Extractors exist for reading information from the following sources:

Once information has been recorded into THL, particularly when that information has been recorded in row-based format, it is possible to apply that information out to a variety of different targets, both transactional and SQL based solutions, and also NoSQL and analytical targets.

Available appliers include:

For more information on how the heterogeneous replicator works, see Section 2.8.1, “How Heterogeneous Replication Works”. For more information on the batch applier, which works with datawarehouse targets, see Section 5.6, “Batch Loading for Data Warehouses”.

Tungsten Replicator operates by reading information from the source database and transferring that information to the Transaction History Log (THL).

Each transaction within the THL includes the SQL statement or the row-based data written to the database. The information also includes, where possible, transaction specific options and metadata, such as character set data, SQL modes and other information that may affect how the information is written when the data is applied. The combination of the metadata and the global transaction ID also enable more complex data replication scenarios to be supported, such as Composite Active/Active, without fear of duplicating statement or row data application because the source and global transaction ID can be compared.

In addition to all this information, the THL also includes a timestamp and a record of when the information was written into the database before the change was extracted. Using a combination of the global transaction ID and this timing information provides information on the latency and how up to date a dataserver is compared to the original datasource.

Depending on the underlying storage of the data, the information can be reformatted and applied to different data servers. When dealing with row-based data, this can be applied to a different type of data server, or completely reformatted and applied to non-table based services such as MongoDB.

THL information is stored for each replicator service, and can also be exchanged over the network between different replicator instances. This enables transaction data to be exchanged between different hosts within the same network or across wide-area-networks.

Filtering within the replicator enables the information within the THL to be removed, augmented, or modified as the information is transferred within and between the replicators.

During filtering, the information in the THL can be modified in a host of different ways, including but not limited to:

The format, content, and structure of the data and the THL can be modified and new data can even be created through the filters.

For more information on the filters available, and how to use them, see Chapter 10, Replication Filters.

To use the TAR/GZipped packages, download the files to your machine and unpack them:

shell> cd /opt/continuent/software
shell> tar zxf tungsten-replicator-6.1.24-6.tar.gz

This will create a directory matching the downloaded package name, version, and build number from which you can perform an install using either the INI file or command-line configuration. To use, you will need to use the tpm command within the tools directory of the extracted package:

shell> cd tungsten-replicator-6.1.24-6

The RPM packages can be used for installation, but are primarily designed to be in combination with the INI configuration file.

Installation

Installing the RPM package will do the following:

Although the RPM packages complete a number of the pre-requisite steps required to configure your cluster, there are additional steps, such as configuring ssh, that you still need to complete. For more information, see Appendix B, Prerequisites.

By using the package files you are able to setup a new server by creating the /etc/tungsten.ini file and then installing the package. Any output from the tpm command will go to /opt/continuent/service_logs/rpm.output.

root-shell> rpm --import http://www.continuent.com/RPM-GPG-KEY-continuent

root-shell> gpg --keyserver keyserver.ubuntu.com --recv-key 7206c924

Once an INI file has been created and the packages are available, the installation can be completed using:

Upgrades

If you upgrade to a new version of the RPM package it will do the following:

The tpm update will restart all Continuent Tungsten services so you do not need to do anything after upgrading the package file.

In this section we identify the best practices for performing a Tungsten Software upgrade.

WHY is it ok to upgrade and restart everything all at once?

Let’s look at each component to examine what happens during the upgrade, starting with the Manager layer.

Once the cluster is in Maintenance mode, the Managers cease to make changes to the cluster, and therefore Connectors will not reroute traffic either.

Since Manager control of the cluster is passive in Maintenance mode, it is safe to stop and restart all Managers - there will be zero impact to the cluster operations.

The Replicators function independently of client MySQL requests (which come through the Connectors and go to the MySQL database server), so even if the Replicators are stopped and restarted, there should be only a small window of delay while the replicas catch up with the Primary once upgraded. If the Connectors are reading from the Replicas, they may briefly get stale data if not using SmartScale.

Finally, when the Connectors are upgraded they must be restarted so the new version can take over. As discussed in this blog post, Zero-Downtime Upgrades, the Tungsten Cluster software upgrade process will do two key things to help keep traffic flowing during the Connector upgrade promote step:

To remove a datasource from an existing deployment there are two primary stages, removing it from the active service, and then removing it from the active configuration.

For example, to remove host6 from a service:

Now the node has been removed from the active dataservice, the host must be removed from the configuration.

Tungsten Replicator for MySQL operates by

The following diagrams show these two methods of extraction

Figure 2.1. Internals: MySQL Extraction

Figure 2.2. Internals: Amazon Aurora/Remote Database, Offboard Extraction

Tungsten Replicator for MySQL is supported within the following environments:

In addition, the following requirements and limitations are in effect:

The flexibility of the replicator allows you to install the software in a number of ways to fit into a number of possible limitations or restrictions you may be faced with, in addition to a number of flexible topologies. These are outlined below

There are a number of different methods in which Tungsten Replicator can be configured, review Section 2.7.2, “Understanding Deployment Models” for full details of the differences between each deployment style. The following sections explain the different topology styles that can be deployed

2.7.3.1. Simple Primary/Replica Topology

Primary/Replica is the simplest and most straightforward of all replication scenarios, and also the basis of all other types of topology. The fundamental basis for the Primary/Replica topology is that changes in the Source are distributed and applied to the each of the configured Targets.

Figure 2.3. Topologies: Primary/Replica

2.7.3.2. Active/Active Topology

An active/active topology, relies on a number of individual services that are used to define a Primary/Replica topology between each group of hosts. In a three-node active/active setup, for example, three different services are created on each host, each service creates a Primary/Replica relationship between a primary host (itself) and the remote Targets. A change on any individual host will be replicated to the other databases in the topology creating the active/active configuration.

Figure 2.4. Topologies: Active/Active

2.7.3.3. Fan-Out Topology

The fan-out topology allows you to replicate from one single host out to two or more target hosts. Fan-out topologies are often in situations where you have different reporting requirements, for example, sales figures may need aggregating and reporting within a redshift environment but payroll information may need replicating to a MySQL environment for back office processing.

Figure 2.5. Topologies: Fan-Out

2.7.3.4. Fan-In Topology

The fan-in topology is the logical opposite of a Primary/Replica topology. In a fan-in topology, the data from two (or more) Sources is combined together on one Target. Fan-in topologies are often in situations where you have satellite databases, maybe for sales or retail operations, and need to combine that information together in a single database for processing.

Figure 2.6. Topologies: Fan-In

2.7.3.5. Replicating in/out of an existing Tungsten Cluster

If you have an existing cluster and you want to replicate the data out to a separate standalone server using Tungsten Replicator then you can create a cluster alias, and use a Primary/Replica topology to replicate from the cluster. This allows for THL events from the cluster to be applied to a separate server for the purposes of backup or separate analysis.

Figure 2.7. Topologies: Cluster-Extractor

Heterogeneous replication works slightly differently compared to the native MySQL to MySQL replication. This is because SQL statements, including both Data Manipulation Language (DML) and Data Definition Language (DDL) cannot be executed on a target system as they were extracted from the MySQL database. The SQL dialects are different, so that an SQL statement on MySQL is not the same as an SQL statement on Oracle, and differences in the dialects mean that either the statement would fail, or would perform an incorrect operation.

On targets that do not support SQL of any kind, such as MongoDB, replicating SQL statements would achieve nothing since they cannot be executed at all.

All heterogeneous replication deployments therefore use row-based replication. This extracts only the raw row data, not the statement information. Because it is only row-data, it can be easily re-assembled or constructed into another format, including statements in other SQL dialects, native appliers for alternative formats, such as JSON or BSON, or external CSV formats that enable the data to be loaded in bulk batches into a variety of different targets.

Once the service has been started, a quick view of the service status can be determined using trepctl:

shell> trepctl services
Processing services command...
NAME              VALUE
----              -----
appliedLastSeqno: 3593
appliedLatency  : 1.074
role            : master
serviceName     : alpha
serviceType     : local
started         : true
state           : ONLINE
Finished services command...

The key fields are:

More detailed status information can also be obtained. On the Extractor:

shell> trepctl status
Processing status command...
NAME                     VALUE
----                     -----
appliedLastEventId     : mysql-bin.000009:0000000000001033;0
appliedLastSeqno       : 3593
appliedLatency         : 1.074
channels               : 1
clusterName            : default
currentEventId         : mysql-bin.000009:0000000000001033
currentTimeMillis      : 1373615598598
dataServerHost         : host1
extensions             : 
latestEpochNumber      : 3589
masterConnectUri       : 
masterListenUri        : thl://host1:2112/
maximumStoredSeqNo     : 3593
minimumStoredSeqNo     : 0
offlineRequests        : NONE
pendingError           : NONE
pendingErrorCode       : NONE
pendingErrorEventId    : NONE
pendingErrorSeqno      : -1
pendingExceptionMessage: NONE
pipelineSource         : jdbc:mysql:thin://host1:3306/
relativeLatency        : 604904.598
resourcePrecedence     : 99
rmiPort                : 10000
role                   : master
seqnoType              : java.lang.Long
serviceName            : alpha
serviceType            : local
simpleServiceName      : alpha
siteName               : default
sourceId               : host1
state                  : ONLINE
timeInStateSeconds     : 604903.621
transitioningTo        : 
uptimeSeconds          : 1202137.328
version                : Tungsten Replicator 6.1.24 build 6
Finished status command...

For more information on using trepctl, see Section 8.19, “The trepctl Command”.

Definitions of the individual field descriptions in the above example output can be found in Section E.2, “Generated Field Reference”.

For more information on management and operational detailed for managing your replicator installation, see Chapter 7, Operations Guide.

The configuration of RDS and Aurora instances can be modified to change the parameters for MySQL instances, the Amazon equivalent of modifying the my.cnf file.

mysql> call mysql.rds_set_configuration('binlog retention hours', 48);

shell> wget http://s3.amazonaws.com/rds-downloads/RDSCli.zip
shell> unzip RDSCli.zip
shell> export AWS_RDS_HOME=/home/tungsten/RDSCli-1.13.002
shell> export PATH=$PATH:$AWS_RDS_HOME/bin

shell> rds-describe-db-instances --region=us-east-1

During the installation and startup, tpm will notify you of any problems that need to be fixed before the service can be correctly installed and started. If the service starts correctly, you should see the configuration and current status of the service.

If the installation process fails, check the output of the /tmp/tungsten-configure.log file for more information about the root cause.

The cluster should be installed and ready to use.

Configure the source and target hosts following the prerequisites outlined in Appendix B, Prerequisites then follow the appropriate steps for the required extractor topology outlined in Chapter 3, Deploying MySQL Extractors.

The data replicated from MySQL can be any data, although there are some known limitations and assumptions made on the way the information is transferred.

If your target is an Amazon RDS or Aurora Instance, that has not yet been created, follow the steps in Section 4.1.2, “Prepare Amazon RDS/Amazon Aurora”

If your target is a hosted MySQL environment, proceed to Section 4.1.3, “Install MySQL Applier”

The applier will read information from the Extractor and write database changes into the target instance.

To configure the Applier replicator for either local or remote MySQL or for Amazon RDS/Aurora, the process is the same, but with a slightly different configuration, this is outlined below:

If the installation process fails, check the output of the /tmp/tungsten-configure.log file for more information about the root cause.

The replicators can now be started using the replicator command.

The status of the replicator can be checked and monitored by using the trepctl command.

Replication to MySQL and Amazon based instances operates in the same manner as all other replication environments. The current status can be monitored using trepctl. On the Extractor:

shell> trepctl status
Processing status command...
NAME                     VALUE
----                     -----
appliedLastEventId     : mysql-bin.000043:0000000000000291;84
appliedLastSeqno       : 2320
appliedLatency         : 0.733
channels               : 1
clusterName            : alpha
currentEventId         : mysql-bin.000043:0000000000000291
currentTimeMillis      : 1387544952494
dataServerHost         : host1
extensions             : 
host                   : host1
latestEpochNumber      : 60
masterConnectUri       : thl://localhost:/
masterListenUri        : thl://host1:2112/
maximumStoredSeqNo     : 2320
minimumStoredSeqNo     : 0
offlineRequests        : NONE
pendingError           : NONE
pendingErrorCode       : NONE
pendingErrorEventId    : NONE
pendingErrorSeqno      : -1
pendingExceptionMessage: NONE
pipelineSource         : jdbc:mysql:thin://host1:13306/
relativeLatency        : 23.494
resourcePrecedence     : 99
rmiPort                : 10000
role                   : master
seqnoType              : java.lang.Long
serviceName            : alpha
serviceType            : local
simpleServiceName      : alpha
siteName               : default
sourceId               : host1
state                  : ONLINE
timeInStateSeconds     : 99525.477
transitioningTo        : 
uptimeSeconds          : 99527.364
useSSLConnection       : false
version                : Tungsten Replicator 6.1.24 build 6
Finished status command...

On the Applier, use trepctl and monitor the appliedLatency and appliedLastSeqno. The output will include the hostname of the Amazon RDS instance:

shell> trepctl status
Processing status command...
NAME                     VALUE
----                     -----
appliedLastEventId     : mysql-bin.000043:0000000000000291;84
appliedLastSeqno       : 2320
appliedLatency         : 797.615
channels               : 1
clusterName            : default
currentEventId         : NONE
currentTimeMillis      : 1387545785268
dataServerHost         : documentationtest.cnlhon44f2wq.eu-west-1.rds.amazonaws.com
extensions             : 
host                   : documentationtest.cnlhon44f2wq.eu-west-1.rds.amazonaws.com
latestEpochNumber      : 60
masterConnectUri       : thl://host1:2112/
masterListenUri        : thl://host2:2112/
maximumStoredSeqNo     : 2320
minimumStoredSeqNo     : 0
offlineRequests        : NONE
pendingError           : NONE
pendingErrorCode       : NONE
pendingErrorEventId    : NONE
pendingErrorSeqno      : -1
pendingExceptionMessage: NONE
pipelineSource         : thl://host1:2112/
relativeLatency        : 856.268
resourcePrecedence     : 99
rmiPort                : 10000
role                   : slave
seqnoType              : java.lang.Long
serviceName            : alpha
serviceType            : local
simpleServiceName      : alpha
siteName               : default
sourceId               : documentationtest.cnlhon44f2wq.eu-west-1.rds.amazonaws.com
state                  : ONLINE
timeInStateSeconds     : 461.885
transitioningTo        : 
uptimeSeconds          : 668.606
useSSLConnection       : false
version                : Tungsten Replicator 6.1.24 build 6
Finished status command...

The Redshift applier makes use of the JavaScript based batch loading system (see Section 5.6.4, “JavaScript Batchloader Scripts”). This constructs change data from the source-database. The change data is then loaded into staging tables, at which point a process will then merge the change data up into the base tables A summary of this basic structure can be seen in Figure 4.3, “Topologies: Redshift Replication Operation”.

Figure 4.3. Topologies: Redshift Replication Operation

Different object types within the two systems are mapped as follows:

The full replication of information operates as follows: