In MySQL 5.7, there is a new feature called Group replication used for fault tolerant system.
Group Replication Doc
I implemented the group replication with 1 master and 3 slaves and it working fine. But i feel it little slow. Slow means query taking time in execution on master. It may be because of master waits for acknowledgement from slave or time in certification acceptance etc.
I know it may be broad question but if you guide some parameters related to group replication to improve the performance then it will be helpful.
Thanks
As you say, the Master does have to communicate with its Slave(s). So, yes, that does slow down each transaction.
Each COMMIT is delayed by the coordination among the servers. So, two things might be possible in your app:
Fewer COMMITs; that is more statements in each transaction. (But not too many.)
More parallelism at the client, hence more transactions running in parallel.
Related
I am running a MySQL 5.5 Master-Slave setup. For avoiding too many hits on my master server, I am thinking of having one or may be more servers for MySQL and incoming requests will first hit the HAProxy and it accordingly forwards the requests either in round robin or any scheduling algorithm defined in HAProxy. So set up will be like -
APP -> API Gateaway/Server -> HAProxy -> Master Server1/Master Server2
So what can be pros and cons to this setup ?
Replication in MySQL is asynchronous by default, so you can't always assume that the replicas are in sync with their source.
If you intend to use your load-balancer to split writes over the two master instances, you could get into trouble with that because of MySQL's asynchronous replication.
Say you commit a row on master1 to a table that has a unique key. Then you commit a row with the same unique value to the same table on master2, before the change on master1 has been applied through replication. Both servers allowed the row to be committed, because as far as they knew, it did not violate the unique constraint. But then as replication tries to apply the change on each server, those changes do conflict with the row committed. This is called split-brain, and it's incredibly difficult to recover from.
If your load-balancer randomly sends some read queries to another instance, they might not return data that you just committed on the other instance. This is called replication lag.
This may or may not be a problem for your app, but it's likely that in your app, at least some of the queries require strong consistency, i.e. reading outdated results is not permitted. Other cases even with the same app may be more tolerant of some replication lag.
I wrote a presentation some years ago about splitting queries between source and replica MySQL instances: https://www.percona.com/sites/default/files/presentations/Read%20Write%20Split.pdf. The presentation goes into more details about the different types of tolerance for replication lag.
MySQL 8.0 has introduced a more sophisticated solution for all of these problems. It's called Group Replication, and it does its best to ensure that all instances are in sync all the time, so you don't have the risk of reading stale data or creating write conflicts. The downside of Group Replication is that to ensure no replication lag occurs, it may need to constrain your transaction throughput. In other words, COMMITs may be blocked until the other instances in the replication cluster respond.
Read more about Group Replication here: https://dev.mysql.com/doc/refman/8.0/en/group-replication.html
P.S.: Whichever solution you decide to pursue, I recommend you do upgrade your version of MySQL. MySQL 5.5 passed its end-of-life in 2018, so it will no longer get updates even for security flaws.
I am trying to understand what exactly are the limitations of using MongoDB as the primary database for a project I am working on, it can be hard to wade through the crap online to properly understand how it compares to a more traditional database choice of say MySQL.
From what I understand from reading about HADR configuration of
IBM DB2 - http://pic.dhe.ibm.com/infocenter/db2luw/v9r7/index.jsp?topic=%2Fcom.ibm.db2.luw.admin.ha.doc%2Fdoc%2Fc0011724.html,
MySQL - http://dev.mysql.com/doc/refman/5.5/en/replication-semisync.html
and MongoDB - http://docs.mongodb.org/manual/core/write-concern/
It seems that Replica Acknowledged http://docs.mongodb.org/manual/core/replica-set-write-concern/ is the highest level of write concern in a replica set.
Is replica acknowledged the equivalent to the synchronous level in DB2 and Semisynchronous level in MySQL?
No they are not.
IBM DB2 provides a way to make sure that all members of a replica set are upto speed at the same time, it is the same as MySQLs own synchronous replication. It ensures full consistentcy at all times throughout the slave set.
Semisynchronous replication again is not replica set majority either; from the documentation page:
The master waits after commit only until at least one slave has received and logged the events.
But then:
It does not wait for all slaves to acknowledge receipt, and it requires only receipt, not that the events have been fully executed and committed on the slave side.
In other words you have no idea whether or not any slaves actually performed the command. It is the same as w:0 or "unsafe" writes in MongoDB.
With majority you have an idea that every member you send to has actually performed your command as can be seen by a cute little diagram in the documentation: http://docs.mongodb.org/manual/core/replica-set-write-concern/#verify-write-operations
and if that doesn't convince you then the quote:
The following sequence of commands creates a configuration that waits for the write operation to complete on a majority of the set members before returning:
From the next paragraph should.
So MySQL semisynchronous is similar to majority but it isn't the same. DB2 is totally different.
The IBM documentation sums up the differences in replica/slave wirte concern quite well:
The more strict the synchronization mode configuration parameter value, the more protection your database solution has against transaction data loss, but the slower your transaction processing performance. You must balance the need for protection against transaction loss with the need for performance.
This applies to DB2, MySQL and MongoDB alike. You must choose.
I understand that mysql replication uses two different threads on slave -
Slave I/O thread to read binlog from master and write it to local relay log
Slave SQL thread to execute the sql statements from the local relay log. This thread is for executing update, delete and create sqls.
What about select queries on slave? Can SELECT queries interfere with the replication process? Or is there a different thread that execute SELECT queries?
I mean, can slow select queries on slave make the replication to lag behind master ?
In short queries can interfere with the replication it is not the threading that matters here but the locking being applied (ACID vs. threading). A update query from the master that is being replicated to the slave can be blocked by a select query on the slave. However the replication sub-system will deal with these query locking issues most of the time. If you don’t mind dirty reads you can set the transaction serialization isolation level on the slave to something less restrictive to mitigate the risk. However make sure dirty reads is acceptable see this link for more information: http://dev.mysql.com/doc/refman/5.0/en/set-transaction.html
You are concerned about lag and that is not something you can eliminate in any replication schema there will be lag. There is almost always a network in between the master and slave. This will introduce lag right from the start. For example large replicated statements could saturate the network bandwidth and this is probably going to happen more often than a query blocking the replication. Replication never was and never will be instantaneous. So your point about lag can be answered like this lag is something you HAVE to deal with not something you can completely eliminate.
Dont get me wrong replication can be fast but it is NEVER instantaneous.
Another thing to keep in mind is that replication can fail and you need to plan for that as well. It will happen at some point and being prepared for it is essential. So basically you will have lag no matter how you do replication and you need to be able to deal with it. Also be prepared for replication failing at some point and how you will recover from it.
While replication can be useful in many places you need to make sure you are preparing for it on many levels such as adequate network infrastructure, how to deal with it during disaster recovery(failover), monitoring it during production and how to get it back online when it breaks.
We have to show a difference to show the advantages of using replication. We have two computers, linked by teamviewer so we can show our class what we are doing exactly.
Is it possible to show a difference in performance? (How long it takes to execute certain queries?)
What sort queries should we test? (in other words, where is the difference between using/not using replication the biggest)
How should we fill our database? How much data should be there?
Thanks a lot!
I guess the answer to the above questions depends on factors such as which storage engine you are using, size of the database, as well as your chosen replication architecture.
I don't think replication will have much of an impact on query execution for simple master->slave architecture. If however, you have an architecture where there are two masters: one handling writes, replicating to another master which exclusively handles reads, and then replication to a slave which handles backups, then you are far more likely to be able to present some of the more positive scenarios. Have a read up on locks and storage engines, as this might influence your choices.
One simple way to show how Replication can be positive is to demonstrate a simple backup strategy. E.g. Taking hourly backups on a master server itself can bring the underlying application to a complete halt for the duration of the backup (Taking backups using mysqldump locks the tables so that no read/write operations can occur). Whereas replicating to a slave, then taking backups from there negates this affect.
If you want to show detailed statistics, it's probably better to look into some benchmarking/profiling tools (sysbench,mysqlslap,sql-bench to name a few). This can become quite complex though.
Also might be worth looking at the Percona Toolkit and the Percona monitoring plugins here: http://www.percona.com/software/
Replication has several advantages:
Robustness is increased with a master/slave setup. In the event of problems with the master, you can switch to the slave as a backup
Better response time for clients can be achieved by splitting the load for processing client queries between the master and slave servers
Another benefit of using replication is that you can perform database backups using a slave server without disturbing the master.
Using replication always a safe thing to do you should be replicating your Production server always incase of failure it will be helpful.
You can show seconds_behind_master value while showing replication performance, this shows indication of how “late” the slave is this value should not be more than 600-800 seconds but network latency does matter here.
Make sure that Master and Slave servers are configured correctly now
You can stop slave server and let Master server has some updates/inserts (bulk inserts) happening and now start slave server you will see larger seconds_behind_master value it should be keep on decreasing till reaches 0 value.
There is a tool called MONyog - MySQL Monitor and Advisor which shows Replication status in real-time.
Also what kind of replication to use whether statement based or row based has been explained here
http://dev.mysql.com/doc/refman/5.1/en/replication-sbr-rbr.html
I currently have a MySQL dual master replication (A<->B) set up and everything seems to be running swimmingly. I drew on the basic ideas from here and here.
Server A is my web server (a VPS). User interaction with the application leads to updates to several fields in table X (which are replicated to server B). Server B is the heavy-lifter, where all the big calculations are done. A cron job on server B regularly adds rows to table X (which are replicated to server A).
So server A can update (but never add) rows, and server B can add rows. Server B can also update fields in X, but only after the user no longer has the ability to update that row.
What kinds of potential disasters can I expect with this scenario if I go to production with it? Or does this seem OK? I'm asking mostly because I'm ignorant about whether any simultaneous operation on the table (from either the A copy or the B copy) can cause problems or if it's just operations on the same row that get hairy.
Dual master replication is messy if you attempt to write to the same database on both masters.
One of the biggest points of contention (and high blood pressure) is the use of autoincrement keys.
As long as you remember to set auto_increment_increment and auto_increment_offset, you can lookup any data you want and retrieve auto_incremented ids.
You just have to remember this rule: If you read an id from serverX, you must lookup needed data from serverX using the same id.
Here is one saving grace for using dual master replication.
Suppose you have
two databases (db1 and db2)
two DB servers (serverA and serverB)
If you impose the following restrictions
all writes of db1 to serverA
all writes of db2 to serverB
then you are not required to set auto_increment_increment and auto_increment_offset.
I hope my answer clarifies the good, the bad, and the ugly of using dual master replication.
Here is a pictorial example of 4 masters using auto increment settings
Nice article from Percona on this subject
Master-master replication can be very tricky, are you sure that this is the best solution for you ? Usually it is used for load-balancing purposes (e.g. round-robin connect to your db servers) and sometimes when you want to avoid the replication lag effect. A big known issue is the auto_increment problem which is supposedly solved using different offsets and increment value.
I think you should modify your configuration to simple master-slave by making A the master and B the slave, unless I am mistaken about the requirements of your system.
I think you can depend on
Percona XtraDB Cluster Feature 2: Multi-Master replication than regular MySQL replication
They promise the foll:
By Multi-Master I mean the ability to write to any node in your cluster and do not worry that eventually you get out-of-sync situation, as it regularly happens with regular MySQL replication if you imprudently write to the wrong server.
With Cluster you can write to any node, and the Cluster guarantees consistency of writes. That is the write is either committed on all nodes or not committed at all.
The two important consequences of Muti-master architecture.
First: we can have several appliers working in parallel. This gives us true parallel replication. Slave can have many parallel threads, and you can tune it by variable wsrep_slave_threads
Second: There might be a small period of time when the slave is out-of-sync from master. This happens because the master may apply event faster than a slave. And if you do read from the slave, you may read data, that has not changes yet. You can see that from diagram. However you can change this behavior by using variable wsrep_causal_reads=ON. In this case the read on the slave will wait until event is applied (this however will increase the response time of the read. This gap between slave and master is the reason why this replication named “virtually synchronous replication”, not real “synchronous replication”
The described behavior of COMMIT also has the second serious implication.
If you run write transactions to two different nodes, the cluster will use an optimistic locking model.
That means a transaction will not check on possible locking conflicts during individual queries, but rather on the COMMIT stage. And you may get ERROR response on COMMIT. I am highlighting this, as this is one of incompatibilities with regular InnoDB, that you may experience. In InnoDB usually DEADLOCK and LOCK TIMEOUT errors happen in response on particular query, but not on COMMIT. Well, if you follow a good practice, you still check errors code after “COMMIT” query, but I saw many applications that do not do that.
So, if you plan to use Multi-Master capabilities of XtraDB Cluster, and run write transactions on several nodes, you may need to make sure you handle response on “COMMIT” query.
You can find it here along with pictorial expln
From my rather extensive experience on this topic I can say you will regret writing to more than one master someday. It may be soon, it may not be for a long time, but it will happen. You will have two servers that each have some correct data and some wrong data, and you will either pick one as the authoritative source and throw the other away (probably without really knowing what you're throwing away) or you'll reconcile the two. No matter how you design it, you cannot eliminate the possibility of this happening, so it's a mathematical certainty that it will happen someday.
Percona (my employer) has handled probably several hundred cases of recovery after doing what you're attempting. Some of them take hours, some take weeks, one I helped with took a few months -- and that's with excellent tools to help.
Use a different replication technology or find a different way to do what you want to do. MMM will not help -- it will bring catastrophe sooner. You cannot do this with standard MySQL replication, with or without external tools. You need a replacement replication technology such as Continuent Tungsten or Percona XtraDB Cluster.
It's often easier to just solve the real need in some other fashion and give up multi-master writes, if you want to use vanilla MySQL replication.
and thanks for sharing my Master-Master Mysql cluster article. As Rolando clarified this configuration is not suitable for most production environment due to the limitation of autoincrement support.
The most adequate way to get a MySQL cluster is using NDB, which require at least 4 servers (2 management and 2 data nodes).
I have written a detailed article to get this running on two servers only, which is very similar to my previous article but using NDB instead.
http://www.hbyconsultancy.com/blog/mysql-cluster-ndb-up-and-running-7-4-and-6-3-on-ubuntu-server-trusty-14-04.html
Notice that I always recommend to analyse your needs and find out the most adequate solution, don't just look for available solutions and try to figure out if they fit with your needs or not.
-Hatem
I would highly recommend looking into a tool that will manage this for you. Multi-master replication can be very troublesome if things go wrong.
I would suggest something like Percona XtraDB Cluster. I've been following this project, and it looks very cool. I definitely think it will be a game changer in the MySQL world. It's still in beta though.