB UNDO log pages. To avoid growing of ibdata1 you have to create a database instance with separate InnoDB UNDO tablespaces: Undo Tablespaces.

Taxonomy upgrade extras: undoinnodbtablespaceibdata1

MariaDB indexing of NULL values

Thu, 2018-11-29 20:10

In the recent MariaDB DBA advanced training class the question came up if MariaDB can make use of an index when searching for NULL values... And to be honest I was not sure any more. So instead of reading boring documentation I did some little tests:

Search for NULL

First I started with a little test data set. Some of you might already know it:

CREATE TABLE null_test ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , data VARCHAR(32) DEFAULT NULL , ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP() ); INSERT INTO null_test VALUES (NULL, 'Some data to show if null works', NULL); INSERT INTO null_test SELECT NULL, 'Some data to show if null works', NULL FROM null_test; ... up to 1 Mio rows

Then I modified the data according to my needs to see if the MariaDB Optimizer can make use of the index:

-- Set 0.1% of the rows to NULL UPDATE null_test SET data = NULL WHERE ID % 1000 = 0; ALTER TABLE null_test ADD INDEX (data); ANALYZE TABLE null_test;

and finally I run the test (MariaDB 10.3.11):

EXPLAIN EXTENDED SELECT * FROM null_test WHERE data IS NULL; +------+-------------+-----------+------+---------------+------+---------+-------+------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+-----------+------+---------------+------+---------+-------+------+----------+-----------------------+ | 1 | SIMPLE | null_test | ref | data | data | 35 | const | 1047 | 100.00 | Using index condition | +------+-------------+-----------+------+---------------+------+---------+-------+------+----------+-----------------------+

We can clearly see that the MariaDB Optimizer considers and uses the index and its estimation of about 1047 rows is quite appropriate.

Unfortunately the optimizer chooses the completely wrong strategy (3 times slower) for the opposite query:

EXPLAIN EXTENDED SELECT * FROM null_test WHERE data = 'Some data to show if null works'; +------+-------------+-----------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+-----------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | 1 | SIMPLE | null_test | ref | data | data | 35 | const | 522351 | 100.00 | Using index condition | +------+-------------+-----------+------+---------------+------+---------+-------+--------+----------+-----------------------+
Search for NOT NULL

Now let us try to test the opposite problem:

CREATE TABLE anti_null_test ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , data VARCHAR(32) DEFAULT NULL , ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP() ); INSERT INTO anti_null_test VALUES (NULL, 'Some data to show if null works', NULL); INSERT INTO anti_null_test SELECT NULL, 'Some data to show if null works', NULL FROM anti_null_test; ... up to 1 Mio rows

Then I modified the data as well but this time in the opposite direction:

-- Set 99.9% of the rows to NULL UPDATE anti_null_test SET data = NULL WHERE ID % 1000 != 0; ALTER TABLE anti_null_test ADD INDEX (data); ANALYZE TABLE anti_null_test;

and then we have to test again the query:

EXPLAIN EXTENDED SELECT * FROM anti_null_test WHERE data IS NOT NULL; +------+-------------+----------------+-------+---------------+------+---------+------+------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+----------------+-------+---------------+------+---------+------+------+----------+-----------------------+ | 1 | SIMPLE | anti_null_test | range | data | data | 35 | NULL | 1047 | 100.00 | Using index condition | +------+-------------+----------------+-------+---------------+------+---------+------+------+----------+-----------------------+

Also in this case the MariaDB Optimizer considers and uses the index and produces a quite fast Query Execution Plan.

Also in this case the optimizer behaves wrong for the opposite query:

EXPLAIN EXTENDED SELECT * FROM anti_null_test WHERE data IS NULL; +------+-------------+----------------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+----------------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | 1 | SIMPLE | anti_null_test | ref | data | data | 35 | const | 523506 | 100.00 | Using index condition | +------+-------------+----------------+------+---------------+------+---------+-------+--------+----------+-----------------------+ Taxonomy upgrade extras: Optimizernullindexmariadb

MariaDB indexing of NULL values

Thu, 2018-11-29 20:10

In the recent MariaDB DBA advanced training class the question came up if MariaDB can make use of an index when searching for NULL values... And to be honest I was not sure any more. So instead of reading boring documentation I did some little tests:

Search for NULL

First I started with a little test data set. Some of you might already know it:

CREATE TABLE null_test ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , data VARCHAR(32) DEFAULT NULL , ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP() ); INSERT INTO null_test VALUES (NULL, 'Some data to show if null works', NULL); INSERT INTO null_test SELECT NULL, 'Some data to show if null works', NULL FROM null_test; ... up to 1 Mio rows

Then I modified the data according to my needs to see if the MariaDB Optimizer can make use of the index:

-- Set 0.1% of the rows to NULL UPDATE null_test SET data = NULL WHERE ID % 1000 = 0; ALTER TABLE null_test ADD INDEX (data); ANALYZE TABLE null_test;

and finally I run the test (MariaDB 10.3.11):

EXPLAIN EXTENDED SELECT * FROM null_test WHERE data IS NULL; +------+-------------+-----------+------+---------------+------+---------+-------+------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+-----------+------+---------------+------+---------+-------+------+----------+-----------------------+ | 1 | SIMPLE | null_test | ref | data | data | 35 | const | 1047 | 100.00 | Using index condition | +------+-------------+-----------+------+---------------+------+---------+-------+------+----------+-----------------------+

We can clearly see that the MariaDB Optimizer considers and uses the index and its estimation of about 1047 rows is quite appropriate.

Unfortunately the optimizer chooses the completely wrong strategy (3 times slower) for the opposite query:

EXPLAIN EXTENDED SELECT * FROM null_test WHERE data = 'Some data to show if null works'; +------+-------------+-----------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+-----------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | 1 | SIMPLE | null_test | ref | data | data | 35 | const | 522351 | 100.00 | Using index condition | +------+-------------+-----------+------+---------------+------+---------+-------+--------+----------+-----------------------+
Search for NOT NULL

Now let us try to test the opposite problem:

CREATE TABLE anti_null_test ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY , data VARCHAR(32) DEFAULT NULL , ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP() ); INSERT INTO anti_null_test VALUES (NULL, 'Some data to show if null works', NULL); INSERT INTO anti_null_test SELECT NULL, 'Some data to show if null works', NULL FROM anti_null_test; ... up to 1 Mio rows

Then I modified the data as well but this time in the opposite direction:

-- Set 99.9% of the rows to NULL UPDATE anti_null_test SET data = NULL WHERE ID % 1000 != 0; ALTER TABLE anti_null_test ADD INDEX (data); ANALYZE TABLE anti_null_test;

and then we have to test again the query:

EXPLAIN EXTENDED SELECT * FROM anti_null_test WHERE data IS NOT NULL; +------+-------------+----------------+-------+---------------+------+---------+------+------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+----------------+-------+---------------+------+---------+------+------+----------+-----------------------+ | 1 | SIMPLE | anti_null_test | range | data | data | 35 | NULL | 1047 | 100.00 | Using index condition | +------+-------------+----------------+-------+---------------+------+---------+------+------+----------+-----------------------+

Also in this case the MariaDB Optimizer considers and uses the index and produces a quite fast Query Execution Plan.

Also in this case the optimizer behaves wrong for the opposite query:

EXPLAIN EXTENDED SELECT * FROM anti_null_test WHERE data IS NULL; +------+-------------+----------------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +------+-------------+----------------+------+---------------+------+---------+-------+--------+----------+-----------------------+ | 1 | SIMPLE | anti_null_test | ref | data | data | 35 | const | 523506 | 100.00 | Using index condition | +------+-------------+----------------+------+---------------+------+---------+-------+--------+----------+-----------------------+ Taxonomy upgrade extras: Optimizernullindexmariadb

MariaDB/MySQL Schulungstermine 2019

Fri, 2018-10-05 10:54

Jetzt sind auch noch die letzten MariaDB und MySQL Schulungstermine für 2019 festgelegt und veröffentlicht.

Mit unseren drei Schulungspartnern in Essen, Köln und Berlin bietet FromDual zur Zeit insgesamt 12 öffentliche Schulungen zum Thema MariaDB und MySQL an.

Es sind dies:


Diese Schulungen finden in deutsch statt. Auf Wunsch können auch Schulungen in englisch angeboten werden.

Was bleibt übrig für 2018?

Noch im Jahr 2018 werden 5 weitere Schulungen durchgeführt. Diese finden alle sicher statt!

Es sind dies:


In diesen Schulungen sind noch vereinzelt Plätze frei. Habt Ihr Eure MariaDB/MySQL Schulung für 2018 schon bezogen?

Bei Fragen zu den MariaDB oder MySQL Schulungen hilft Euch das FromDual Schulungsteam gerne weiter!

Taxonomy upgrade extras: galera cluster schulungtrainingmysql trainingmariadb traininggalera cluster trainingschulungmysql schulungmariadb schulung

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