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  • MySQL 8.0 InnoDB Cluster – the quick hands-on manual
    I’m just back from a trip in Barcelona where I presented MySQL 8.0 InnoDB Cluster (at dataops and Barcelona MySQL Meetup) and the majority of feedback was great, but I also had some comments on the demos I showed. The first one was: This is a joke of course (maybe it’s true for some), people found it very easy and they liked it. But then, the second one was that all I showed wasn’t easy to find, some people who already played with the solution didn’t succeeded in creating a cluster so easily… not because they had errors or encountered bugs, but more because they just didn’t know how to do it. The goal of this blog post is to illustrate how to create a MySQL 8.0 InnoDB Cluster very quickly using the new MySQL Shell only ! Initial environment We have 3 MySQL 8.0.11 instances running: mysql1, mysql2 and mysql3 They can all communicate to each others and they have a user with all privileges created on each of them : clusteradmin. Nothing else has been changed, no configuration file has been modified. The only important thing is that if you have created the admin user on them individually, just run RESET MASTER on all the instances. Quick Cluster Creation Let’s connect to one instance (doesn’t matter which one), and let’s create the cluster. I will list all commands needed to create the cluster very quickly and on a next post I will explain them in more details: Connection using the Shell MySQL JS> \c clusteradmin@mysql1 Creating a session to 'clusteradmin@mysql1' Enter password: **** Fetching schema names for autocompletion... Press ^C to stop. Your MySQL connection id is 10 (X protocol) Server version: 8.0.11 MySQL Community Server - GPL No default schema selected; type \use to set one. MySQL [mysql1+ ssl] JS> MySQL Configuration MySQL [mysql1+ ssl] JS> dba.configureInstance('clusteradmin@mysql1',{'restart': true}) You will prompted to validate the changes and if a restart of MySQL is required, it will happen (if you use a default MySQL installation, 3 settings will be changed and a restart will be required). And you need to configure all the other nodes that you want to be part of the cluster: MySQL [mysql1+ ssl] JS> dba.configureInstance('clusteradmin@mysql2',{'restart': true}) MySQL [mysql1+ ssl] JS> dba.configureInstance('clusteradmin@mysql3',{'restart': true}) Cluster Creation When the servers are restarted, just connect again to one of them using the Shell and create the cluster: MySQL [mysql1+ ssl] JS> \c clusteradmin@mysql1 MySQL [mysql1+ ssl] JS> cluster=dba.createCluster('MyCluster') Now you already have a cluster but with only one membere, you can verify this using the status() method of the cluster object we created: MySQL [mysql1+ ssl] JS> cluster.status() { "clusterName": "MyCluster", "defaultReplicaSet": { "name": "default", "primary": "mysql1:3306", "ssl": "REQUIRED", "status": "OK_NO_TOLERANCE", "statusText": "Cluster is NOT tolerant to any failures.", "topology": { "mysql1:3306": { "address": "mysql1:3306", "mode": "R/W", "readReplicas": {}, "role": "HA", "status": "ONLINE" } } }, "groupInformationSourceMember": "mysql://clusteradmin@mysql1:3306" } Add the other members Now it’s time to add the 2nd and 3rd member to the new cluster: MySQL [mysql1+ ssl] JS> cluster.addInstance('clusteradmin@mysql2:3306') MySQL [mysql1+ ssl] JS> cluster.addInstance('clusteradmin@mysql3:3306') Please, pay attention that here the port for MySQL standard protocol (3306) is required. Check the cluster We can verify our cluster using again the status() method: MySQL [mysql1+ ssl] JS> cluster.status() { "clusterName": "MyCluster", "defaultReplicaSet": { "name": "default", "primary": "mysql1:3306", "ssl": "REQUIRED", "status": "OK", "statusText": "Cluster is ONLINE and can tolerate up to ONE failure.", "topology": { "mysql1:3306": { "address": "mysql1:3306", "mode": "R/W", "readReplicas": {}, "role": "HA", "status": "ONLINE" }, "mysql2:3306": { "address": "mysql2:3306", "mode": "R/O", "readReplicas": {}, "role": "HA", "status": "ONLINE" }, "mysql3:3306": { "address": "mysql3:3306", "mode": "R/O", "readReplicas": {}, "role": "HA", "status": "ONLINE" } } }, "groupInformationSourceMember": "mysql://clusteradmin@mysql1:3306" } And voilà ! We have a 3 node MySQL 8.0 InnoDB Cluster ! Minimal Commands Summary connect to mysql1: \c clusteradmin@mysql1 configure mysql1: dba.configureInstance('clusteradmin@mysql1',{'restart': true}) configure mysql2: dba.configureInstance('clusteradmin@mysql2',{'restart': true}) configure mysql3: dba.configureInstance('clusteradmin@mysql3',{'restart': true}) connect to mysql1 (after restart): \c clusteradmin@mysql1 create cluster: dba.createCluster('MyCluster') add mysql2 to the cluster: cluster.addInstance('clusteradmin@mysql2:3306') add mysql3 to the cluster: cluster.addInstance('clusteradmin@mysql3:3306')

  • On Partitioning in MySQL
    Back in April I was preparing for vacations that my wife and I planned to spend in UK. Among other things planned I wanted to visit a customer's office in London and discuss few MySQL and MariaDB related topics, let's call them "stories". I tried to prepare myself for the discussion and collected a list of known active bugs (what else could I do as MySQL entomologist) for each of them. Surely live discussion was not suitable to share lists of bugs (and for some "stories" they were long), so I promised to share them later, in my blog. Time to do what I promised had finally come!One of the stories we briefly discussed was "partitioning story". Right now I can immediately identify at least 47 active MySQL bugs in the related category.  While preparing I checked the same list and picked up 15 or so bug reports that had to illustrate my points. Let me share them here in no specific order, and add few more.In April the latest still active bug in partitioning reported by MySQL community was  Bug #88916 - "Assertion `table->s->db_create_options == part_table->s->db_create_options'", from my colleague Elena Stepanova. Note a very simple test case that leads to assertion in debug builds, immediately verified.Recently two more bugs were reported. Reporter of Bug #91190 - "DROP PARTITION and REORGANIZE PARTITION are slow" suspects a performance regression in MySQL 8.0.11. I've subscribed to this bug and is following the progress carefully. Same with Bug #91203 - "For partitions table, deal with NULL with is mismatch with reference guide". I think what happens with NULL value and range partitioning perfectly matches the manual, but the fact that INFORMATION_SCHEMA.PARTITIONS table may return wrong information after dropping partition with NULL value is somewhat unexpected.Now back to the original lists for the "story" I prepared in April: Bug #60023 - "No Loose Index Scan for GROUP BY / DISTINCT on InnoDB partitioned table". It was reported by Rene' Cannao' and since 2013 I strongly suspect that it's fixed in MySQL 5.6+ or, as noted in another comment, may depend on statistics properly collected for the table. Still the status remains "Verified". Bug #78164 - "alter table command affect partitioned table data directory". Your custom DATA DIRECTORY settings may get lost when ALTER is applied to the whole table. Quick test shows that at least in MariaDB 10.3.7 this is no longer the case. The bug is still "Verified". Bug #85126 - "Delete by range in presence of partitioning and no PK always picks wrong index". It was reported by Riccardo Pizzi 16 months ago, immediately verified (without explicit list of versions affected, by the way). One more case when ordering of indexes in CREATE TABLE may matter... Bug #81712 - "lower_case_table_names=2 ignored on ADD PARTITION on Windows". Who cares about Windows these days? Bug #84356 - "General tablespace table encryption". It seems partitioning allows to overcome documented limitation. If this is intended, then the manual is wrong, otherwise I suspect the lack of careful testing of partitioning integration with other features. Bug #88673 - "Regression CREATE TBL from 5.7.17 to 20 (part #1: innodb_file_per_table = ON)." I've probably mentioned this bug reported by Jean-François Gagné in more than one blog post already. Take care and do not use long partition names. Bug #85413 - "Failing to rename a column involved in partition". As simple as it sounds, and it still happens. Bug #83435 - "ALTER TABLE is very slow when using PARTITIONED table". It was reported by Roel Van de Paar back in 2016 and still remains "Verified". Bug #73084 - "Exchanging partitions defined with DATA DIRECTORY and INDEX DIRECTORY options". The bug still remains "Open" (see Bug #77772 also). Bug #73648 - "innodb table replication is very slow with some of the partitioned table". It seems to be fixed last year as internal Bug #25687813 (see release notes for 5.6.38), but nobody cares to find this older duplicate and change its status or re-verify it. Bug #83750 - "Import via TTS of a partitioned table only uses 1 cpu core". This feature requested by Daniël van Eeden makes a lot of sense. I truly hope to see parallel operations implemented for partitioned tables in GA MySQL versions (as I saw some parallel processing for partitions done for some upcoming "6.1" or so version back in 2008 in Riga during the MySQL's last company meeting I've attended). Bug #64498 - "Running out of file handles when ALTERing partitioned MyISAM table". Too many file handles are needed. This is a documented limitation that DBAs should still take into account. I also prepared a separate small list of partition pruning bugs: Bug #83248 - "Partition pruning is not working with LEFT JOIN". I've reported it back in 2016 and it is still not fixed. There are reasons to think it is not so easy. Bug #75085 - "Partition pruning on key partitioning with ENUM". It was reported by  Daniël van Eeden back in 2014! Bug #77318 - "Selects waiting on MDL when altering partitioned table". One of the worst expectations DBA may have is that partitioned tables help to workaround "global" MDL locks because of partition pruning! This is not the case. Does this story have any moral? I think so, and for me it's the following: Partitioning bugs do not get proper attention from Oracle engineers. We see bugs with wrong status and even a bug with a clear test case and a duplicate that is "Open" for 4 years. Some typical use cases are affected badly, and still no fixes (even though since 5.7 we have native partitioning in InnoDB and changing implementation gave good chance to review and either fix or re-check these bugs). MySQL DBAs should expect all kinds of surprises when running usual DDL statements (ALTER TABLE to add column even) with partitioned tables. In the best case DDL is just unexpectedly slow for them. Partition pruning may not work they way one expects. We miss parallel processing for partitioned tables. They should allow to speed up queries and DDL, not to slow them down instead... One can suspect that there is no careful internal testing performed on integration of partitioning with other features, or even basic partition maintenance operations.

  • Not a Fan of Redhat RPMs Today or Why No Follow Up for RH/Centos/Fedora from Last Blog
    I received a lot of good feedback Building the PHP MySQL XDevAPI PECL Extension on MySQL 8.0.11 and PHP 7.2 for the MySQL Document Store including a few folks asking if I could document that it takes to get the MySQL X DevAPI working with an RPM based Linux distro.Well I'd really like to.  But I can't.Redhat Linux 4 I still remember getting my copy of Redhat Linux 4.0 (not RHEL -- no enterprise thoughts in those days)  It was January 1997 and I installed it the week before Rehaht 4.1 came out.  I thought that RPMs were much better than the old 'unzip the tar file;./configure; make install' circus. I thought Redhat was pretty cool. Heck I even became a RHCE.   Then I found the Debian variants easier to work with and more up to date.  My not so humble opinion is that Ubuntu is the best all around Linux distro around. But there are a lot of RPM based systems out there and I need to be able to show how to get the MySQL X Devapi working on them.  But it ain't easy. Step 1 Install CentOS 7 I had not installed CentOS in some time and it installed fairly nicely or as nice as Ubuntu.   So no problem there, Step 2 What is that Deb package Called in RPM speak? Here is where the wagon goes off the rails. TO get the developer tools you must sudo yum -y groupinstall  'Development Tools'.  Then you get to download the OpenSSL tarball 'cause there is not one RPM for CentOS 7 (considering its popularity I was gobsmacked to discover this lacking). Next was loading the protobuf-devel package.   But when I try to run the PECL install mysql_xdevapi I run into a compiler error.  Well, it is Friday afternoon and my frustration/inexperience with recent RPM software is telling me to call it a week. I will try again later.  If you are more up to speed on RPMs and want to provide guidance for me please do so.  If not have a good weekend!

  • Getting started with Orchestrator
    Orchestrator is a MySQL high availability and replication management tool. In this blog post, we will cover the first steps for getting started with it on an existing topology. The code examples assume you are running Centos 7, but the general steps should be similar if you are running other operating system versions/flavors. Prep work 1. Create a MySQL user on each of your database servers. Orchestrator will connect with this user to discover the topology and to perform any changes you tell it to make. CREATE USER 'orchestrator'@'%' IDENTIFIED BY '****'; GRANT SUPER, PROCESS, REPLICATION SLAVE, RELOAD ON *.* TO 'orchestrator'@'%'; GRANT SELECT ON mysql.slave_master_info TO 'orchestrator'@'%'; GRANT SELECT ON meta.* TO 'orchestrator'@'%'; Note: Orchestrator reads replication credentials stored in mysql.slave_master_info table, which implies you need to set up your servers with master_info_repository = ‘TABLE’ option if you want Orchestrator to be able to make topology changes on your behalf. 2. (Optional) Create a table to store the cluster name on each of your database servers. The idea is that if you set this up on each of your database servers, Orchestrator will pick up the cluster name automatically. While you could skip this step and just rename the clusters via the GUI later, it is a nice to have. CREATE DATABASE meta; CREATE TABLE meta.cluster ( anchor TINYINT NOT NULL, cluster_name VARCHAR(128) CHARSET ascii NOT NULL DEFAULT '', cluster_domain VARCHAR(128) CHARSET ascii NOT NULL DEFAULT '', PRIMARY KEY (anchor) ) ENGINE=InnoDB DEFAULT CHARSET=utf8; INSERT INTO meta.cluster (anchor, cluster_name, cluster_domain) VALUES (1, 'testcluster', 'example.com'); Installation steps 1. Get the prerequisites. Orchestrator client requires jq package, which is available from epel repo, so let’s install that first: sudo yum install epel-release sudo yum install jq 2. Install Orchestrator. Orchestrator is readily available as .deb or .rpm package so let’s use that: sudo yum install https://github.com/github/orchestrator/releases/download/v3.0.11/orchestrator-3.0.11-1.x86_64.rpm 3. Prepare the configuration file. Let’s start by copying the sample config file: cp /usr/local/orchestrator/orchestrator-sample.conf.json /etc/orchestrator.conf.json There are a lot of settings we can tweak, but to get started, we need to config the following values: “MySQLTopologyUser” “MySQLTopologyPassword” These are the ones we defined above. “DetectClusterAliasQuery” We have to define a query that will let Orchestrator figure out the cluster name based on the table we created in the previous step. “BackendDB” “SQLite3DataFile” You can use different backends for Orchestrator metadata. For simplicity, I suggest using SQLite which requires only the two lines above. Here’s a complete configuration file: { "Debug": true, "EnableSyslog": false, "ListenAddress": ":3000", "MySQLTopologyUser": "orchestrator", "MySQLTopologyPassword": "****", "MySQLTopologyCredentialsConfigFile": "", "MySQLTopologySSLPrivateKeyFile": "", "MySQLTopologySSLCertFile": "", "MySQLTopologySSLCAFile": "", "MySQLTopologySSLSkipVerify": true, "MySQLTopologyUseMutualTLS": false, "MySQLOrchestratorHost": "127.0.0.1", "MySQLOrchestratorPort": 3306, "MySQLOrchestratorDatabase": "orchestrator", "MySQLOrchestratorUser": "orc_server_user", "MySQLOrchestratorPassword": "orc_server_password", "MySQLOrchestratorCredentialsConfigFile": "", "MySQLOrchestratorSSLPrivateKeyFile": "", "MySQLOrchestratorSSLCertFile": "", "MySQLOrchestratorSSLCAFile": "", "MySQLOrchestratorSSLSkipVerify": true, "MySQLOrchestratorUseMutualTLS": false, "MySQLConnectTimeoutSeconds": 1, "DefaultInstancePort": 3306, "DiscoverByShowSlaveHosts": true, "InstancePollSeconds": 5, "UnseenInstanceForgetHours": 240, "SnapshotTopologiesIntervalHours": 0, "InstanceBulkOperationsWaitTimeoutSeconds": 10, "HostnameResolveMethod": "default", "MySQLHostnameResolveMethod": "@@hostname", "SkipBinlogServerUnresolveCheck": true, "ExpiryHostnameResolvesMinutes": 60, "RejectHostnameResolvePattern": "", "ReasonableReplicationLagSeconds": 10, "ProblemIgnoreHostnameFilters": [], "VerifyReplicationFilters": false, "ReasonableMaintenanceReplicationLagSeconds": 20, "CandidateInstanceExpireMinutes": 60, "AuditLogFile": "", "AuditToSyslog": false, "RemoveTextFromHostnameDisplay": ".mydomain.com:3306", "ReadOnly": false, "AuthenticationMethod": "", "HTTPAuthUser": "", "HTTPAuthPassword": "", "AuthUserHeader": "", "PowerAuthUsers": [ "*" ], "ClusterNameToAlias": { "127.0.0.1": "test suite" }, "SlaveLagQuery": "", "DetectClusterAliasQuery": "SELECT ifnull(max(cluster_name), '''') as cluster_alias from meta.cluster where anchor=1;", "DetectClusterDomainQuery": "", "DetectInstanceAliasQuery": "", "DetectPromotionRuleQuery": "", "DataCenterPattern": "[.]([^.]+)[.][^.]+[.]mydomain[.]com", "PhysicalEnvironmentPattern": "[.]([^.]+[.][^.]+)[.]mydomain[.]com", "PromotionIgnoreHostnameFilters": [], "DetectSemiSyncEnforcedQuery": "", "ServeAgentsHttp": false, "AgentsServerPort": ":3001", "AgentsUseSSL": false, "AgentsUseMutualTLS": false, "AgentSSLSkipVerify": false, "AgentSSLPrivateKeyFile": "", "AgentSSLCertFile": "", "AgentSSLCAFile": "", "AgentSSLValidOUs": [], "UseSSL": false, "UseMutualTLS": false, "SSLSkipVerify": false, "SSLPrivateKeyFile": "", "SSLCertFile": "", "SSLCAFile": "", "SSLValidOUs": [], "URLPrefix": "", "StatusEndpoint": "/api/status", "StatusSimpleHealth": true, "StatusOUVerify": false, "AgentPollMinutes": 60, "UnseenAgentForgetHours": 6, "StaleSeedFailMinutes": 60, "SeedAcceptableBytesDiff": 8192, "PseudoGTIDPattern": "", "PseudoGTIDPatternIsFixedSubstring": false, "PseudoGTIDMonotonicHint": "asc:", "DetectPseudoGTIDQuery": "", "BinlogEventsChunkSize": 10000, "SkipBinlogEventsContaining": [], "ReduceReplicationAnalysisCount": true, "FailureDetectionPeriodBlockMinutes": 60, "RecoveryPollSeconds": 10, "RecoveryPeriodBlockSeconds": 3600, "RecoveryIgnoreHostnameFilters": [], "RecoverMasterClusterFilters": [ ".*" ], "RecoverIntermediateMasterClusterFilters": [ "_intermediate_master_pattern_" ], "OnFailureDetectionProcesses": [ "echo 'Detected {failureType} on {failureCluster}. Affected replicas: {countSlaves}' >> /tmp/recovery.log" ], "PreFailoverProcesses": [ "echo 'Will recover from {failureType} on {failureCluster}' >> /tmp/recovery.log" ], "PostFailoverProcesses": [ "echo '(for all types) Recovered from {failureType} on {failureCluster}. Failed: {failedHost}:{failedPort}; Successor: {successorHost}:{successorPort}' >> /tmp/recovery.log" ], "PostUnsuccessfulFailoverProcesses": [], "PostMasterFailoverProcesses": [ "echo 'Recovered from {failureType} on {failureCluster}. Failed: {failedHost}:{failedPort}; Promoted: {successorHost}:{successorPort}' >> /tmp/recovery.log" ], "PostIntermediateMasterFailoverProcesses": [ "echo 'Recovered from {failureType} on {failureCluster}. Failed: {failedHost}:{failedPort}; Successor: {successorHost}:{successorPort}' >> /tmp/recovery.log" ], "CoMasterRecoveryMustPromoteOtherCoMaster": true, "DetachLostSlavesAfterMasterFailover": true, "ApplyMySQLPromotionAfterMasterFailover": true, "MasterFailoverDetachSlaveMasterHost": false, "MasterFailoverLostInstancesDowntimeMinutes": 0, "PostponeSlaveRecoveryOnLagMinutes": 0, "OSCIgnoreHostnameFilters": [], "GraphiteAddr": "", "GraphitePath": "", "GraphiteConvertHostnameDotsToUnderscores": true, "BackendDB": "sqlite", "SQLite3DataFile": "/usr/local/orchestrator/orchestrator.db" } 4. Prepare systemd script. At the time of this writing, a systemd script to manage start/stop of the service is not included. I set that up as follows: vi /etc/systemd/system/orchestrator.service [Unit] Description="orchestrator: MySQL replication management and visualization" After=syslog.target network.target [Service] Type=simple ExecStart=/usr/local/orchestrator/orchestrator --verbose http PIDFile=/var/run/orchestrator.pid WorkingDirectory=/usr/local/orchestrator [Install] WantedBy=multi-user.target 5. Reload the service so it reads the updated configuration file /etc/orchestrator.conf.json. service orchestrator reload That’s it for the installation steps. Using the GUI The first step is pointing Orchestrator to a starting host. It will then automatically discover any other hosts that are members of the same cluster by crawling up and down the replication chain. 1. Using a browser, open the GUI (by default port 3000) on the host where you installed Orchestrator:http://192.168.56.100:3000/ 2. Click ‘Discover‘ on the top bar, enter the ip address and port of any host you want, and hit the Submit button. 3. Click on Clusters -> Dashboard. After a few seconds, you should see the cluster being shown (refresh the page if needed). 4. Now click on the cluster name and you should see the details about all current members of the replication topology. The cluster should have automatically been named according to what is specified in meta.cluster table. You can also use the GUI to drag & drop to perform topology changes, provided you are using GTID or pseudo-GTID (which is a topic for a different post). Closing thoughts Orchestrator is rapidly becoming the go-to topology management tool in the MySQL world. I encourage you to start playing with it as soon as possible. If you are interested in learning more, I suggest you also check out the following posts in the Pythian blog. Happy Orchestrating! MySQL High availability with HAProxy, Consul and Orchestrator Graceful master switchover with ProxySQL and Orchestrator  

  • Back to basics: Isolation Levels In MySQL
    In this blog, we will see the very basic thing “I” of “ACID” and an important property of Transaction ie., “ISOLATION” The isolation defines the way in which the MySQL server (InnoDB) separates each transaction from other concurrent running transaction in the server and also ensures that the transactions are processed in a reliable way. If transactions are not isolated then one transaction could modify the data that another transaction is reading hence creating data inconsistency. Isolation levels determine how isolated the transactions are from each other. MySQL supports all four the isolation levels that SQL-Standard defines.The four isolation levels are READ UNCOMMITTED READ COMMITTED REPEATABLE READ SERIALIZABLE The Isolation level’s can be set globally or session based on our requirements.     Choosing the best isolation level based, have a great impact on the database, Each level of isolation comes with a trade-off, let’s discuss on each of them, READ UNCOMMITTED: In READ-UNCOMMITTED isolation level, there isn’t much isolation present between the transactions at all, ie ., No locks. A transaction can see changes to data made by other transactions that are not committed yet. This is the lowest level in isolation and highly performant since there is no overhead of maintaining locks, With this isolation level, there is always for getting a “Dirty-Read” That means transactions could be reading data that may not even exist eventually because the other transaction that was updating the data rolled-back the changes and didn’t commit. lest see the below image for better understanding Suppose a transaction T1 modifies a row if a transaction T2 reads the row and sees the modification even though T1 has not committed it, that is a dirty read, the problem here is if T1 rolls back, T2 doesn’t know that and will be in a state of “totally perplexed” READ COMMITTED: IN READ-COMMITTED isolation level, the phenomenon of dirty read is avoided, because any uncommitted changes are not visible to any other transaction until the change is committed. This is the default isolation level with most of popular RDBMS software, but not with MySQL. Within this isolation level, each SELECT uses its own snapshot of the committed data that was committed before the execution of the SELECT. Now because each SELECT has its own snapshot, here is the trade-off now, so the same SELECT, when running multiple times during the same transaction, could return different result sets. This phenomenon is called non-repeatable read. A non-repeatable occurs when a transaction performs the same transaction twice but gets a different result set each time. Suppose T2 reads some of the rows and T1 then change a row and commit the change, now T2 reads the same row set and gets a different result ie.., the initial read is non-repeatable. Read-committed is the recommended isolation level for Galera ( PXC, MariaDB Cluster ) and InnoDB clusters. REPEATABLE READ: In REPEATABLE-READ isolation level, the phenomenon of non-repeatable read is avoided. It is the default isolation in MySQL.This isolation level returns the same result set throughout the transaction execution for the same SELECT run any number of times during the progression of a transaction. This is how it works, a snapshot of the SELECT is taken the first time the SELECT is run during the transaction and the same snapshot is used throughout the transaction when the same SELECT is executed. A transaction running in this isolation level does not take into account any changes to data made by other transactions, regardless of whether the changes have been committed or not. This ensures that reads are always consistent(repeatable). Maintaining a snapshot can cause extra overhead and impact some performance Although this isolation level solves the problem of non-repeatable read, another possible problem that occurs is phantom reads. A Phantom is a row that appears where it is not visible before. InnoDB and XtraDB solve the phantom read problem with multi-version concurrency control. REPEATABLE READ is MySQL’s default transaction isolation level. SERIALIZABLE SERIALIZABLE completely isolates the effect of one transaction from others. It is similar to REPEATABLE READ with the additional restriction that row selected by one transaction cannot be changed by another until the first transaction finishes. The phenomenon of phantom reads is avoided. This isolation level is the strongest possible isolation level. AWS Aurora do not support this isolation level.   Photo by Alberto Triano on Unsplash

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